Bearing capacity of roads, railways and airfields.pdf

BEARING CAPACITY OF ROADS, RAILWAYS AND AIRFIELDS

PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON THE BEARING CAPACITY OF ROADS, RAILWAYS AND AIRFIELDS, CHAMPAIGN, ILLINOIS, USA, JUNE 29–JULY 2, 2009

Bearing Capacity of Roads, Railways and Airfields Editors Erol Tutumluer & Imad L. Al-Qadi Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

VOLUME I

CRC Press/Balkema is an imprint of the Taylor & Francis Group, an informa business © 2009 Taylor & Francis Group, London, UK Typeset by Vikatan Publishing Solutions (P) Ltd., Chennai, India Printed and bound in the USA by Edwards Brothers, Inc, Lillington, NC All rights reserved. No part of this publication or the information contained herein may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, by photocopying, recording or otherwise, without written prior permission from the publisher. Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers nor the author for any damage to the property or persons as a result of operation or use of this publication and/or the information contained herein. Published by: CRC Press/Balkema P.O. Box 447, 2300 AK Leiden, The Netherlands e-mail: [email protected] www.crcpress.com – www.taylorandfrancis.co.uk – www.balkema.nl ISBN: 978-0-415-87199-0 (set of 2 volumes + CD-ROM) ISBN: 978-0-415-80432-5 (vol 1) ISBN: 978-0-415-87200-3 (vol 2) ISBN: 978-0-203-86528-6 (ebook)

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Table of contents

Preface E. Tutumluer & I.L. Al-Qadi

XV

Organization

XVII

VOLUME I Keynote presentations Recent and landmark improvements in performance characterization of unbound aggregate bases and subbases and sublayers comprised of Chemically Stabilized Materials (CSMs) D.N. Little The performance of rail track incorporating the effects of ballast breakage, confining pressure and geosynthetic reinforcement B. Indraratna, S. Nimbalkar & D. Christie Airport pavement design for the 21st century S.K. Agrawal

3

5 25

Subgrade soils Improving subgrade strength and pavement performance by chemical treating subgrade soils N. Bandara & M.J. Grazioli Study of dry sludge stabilization from Water Treatment Plant (WTP) in Taiaçupeba to use as compacted soil in earthwork ditches R.M. Fortes, J.V. Merighi, D.R. Pauli, M.A.L. Barros, M.H. de Carvalho, N.C. Menetti, Á.S. Barbosa, F.V. Ribeiro & B.B. Bento Alternatives to heavy test rolling for cohesive subgrade assessment D.J. White, P.K.R. Vennapusa, H.H. Gieselman, L. Johanson & J. Siekmeier A comparative subgrade evaluation using CBR, vane shear, light weight deflectometer, and resilient modulus tests N. Garg, A. Larkin & H. Brar

29

37

45

57

Stabilization of clays using liquid enzymes Y. Yilmaz, A.G. Gungor & C. Avsar

65

The effect of moisture hysteresis on resilient modulus of subgrade soils C. Khoury & N. Khoury

71

Dynamic properties of a full weathering granite subgrade and other pavement materials studied by model tests J. Zou, Z. Li & X. Cao

V

79

The use of geofiber and synthetic fluid for stabilizing marginal soils K. Hazirbaba & B. Connor

89

Subgrade modification—practitioner’s experience T. McCleary

97

“Baku Bayil Yard Site” soil improvement geotechnical works E. Guler, A. Gure & E. Cetin

107

Resilient characteristics of bottom ash H.H. Titi, A.R. Coenen & M.B. Elias

117

Precision triaxial equipment for the evaluation of the elastic behavior of soils N. Araújo & A. Gomes Correia

125

Granular materials A performance study of different curing materials applied to soil-Portland cement base course cure R.M. Fortes & J.V. Merighi Pavement base unbound granular materials gradation optimization J.P. Bilodeau, G. Doré & P. Pierre

137 145

Influence of the macroscopic cohesion on the 3D FE modeling of a flexible pavement rut depth F. Allou, C. Petit, C. Chazallon & P. Hornych

155

Effect of grading and moisture on the deformation properties of unbound granular aggregates L.U. Mathisen

167

IDOT test loop: Evaluating the field performance of various dense graded aggregates G. Heckel

179

Analytical evaluation of unbound granular layers in regard to permanent deformation L.A.T. Brito, A.R. Dawson & P.J. Kolisoja

187

Processed Portuguese steel slag—A new geomaterial A. Gomes Correia, S.M. Reis Ferreira, A.J. Roque & A. Cavalheiro

197

Resilient modulus of hydraulically bound road base materials with high volume waste dust H. Al Nageim & P. Visulios

205

Characterizing natural and recycled granular materials for (sub)base layers of roads by cyclic triaxial testing C. Grégoire, B. Dethy, J. Detry & A. Gomes Correia

215

Resilient modulus of unbound base material containing extra waste Stancombe limestone dust B. Saghafi & H. Al Nageim

225

Characterizing aggregate permanent deformation behavior based on types and amounts of fines D. Mishra, E. Tutumluer, J. Kern & A. Butt

237

Asphalt mixtures Use of polymer modified binders to reduce rutting in Nordic asphalt pavements B.O. Lerfald, J. Aurstad & N.S. Uthus

VI

249

Contribution of asphalt mix components to permanent deformation resistance P.M. Muraya, A.A.A. Molenaar & M.F.C. van de Ven

259

A new rutting evaluation indicator for asphalt mixtures K. Su, L. Sun, Y. Hachiya & R. Maekawa

269

Evaluation of different predictive dynamic modulus models of asphalt mixtures used in Argentina F.O. Martínez & S.M. Angelone Development of wear resistant pavements using polymer modified binders R.G. Saba, L.J. Bakløkk, J. Aksnes & B.O. Lerfald Permanent deformation evaluation of Idaho Superpave mixes using the gyratory stability F. Bayomy, A. Abu Abdo & M.J. Santi

275 285

295

Prediction of the dynamic modulus of Superpave mixes A. Abu Abdo, F. Bayomy, R. Nielsen, T. Weaver, S.J. Jung & M.J. Santi

305

Laboratory evaluation of warm mix asphalt using Sasobit® S.W. Goh, Y. Liu & Z. You

315

Dynamic modulus prediction of asphalt concrete using three tensile tests S. Adhikari & Z. You

321

Assessing low temperature properties of asphalt materials by means of static testing techniques M. Wistuba, K. Mollenhauer & K. Metzker Ageing of stone mastic asphalt and evaluation of cracking resistance S. Büchler, K. Mollenhauer, M. Wistuba & P. Renken Fatigue resistance of hot mix asphalt at low temperatures—Is there a way to reduce the test efforts? K. Mollenhauer & M. Wistuba Hot mix asphalt produced from marble waste C. Gurer, H. Akbulut & A. Yildiz

327 339

349 359

Discrete element analysis of aggregate variability, blending, and fracture in asphalt mixture E. Masad, E. Mahmoud & S. Nazarian

367

Multidirectional behavior of bituminous mixture P. Clec’h, C. Sauzéat & H. Di Benedetto

377

Design of pavements containing foamed bitumen recycled layers M. Losa, R. Bacci, A. Terrosi Axerio & P. Leandri

387

Long-term study on asphalt mixture segregation in Connecticut: Preliminary results on use of MTV D.J. Nener-Plante & A. Zofka

397

In-situ measurement techniques and developments Development of the UK highways agency traffic speed deflectometer B. Ferne, P. Langdale, N. Round & R. Fairclough Implementation of a network-level falling weight deflectometer survey of Virginia’s interstate system B.K. Diefenderfer, T. Chowdhury & R.A. Shekharan

VII

409

419

Application of FBG strain sensors in the measurement of three-directional strains within asphalt pavement D. Zejiao, T. Yiqiu, C. Fengchen & L. Hao 3D visualization model of road surface X. Li, S. Ma & X. Hou

427 435

Three years of high speed deflectograph measurements of the Danish state road network S. Baltzer

443

A method for benefiting pavement quality assurance measures related to roughness condition surveys C. Plati & A. Loizos

451

Structural roadway assessment with frequency response function J.-M. Simonin, D. Lièvre & J.-C. Dargenton

459

Deflection measurement: The need of a continuous and full view approach J.-M. Simonin, L.-M. Cottineau, V. Muzet, C. Heinkele & Y. Guillard

467

Modeling & methods of functional testing Laboratory characterization of half-warm mix asphalts with high recycling rate by means of the factorial experiment design approach F. Olard, E. Beduneau, D. Bonneau, S. Dupriet & N. Seignez Viability of the use of construction and demolition debris in hot mix asphalt I. Pérez, M. Toledano & J. Gallego Thermal stresses of asphalt pavement with temperature-dependent modulus of elasticity Y. Zhong & L.Geng

479 487

495

Rigid pavement reinforcement: Modeling of structural behavior P. Domingos, M.L. Antunes & J.M.C. Neves

503

Development and testing of low noise pavements in Norway J. Aksnes, R.G. Saba & T. Berge

513

Roughness progression models by regression and artificial neural network techniques E. Taddesse & H. Mork

521

Joint modeling for JPCP: Successes and pending problems E.H. Guo

531

Mechanistic modelling of potential interlayer slip at base sub-base level E. Horak, J.W. Maina, S.E. Emery & B. Walker

543

PFC2D simulation research on vibrating compaction test of soil and rock aggregate mixture X. Jia, H. Chai, Z. Yan & Y. Zheng Axi-symmetric analyses of vertically inhomogeneous elastic multilayered systems J.W. Maina, Y. Ozawa & K. Matsui Models to estimate k subgrade reaction modulus values based on deflection basin parameters C.Y. Suzuki, C.R.G. Santos, S. Ferri, F.M. Lopes, R.T.G. Cruz & A.M. Azevedo

VIII

551 561

571

Application of gray theory in settlement forecast of rock-fill highway embankment X. Wang, W. Qin, M.C. Wang & Z. Wang

581

FEM analysis of the bearing plate deflection tests on rubblized concrete pavement Y. Liu, Y. Sheng & L. Wang

589

Data mining applied to compaction of geomaterials R. Marques, A. Gomes Correia & P. Cortez

597

Finite element analyses of pavement materials at or near failure: A constant bulk modulus approach C. Gonzalez & S. Jersey

607

Use of 3-dimensional discrete element model to examine aggregate layer particle movement due to load wander P.R. Donovan, E. Tutumluer & H. Huang

619

Backcalculation analyses of deflection measurements Backcalculation of the stiffnesses of cement treated base courses using artificial intelligence M. Miradi, A.A.A. Molenaar, M.F.C. van de Ven & S. Molenaar

633

Bearing capacity assessment of recycled asphalt pavements V. Papavasiliou & A. Loizos

643

Dynamic analysis of non-destructive tests W.T. van Bijsterveld & R.L. Álvarez Loranca

653

Automated pavement thickness evaluation for FWD backcalculation K.R. Maser, L.A. McGrath, B.C. Miller, H. Ceylan & G. Sanati

661

Analysis of FWD data and characterization of airfield pavement materials in New Mexico M.U. Ahmed, R. Bisht & R.A. Tarefder

669

SOFTSYS for backcalculation of full-depth asphalt pavement layer moduli O. Pekcan, E. Tutumluer & J. Ghaboussi

679

Deterministic-empirical backcalculation of LWD deflection basins R.N. Stubstad, H.C. Korsgaard, K. Olsen & J.P. Pedersen

689

New and/or innovative techniques in compaction & construction Long-term in-situ measurements of concrete culverts with high fills J. Vaslestad, G.Y. Yesuf & T.H. Johansen Research and applications of new pavement structure based on large stone porous asphalt mixture B. Yufeng, W. Songgen & G. Huber

697

707

Fiber-reinforced concrete pavement design and material requirements A. Bordelon & J.R. Roesler

717

Using falling weight deflectometer data for new construction interactive design C.A. Lenngren

729

Appraisal of density-based field compaction control test validity J. Sadrekarimi & S. Seyyedi

739

IX

Continuous compaction control: Preliminary data from a Delaware case study F.S. Tehrani & C.L. Meehan

745

Geostatistical analysis of roller-integrated continuous compaction control data N. Facas, M. Mooney & R. Furrer

755

Author index

763

VOLUME II Structural evaluation & performance prediction Evaluation of effectiveness of FWD use for assessment of pavement interlayer bond D. Sybilski, T. Mechowski & P. Harasim The use of impact-stiffness modulus outputs from FWD measurements to determine PCN in Israel M. Livneh

769

777

Temperature correction of falling weight deflectometer measurements E. Straube & D. Jansen

789

Nature resources and functional road design criteria C.A. Lenngren & R. Fredriksson

799

Lightweight deflectometers for quality assurance in road construction P.R. Fleming, M.W. Frost & J.P. Lambert

809

The use of surfacing service life as a parameter in pavement strengthening design G. Refsdal, R. Johansen & G. Berntsen

819

Going beyond elastic response while evaluating falling weight deflectometer data C.A. Lenngren

829

Pavement contribution to truck rolling resistance C.A. Lenngren

839

Structural assessment of the English strategic road network—latest developments B. Ferne, R. Sinhal & R. Fairclough

849

Practical use of light weight deflectometer for pavement design S. Baltzer, C. Hejlesen, H.C. Korsgaard & P.E. Jakobsen

859

Structural evaluation of rubblized concrete pavements in Iowa H. Ceylan, K. Gopalakrishnan & S. Kim

869

Structural evaluation of Full-Depth Reclamation in Virginia A.K. Apeagyei & B.K. Diefenderfer

879

Structural design systems for new construction & rehabilitation A probabilistic approach to flexible aircraft pavement thickness determination G.W. White

889

Comparison of design thickness between the 1993 AASHTO Guide and MEPDG for full depth reclamation pavement Y. Ji & T.E. Nantung

897

Dynamic response of rigid pavements under moving traffic loads with variable velocities Y. Zhong & L. Geng

907

X

Design of pavement rehabilitation to reduce the reflective cracking in pavements with cement stabilized bases E. Padilla

915

Verification of mechanistic-empirical pavement design guide for the state of New Jersey N. Siraj, Y.A. Mehta, K.M. Muriel & R.W. Sauber

921

Mechanistic evaluation of second generation preservation overlays D.A. Morian, S. Sadasivam, S.M. Stoffels, G. Chehab & T. Kumar

931

A robust approach for the evaluation of airport pavement bearing capacity Y.H. Lee, Y.B. Liu, J.D. Lin & H.W. Ker

941

Influence of unbound materials on flexible pavement performance: A comparison of the AASHTO and MEPDG methods C.W. Schwartz

951

Bearing capacity designs for challenging conditions & load effects The premature failure of slab pavements on heavily trafficked industrial sites C. Van Geem & O. De Myttenaere

963

The discussion on the “b” value of the axle load conversion in China X. Wang & L. Zhang

973

Load bearing analysis of EPS-block geofoam embankments D. Arellano & T.D. Stark

981

A review of the influence of chalk on pavement performance in the South East of England, UK M. Zohrabi

991

Design methodology based on strength and its application to full weathering granite used in highway subgrade Z. Li & C. Dong

1001

Sustainable reconstruction of highways with in-situ reclamation of materials stabilized for heavier loads H. Wen & T.B. Edil

1011

Estimating bearing capacity for opportune landing sites R. Affleck, L. Barna, S. Shoop & C. Ryerson

1019

Shear strength properties of naturally occurring bituminous sands J. Anochie-Boateng & E. Tutumluer

1029

Effects of bearing capacity and load transfer efficiency of jointed concrete pavements on reflective cracking in hot-mix asphalt overlays J. Baek & I.L. Al-Qadi

1039

Bearing capacity designs for climatic conditions Use of Ground Penetrating Radar for detection of salt concentration on Norwegian winter roads A. Lalagüe, I. Hoff, E. Eide & A. Svanekil Seasonal coefficients for the pavement roads in Polish climate conditions M. Graczyk

XI

1053 1063

Seal courses for a soft asphalt pavement with semi-rigid base in cold regions X. Wang, X. Zhang & Y. Tan

1073

Thermal stress analysis in ultra-thin whitetopping pavement J.R. Roesler & D. Wang

1079

Effect of a changed climate on gravel roads P.O. Aursand & I. Horvli

1091

Water impact on the structural behavior of a pavement structure S. Erlingsson

1101

Reinforcement of structural layers Investigation of the effect of a polypropylene fiber material on the shear strength and CBR characteristics of high plasticity Ankara clay M. Mollamahmutoglu & Y. Yilmaz

1113

Evaluation of geogrid displacement on subbase reinforcement using specially designed pullout test M.V. Akpinar & T. Sert

1117

Performance of flexible pavements reinforced with steel fabric S.F. Said, H. Carlsson & H. Hakim

1125

Evaluation of asphalt road pavement rehabilitation using steel mesh reinforcement J.M.C. Neves & A.R.D. Alves

1133

In-situ strain measurement during dynamic shear loading of an unbound geogrid reinforced pavement section B.R. Cox, B. Curry, C.M. Wood, C. Young & J.S. McCartney Experimental study on bearing capacity of geocell-reinforced bases S.K. Pokharel, J. Han, R.L. Parsons, Y. Qian, D. Leshchinsky & I. Halahmi

1143 1159

Utilization of recycled materials The influence of virgin aggregate content on the strength and modulus of cold in place reclaimed asphalt pavement H. Wang, P. Hao & K. Zhang

1169

Unbound crushed concrete in high volume roads—evaluation of field behavior and structural performance J. Aurstad, J.E. Dahlhaug & G. Berntsen

1177

Expansive characteristics of RAP materials for use as aggregates in the pavement substructure layers D. Deniz, E. Tutumluer & J.S. Popovics

1187

Study on fully and highly efficiently recycling of waste concrete L. Lu, Y. He & S. Hu

1197

Railroad track structures Evaluation of roadbed stiffness on bearing capacity of railroad ballast with discontinuous analysis T. Ishikawa, T. Kamei, E. Sekine & Y. Ohnishi

1207

Pressure measurements and structural performance of hot mixed asphalt railway trackbeds L.S. Bryson & J.G. Rose

1219

XII

Emerging trends for high-speed rail track superstructures—ballastless track as an alternative to the ballasted track A.M. Paixão, E.C. Fortunato & M.L. Antunes

1231

An innovative slab track test-line in China J. Ren, R. Xiang & B. Lechner

1243

Performance improvement of railroads over soft subgrades with geocell reinforcement S. Saride, A.J. Puppala, S. Pradhan & T.G. Sitharam

1253

Actions on railway track panel and ballast—behavior of the Hellenic limestone ballast K. Giannakos & A. Loizos

1263

Reducing track faults using polymer geocomposite technology P.K. Woodward, G. Medero & D.V. Griffiths

1273

Ballast evaluation and hot mix asphalt performance H.M. Lees

1283

Effects of incorporating a bituminous subballast layer on the deformation of railway trackbeds T. Ferreira, P.F. Teixeira & R. Cardoso

1291

Influence of the stiffness-damping coupling of the foundation in the performance of a high-speed train track J. Cunha & A. Gomes Correia

1303

Measurement of vibrations induced by high-speed trains J. Martins, A. Gomes Correia, L.F. Ramos, J. Marcelino, L. Caldeira & J. Delgado

1311

The use of biaxial geogrids for enhancing the performance of sub-ballast and ballast layers—previous experience and research J. Kwon & J. Penman

1321

Comparison of in situ performance-based tests methods to evaluate moduli of railway embankments A. Gomes Correia, J. Martins, L. Caldeira, E. Maranha das Neves & J. Delgado

1331

Railway bridge transition case study J.P. Hyslip, D. Li & C.R. McDaniel

1341

Comparison of coal dust fouled railroad ballast behavior—granite vs. limestone W. Dombrow, H. Huang & E. Tutumluer

1349

Full-scale testing Validation of NCAT structural test track experiment using INDOT APT facility E. Levenberg

1361

Construction and field performance of hot mix asphalt with moderate and high RAP contents R. West, N. Tran, A. Kvasnak, B. Powell & P. Turner

1373

Analysis of in-pavement sensor data for CC2 new rigid test items at the FAA National Airport Pavement Test Facility D.R. Brill & E.H. Guo

1383

Using the viscoelasticity and continuum damage theories to quantify the effects of loading speed in accelerated pavement testing results K.M. Theisen, D.R. Victorino, W.P. Nunez & J.A.P. Ceratti

1393

XIII

Full-scale aircraft tire pressure tests C. Fabre, J. Balay, P. Lerat & A. Mazars

1405

Comparison of precast and cast-in-place concrete pavements responses under heavy vehicle simulator loads E. Kohler, J. Harvey, L. Du Plessis & L. Motumah

1415

Field testing of concrete pavements at Chicago O’Hare International Airport Y.-S. Liu & D. Lange

1425

Unbonded concrete overlay movements in response to gear loads D.A. Morian, S. Sadasivam, J. Reiter, S.M. Stoffels, L. Yeh & A. Ioannides

1433

Case histories Idaho Airport saves time and money with full-depth reclamation G.E. Halsted

1445

Mitigating unbound roadway rutting caused by groundwater movement V. Diyaljee

1455

Use of bitumen emulsion in urban paving C.R. de Carvalho Filho, F.P. Cavalcante, C. de Medeiros Brito Cavalcante, J.A. Gonçalves de Macêdo & I.D. da Silva Pontes Filho

1465

A case study: Quantification and modeling of asphalt overlay delamination on an airport pavement E. Horak, J.W. Maina & S.E. Emery

1475

Taxiway embankment over soft ground using staged construction R. Wells, X. Barrett & T. Wells

1485

Evaluation of runway bearing capacity: In-situ measurements and laboratory tests A. Graziani, F. Cardone, E. Santagata & S. Barbati

1493

Lessons learned during regular monitoring of in situ pavement bearing capacity conditions P. Paige-Green

1505

Author index

1517

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Preface

This conference is the eighth conference in the series started in Trondheim, Norway in 1982 and arranged at four-year intervals under the title “Bearing Capacity of Roads and Airfields—BCRA.” In the sixth BCRA Conference in Lisbon, Portugal, a third component on railway track was added in the scope as a vital element of transportation infrastructure worldwide. However, since then the acronym BCRA remained the same. For the first time, this eighth conference uses the acronym BCR2A to emphasize the infrastructure problems that all three transportation modes have in dealing with the bearing capacity challenges of highway and airfield pavements and railroad track structures. The 8th International BCR2A’09 Conference focuses on issues pertaining to the bearing capacity of highway and airfield pavements and railroad track structures and aims to promote efficient design, construction and maintenance of the transportation infrastructure. Bearing capacity issues are steadily changing because of the ever-increasing traffic volumes and weights, which require stronger and more durable pavements, railroad track structures and superstructures. New materials and methods are being developed and new aspects of design and material utilization are brought into focus, which demand a better transition into implementing mechanistic concepts in designing pavements and railroad track structures. The BCR2A’09 conference will provide such a forum for new concepts and innovative solutions. This proceedings book includes submissions to the conference in the areas of subgrade soils, granular materials, asphalt mixtures, in-situ measurement techniques and developments, modeling and methods of functional testing, backcalculation analyses of deflection measurements, new and/or innovative techniques in compaction and construction, structural evaluation and performance prediction, structural design systems for new construction and rehabilitation, bearing capacity designs for challenging conditions and load effects, bearing capacity designs for climatic conditions, reinforcement of structural layers, utilization of recycled materials, railroad track structures, full-scale testing, and case histories of roads, railways, and airfields. At least two, but often three reviewers, including members of the Scientific Committee, subjected all submitted contributions to an exhaustive refereed peer review procedure. Based on the reviewers’ recommendations, those contributions which best suited the conference goals and objectives were chosen for inclusion in the proceedings. This international conference is coming to the United States for the second time; the first being the successful 1994 conference held in Minnesota. Taking this into consideration, the University of Illinois at Urbana-Champaign (UIUC) was in a unique position to host this conference. Illinois is at the crossroads of the U.S. transportation network and the highly ranked Civil and Environmental Engineering Department at UIUC along with its prominent transportation centers and programs have a long-standing reputation of cutting edge research on transportation infrastructure. The UIUC Newmark Civil Engineering Laboratory houses the Center of Excellence for Airport Pavement Technology (CEAT) and the Association of American Railroads’ Affiliated Research Laboratory. The Advanced Transportation Research and Engineering Laboratory (ATREL), in Rantoul, Illinois, houses the Illinois Center for Transportation (ICT), one of the largest centers in the UIUC College of Engineering. These centers and laboratories are the highlighted sites for technical tours during the BCR2A’09 Conference with a post conference visit to the Chicago O’Hare International Airport. During the BCR2A’09 event, four half-day pre-conference workshops have also been organized on climatic effects on

XV

pavement infrastructure, pavement interlayer systems, railroad track design including asphalt trackbeds, and designs for new and rehabilitated airport pavements. The Editors would like to thank the Scientific Committee members and individual reviewers for their dedication and contributions of their time and efforts to ensure the high technical quality of the accepted papers. In addition, sincere thanks are extended to Ms. Elaine Wolf for collecting abstracts and Ms. Sinem Ertunga Tutumluer for ensuring that final manuscripts were in accordance with the publication format requirements. The guidance and continuing input from the International Advisory Committee members were essential in planning of this conference, and highly appreciated. Finally, we would like to gratefully acknowledge the Organizing Committee members for their help, suggestions and contributions to the management of the Conference affairs; especially Chris Barkan, Bill Buttlar, Riley Edwards, Dave Lange, Dave Lippert, and Jeff Roesler. Erol Tutumluer Imad L. Al-Qadi Urbana, Illinois, June 2009

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Organization

Chairmen Erol Tutumluer, Chairman Imad L. Al-Qadi, Co-chairman International Advisory Committee Leif Bakløkk, Chairman Norwegian Public Roads Administration, Norway Erol Tutumluer, Co-chairman University of Illinois at Urbana-Champaign, USA David R. Brill, Federal Aviation Administration, USA David D. Davis, Association of American Railroads, USA Guy Doré, Laval University, Canada Magdy El-Sibaie, Federal Railroad Administration, USA Brian Ferne, Transport Research Laboratory (TRL), United Kingdom Ralph Fischer, Deutsche Bahn AG—DB Systemtechnik, Germany Mahmoud H. Fraha, Canadian Civil Aviation, Transport Canada, Canada Rita Moura Fortes, Mackenzie Presbyterian University, Brazil Antonio Gomes Correia, University of Minho/DEC, Portugal Øyvind Hallquist, Avinor A/S, Norway Ivar Horvli, ViaNova, Norway Takemi Inoue, Research Institute, NIPPON HODO, Japan Geoff Jameson, ARRB Transport Research Ltd., Australia Hans Jørgen Ertmann Larsen, Danish Road Directorate, Denmark Andreas Loizos, National Technical University of Athens, Greece Rafael Alvarez Loranca, Jefe de Area de Gestion de Infraestructuras Geocisa, Spain Jens Melsom, Norwegian National Rail Administration, Norway Helge Mork, Norwegian University of Science and Technology, Norway Jean Michel Piau, Laboratorie Central des Ponts et Chaussées, France Cheryl A. Richter, Federal Highway Administration, USA Tom Scarpas, Delft University of Technology, The Netherlands Ramesh Sinhal, Highways Agency, United Kingdom Dariusz Sybilski, Road and Bridge Research Institute, Poland Xinglong Wang, Heilongjiang Institute of Highway and Transport Research, P.R. China Scientific Committee Erol Tutumluer, Chairman Imad Al-Qadi, Co-chairman Leif Bakløkk, Norwegian Public Roads Administration, Norway David Brill, Federal Aviation Administration, USA Neeraj Buch, Michigan State University, USA William G. Buttlar, University of Illinois, USA Samuel H. Carpenter, University of Illinois, USA Halil Ceylan, Iowa State University, USA XVII

Ghassan Chehab, Penn State University, USA David Davis, Association of American Railroads, USA Andrew Dawson, University of Nottingham, UK Herve Di Benedetto, ENTPE, France Tuncer Edil, University of Wisconsin—Madison, USA Hans Jørgen Ertmann Larsen, Danish Road Directorate, Denmark Paul Fleming, University of Loughborough, UK Antonio Gomes Correia, University of Minho, Portugal Edward Guo, SRA International, Inc., USA Øyvind Hallquist, Avinor, Norway Ivar Horvli, ViaNova, Norway James Hyslip, Hyground Engineering, USA Buddhima Indraratna, University of Wollongong, Australia Tatsuya Ishikawa, Hokkaido University, Japan Geoff Jameson, Australian Road Research Board, Australia David A. Lange, University of Illinois, USA Dingqing Li, Association of American Railroads, USA David L. Lippert, Illinois Department of Transportation, USA Andreas Loizos, National Technical University of Athens, Greece Byron Lord, Federal Highway Administration, USA Robert Lytton, Texas A&M University, USA Eyad Masad, Texas A&M University, USA Jens Melsom, Norwegian National Rail Administration, Norway Andre Molenaar, Delft University of Technology, The Netherlands Helge Mork, Norwegian University of Science and Technology, Norway Soheil Nazarian, University of Texas at El Paso, USA Anand Puppala, University of Texas at Arlington, USA Jeffery R. Roesler, University of Illinois, USA Jerry Rose, University of Kentucky, USA Charles Schwartz, University of Maryland, USA Mark B. Snyder, Mark B. Snyder Engineering, USA Shiraz Tayabji, Fugro Consultants, Inc., USA Marshall Thompson, University of Illinois, USA Richard Thuma, Crawford, Murphy & Tilly, Inc., USA Per Ullidtz, Dynatest, Denmark David White, Iowa State University, USA Organizing Committee Erol Tutumluer, Chairman University of Illinois at Urbana-Champaign Imad L. Al-Qadi, Co-chairman and Highway Area Coordinator Director of Illinois Center for Transportation (ICT), University of Illinois at Urbana-Champaign Christopher P.L. Barkan, Railroad Area Coordinator Director of Association of American Railroads (AAR) Affiliated Research Laboratory, University of Illinois at Urbana-Champaign David A. Lange, Airfield Area Coordinator Director of Center of Excellence for Airport Technology (CEAT), University of Illinois at Urbana-Champaign

XVIII

William G. Buttlar University of Illinois at Urbana-Champaign Riley Edwards University of Illinois at Urbana-Champaign David L. Lippert Illinois Department of Transportation Jeffery R. Roesler University of Illinois at Urbana-Champaign Marshall R. Thompson University of Illinois at Urbana-Champaign Richard Thuma Crawford, Murphy & Tilly, Inc. Elaine E. Wolff University of Illinois at Urbana-Champaign

XIX

Keynote presentations

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Recent and landmark improvements in performance characterization of unbound aggregate bases and subbases and sublayers comprised of Chemically Stabilized Materials (CSMs) Dallas N. Little Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA

ABSTRACT: The importance of aggregate and soil layers within the pavement structure has been appreciated from the time that the California Department of Transportation initiated the use of the California Bearing Ratio in the 1920s. In the late 1950s, the American Association of Highway and Transportation Officials (AASHTO) Road Test assigned structural layer coefficients to all pavement layers including the unbound aggregates base and subbase. Subsequent satellite studies to the AASHTO Road Test assigned structural layer coefficients to chemically stabilized materials (CSMs) used as pavement layers. This lecture discusses significant advancements made within approximately the last 15 years in modeling the performance of unbound aggregates base and subbase layers and CSM layers. The importance of correctly considering not only the hardening and softening effects of stress state on unbound layers but also cross anisotropy are discussed. The new AASHTO mechanistic-empirical pavement design guide (MEPDG) accounts for stress state but not for anisotropy. Prior to development of the MEPDG, the AASHTO structural layer coefficients of CSMs were linked to resilient modulus values of the respective CSM; however, a substantial disconnect exists between moduli versus layer coefficient predictions for unbound aggregate base layers and similar relationships between modulus values and layer coefficients for CSMs. This lecture describes why this disconnect exists and how this is related to a difference in the mode of damage for the respective layers. The lecture discusses the adequacy of the MEPDG approach for assessing the structural value of CSMs as well as granular layers. The lecture further compares the MEPDG-type approach to other widely used structural pavement design methods such as the Texas Flexible Pavement method and the 1998 AASHTO method.

3

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The performance of rail track incorporating the effects of ballast breakage, confining pressure and geosynthetic reinforcement B. Indraratna & S. Nimbalkar Department of Civil Engineering, University of Wollongong, NSW, Australia

D. Christie RailCorp, Sydney, Australia

ABSTRACT: Rail tracks are often placed on ballast which offers the desirable resiliency to cyclic loads. However ballasted beds need periodic maintenance due to deformation and degradation associated with breakage and fouling. A proper understanding of load transfer mechanisms and their effect on ballast breakage are prerequisites for minimizing maintenance costs. Recycled ballast is a cheaper and environmentally viable option but its strength characteristics need to be investigated beforehand. This paper demonstrates the analytical, numerical and laboratory investigations carried out to investigate the geotechnical behavior of ballast, including shear strength, ballast breakage, and confining pressure. The potential use of geosynthetics for improving the stability and drainage of railway tracks under high monotonic and cyclic loading is also studied. Field tests were carried out to measure the in-situ stresses of ballast on a section of instrumented track funded and built by RailCorp, Australia. 1

INTRODUCTION

Rail roads form the largest worldwide network catering for quick and safe, public and freight transportation. In order to compete with the other modes of transportation and meet the ever growing demand of public and freight transport, railway industries face challenges to improve their efficiency and decrease maintenance and infrastructure costs. In spite of recent advances in rail geotechnics, the correct choice of ballast for rail track foundation is still considered critical because aggregates progressively deteriorate and break down under heavy cyclic loading. The degradation of ballast is influenced by factors including the amplitude and number of load cycles, gradation of aggregates, track confining pressure, and the angularity and fracture strength of individual grains. The cost of track maintenance can be significantly reduced if the geotechnical behaviour of rail substructure, in particular the ballast layer, is better understood. The use of geosynthetics beneath the layer of ballast as drainage, confinement and to separate it from subballast, is highly desirable. The potential use of recycled ballast in the rail track reinforced with geosynthetics is also an economically feasible option. 2

GEOTECHNICAL BEHAVIOR OF BALLAST

Ballast forms the largest component of a rail track by weight and volume. Ballast materials usually include dolomite, rheolite, gneiss, basalt, granite and quartzite (Raymond, 1979). It is composed of medium to coarse gravel sized aggregates (10–60 mm) with a smaller percentage of cobble-sized particles. Good quality ballast should possess angular particles, have a high specific gravity, a high shear strength, a high toughness and hardness, a high resistance to weathering, a rough surface, and a minimum of hairline cracks (Indraratna et al. 1998). The main functions of ballast are (Selig & Waters, 1994): distributing and damping the loads received from sleepers, producing lateral resistance, and providing rapid drainage. It could be argued that for high load bearing characteristics and maximum track stability, ballast needs 5

to be angular, well graded, and compact, which in turn reduces drainage. Therefore the use of geosynthetics as a suitable alternative for drainage and separation of ballast and subballast needs to be investigated. In this paper the geotechnical properties of ballast are discussed. The effect of geosynthetics on rail track performance for both fresh and recycled ballast is discussed. It is shown that using geosynthetics with special characteristics in the track bed improves its performance significantly. 2.1 Shear strength The shear strength of granular materials is generally assumed to vary linearly with the applied stress and the Mohr-Coulomb theory is usually used to describe conventional shear behavior. Indraratna et al. (1997) have shown that the shear strength is a function of confining pressure, and is highly non-linear at high stresses. Indraratna et al. (1993) proposed a non-linear strength envelope obtained during the testing of granular media at low normal stresses. This non-linear shear stress envelope is represented by the following equation: τf / σc = m(σn′ / σc)n

(1)

where τf is the shear stress at failure, σc is the uniaxial compressive stress of the parent rock determined from the point load test, m and n are dimensionless constants, and σ'n is the effective normal stress. The non-linearity of the stress envelope is governed by the coefficient n. For the usual range of confining pressures (below 200 kPa) for rail tracks, n takes values in the order of 0.65–0.75. A large-scale cylindrical triaxial apparatus, which could accommodate specimens of 300 mm diameter and 600 mm high (see Figure 1), was used by Indraratna et al. (1998) to verify the non-linearity of shear stress. The results of his study associated with latite basalt in a normalized form are plotted in Figure 2, with results obtained from other researchers (Marsal, 1973; Marachi et al. 1972; Charles & Watts, 1980).

Figure 1.

Cylindrical triaxial apparatus with dynamic actuator design at UoW.

6

0.1

Normalised shear stress, τf/σc

Latite basalt (Indraratna et al., 1998) [1] Basalt (Charles & Watts, 1980) [10] San Francisco basalt (Marsal, 1973) [11] 0.01

Crushed basalt (Marachi et al., 1972) [12] m=0.33 n=0.73

m=0.18 n=0.73

0.001

τf / σc = m (σ 'n / σc)n

0.0001 0.00001

0.0001

0.001

0.01

0.1

Normalised normal stress, σ'n/σc

Figure 2.

Normalized shear strength for latite basalt aggregates (Indraratna et al. 1998).

2.2 Ballast breakage Railway tracks are deformed by the degradation of ballast particles (Selig & Waters, 1994; Indraratna et al. 1998, 2001). Their breakage under load is a complex mechanism that usually starts at the inter-particle contacts (i.e. breakage of asperities), followed by a complete crushing of weaker particles under further loading. A rapid fragmentation of particles and subsequent clogging of voids with fines is commonly observed in overstressed railway foundations. Chrismer & Read (1994) concluded that the degradation of aggregate is the primary cause of contamination, and accounts for up to 40% of the fouled material. Generally, the main factors that affect breakage can be divided into three categories: (a) properties related to the characteristics of the parent rock (e.g. hardness, specific gravity, toughness, weathering, mineralogical composition, internal bonding and grain texture); (b) physical properties associated with individual particles (e.g. soundness, durability, particle shape, size, angularity and surface smoothness); and (c) factors related to the assembly of particles and loading conditions (e.g. confining pressure, initial density or porosity, thickness of ballast layer, ballast gradation, presence of water or ballast moisture content, cyclic loading pattern including load amplitude and frequency). The effects of some of these factors are demonstrated in this paper. In order to quantify ballast breakage in the current study, Marsal’s (1967) method was used in which the volume of particle breakage while loading a specimen of ballast is defined by the changes in particle size distribution curves measured before and after loading. Marsal introduced a breakage index Bg, which is the sum of the difference in percentage retained on sieves, having the same sign. Indraratna et al. (2005) introduced an alternative ballast breakage index (BBI) based on particle size distribution (PSD) curves. The ballast breakage index (BBI) is calculated on the basis of change in the fraction passing a range of sieves, as shown in Figure 3. The increase in degree of breakage causes the PSD curve to shift further towards the smaller particles size region on a conventional PSD plot. The area A between the initial and final PSD increases results in a greater BBI value. BBI has a lower limit of 0 (no breakage) and an upper limit of 1. By referring to the linear particle size axis, BBI can be calculated by using following equation. BBI =

A+B A

(2)

where A is the area as defined previously, and B is the potential breakage or area between the arbitrary boundary of maximum breakage and the final particle size distribution. 2.3 Constitutive modelling of ballast Salim & Indraratna (2004) developed an elasto-plastic stress-strain constitutive model incorporating dilatancy, breakage and the plastic flow rule to predict ballast deformation and 7

Figure 3.

Ballast breakage index (BBI) calculation method (Indraratna et al. 2005).

degradation. The model uses a generalized 3D system to define the contact forces, stresses and strains in granular media, including the plastic potential, the hardening function, and particle breakage. This model is based on the critical state concept and theory of plasticity with a kinematic-type yield locus (constant stress ratio). The increments of plastic distortional strain dε ps, and volumetric strain dε pv , were given by Salim & Indraratna (2004), as follows: d ε sp

( )(1 − )(9 + 3M − 2η * M )(η − η )dη = (M − η ) (1 + e ) ( − 1) ⎡9(M − η *) + {χ + μ (M − η *)}⎤ ⎣ ⎦ 2ακ 2

i

d ε vp =

po ( i ) pcs ( i )

p pcs

i

i

2 po p

(3)

B p

⎛ B ⎞ ⎡ χ + μ (M − η *) ⎤ p 9(M − η ) d ε sp + ⎜ ⎟ ⎢ ⎥ dε s 9 + 3M − 2η * M ⎝ p ⎠ ⎣ 9 + 3M − 2η * M ⎦

(4)

The parameter p is the effective mean stress and pcs is the value of p on the critical state line at the current void ratio. po is the value of p at the intersection of the undrained stress path and the initial stress ratio line. The sub-script i indicates the initial value at the start of shearing. The parameter η is the stress ratio (η = q/p), q is the deviator stress, η* = η (p/pcs), M is the critical state stress ratio, ei is the initial void ratio, κ is the negative slope of compression curve (e-lnp) and α, B, χ and μ are dimensionless constants. The evolutionary techniques of these constants are given in Salim & Indraratna (2002). This model was verified using large-scale triaxial tests (see Figure 4). The above constitutive model contains 11 parameters for monotonic loading and additional 4 parameters for cyclic loading. These parameters can be evaluated using the results of the drained triaxial test and the measurements of particle breakage. 2.4 Effect of confining pressure Although the effect confining pressure on various geotechnical structures is significant and is considered to be key criteria in the design of these structures, it is usually neglected in conventional rail track design. Track substructure is essentially self-supporting with minimal lateral constraints. During a train passage, ballast and capping (subballast) materials are free to spread laterally, which increases track settlement and decreases its shear strength. At the University of Wollongong, cyclic triaxial tests have been conducted on samples of ballast to investigate the effect of confining pressure. Track confinement can be increased by reducing the spacing of sleepers, increasing the height of shoulder ballast, including a geosynthetic layer at the ballast-subballast interface, widening the sleepers at both ends (see Figure 5), and 8

8.0

Test data for crushed basalt (Indraratna and Salim 2001)

εv (%)

Model prediction

1600

σ3 = 300 kPa

1200

Test data for crushed basalt (Indraratna and Salim 2001)

-6.0

Volumetric strain,

Distortional stress, q(kPa)

2000

200 kPa

800

100 kPa 50 kPa

400

Model prediction

-4.0

Dilation

-2.0

100 kPa

0.0 2.0

200 kPa 4.0

300 kPa

Contraction

6.0

0

σ3 = 50 kPa

8.0

0.0

5.0

10.0

15.0

Distrortional strain,

20.0

25.0

0.0

εs(%)

5.0

10.0

15.0

20.0

25.0

Distrortional strain, εs(%)

Figure 4. Model prediction compared with experimental data for drained triaxial shearing (Salim & Indraratna, 2004).

Rails

Winged concrete sleepers

Figure 5.

Sleepers with enlarged ends to increase the confining pressure (Indraratna et al. 2004).

using intermittent lateral restraints at various parts of the track (see Figure 6). The effect of confining pressure on ballast under cyclic loading to reduce the volume of breakage has been studied by Indraratna et al. (2005) and Lackenby et al. (2007) to find out the optimum confining pressure based on loading and track conditions. Specimens were prepared to the recommended gradation and initial porosity (i.e. d50 = 38.5 mm, Cu = 1.54. eo = 0.76 where d50 is the ballast diameter corresponding to 50% finer in the particle size distribution curve and Cu is the coefficient of uniformity). Effective confining pressures (σ 3′) ranging from 1 to 240 kPa with qmax = 500 kPa were applied. Figure 7 shows the results of confining pressure (σ 3′) on the axial and volumetric strains of ballast achieved at the end of 500,000 cycles. As expected, the axial strains decreased with an increasing confining pressure and the specimens dilated at a low confining pressure (σ 3′ < 30), but became progressively more compressive as the confining pressure increased from 30 to 240 kPa. The effect of confining pressure (σ 3′) on particle degradation is shown in Figure 8, where breakage was divided into three regions: (I) a dilatant unstable degradation zone (DUDZ); (II) an optimum degradation zone (ODZ); and (III) a compressive stable degradation zone (CSDZ). Lackenby et al. (2007) has shown that the specimens are subjected to rapid and considerable axial and expansive radial strains that result in an overall volumetric increase or dilation at low confining pressure of DUDZ region (σ 3′ < 30 kPa). Particles in this region are given insufficient time to rearrange and due to the excessive axial and radial strains, a considerable degradation occurs as a result of shearing and attrition of angular projections. Due to the low confining pressures applied in this region, specimens in this degradation zone are characterized by limited particle-to-particle areas of contact. As the confining pressure is increased to the ODZ region (σ 3′ = 30 – 75 kPa), the rate of axial strain is greatly reduced due to an apparent increase in stiffness, and the overall 9

Intermittent lateral restraints

Lateral restraints

or

Rail

Figure 6.

Sleepers

Increasing confining pressure using intermittent lateral restraints (Indraratna et al. 2004). 25

Axial Strain (%)

εa (+) 20

εa εr (+)

15

εr (+) 10 5

Volumetric Strain (%)

0 4

qmax = 500 kPa

2

Compression (+) Dilation (-)

0

-2

0

50

100

150

200

250

Effective Confining Pressure (kPa)

Figure 7.

Variation of axial and volumetric strains with confining pressure (Lackenby et al. 2007).

Ballast Breakage Index, BBI

0.06

qmax = 500 kPa qmax = 230 kPa

0.04

0.02

(I)

(II)

(III)

0 0

50

100

150

200

250

Effective Confining Pressure (kPa) Figure 8.

Effect of confining pressure on particle degradation (Lackenby et al. 2007).

10

volumetric behaviour is slightly compressive. Particles in this region are held together in an optimum array with sufficient lateral confinement so as to provide an optimum distribution of contact stress and increased areas of inter-particle contact which reduces the risk of breakage associated with concentrations of stress. As σ 3′ is increased further in the CSDZ region (σ 3′ > 75 kPa), the particles are forced against each other which limits sliding and rolling but increases their breakage considerably. Particles in this region fail not only at the beginning of loading when axial strain rates are greatest, but also by fatigue as the number of cycles increase. Due to the large lateral forces being applied to the samples in this region, volumetric compression is enhanced, which is partly due to an increase in particle breakage. 3

RESILIENT MODULUS OF BALLAST

The cyclic response of ballast is usually characterised by the resilient modulus. For repeated loads in triaxial testing with constant confining stress, the resilient modulus (MR) is defined as the ratio of the applied cyclic deviator stress to the recoverable (resilient) axial strain during unloading as illustrated in Figure 9 (a) and (b). Resilient modulus is defined as MR =

Δq εr

(5)

where Δq is the difference between qmax and qmin and εr is the recoverable (resilient) axial strain during triaxial unloading. Indraratna et al. (2008) highlighted the influence of particle breakage on the resilient modulus which is summarised below. 3.1 Resilient modulus and bulk stress The resilient modulus of granular materials can be expressed by a simple hyperbolic model popularly known as K-ϕ model (Hicks, 1970). This model expresses MR as a function of the sum of principal stresses ( s1′ + s2′ + s3′ ) also known as the bulk stress (Σψμβο) M R = k1ϕ k 2

(6)

where k1 and k2 are empirical coefficients. For triaxial tests, due to symmetry in directions (2) and (3), (σ 2′ = σ 3′ ), the sum of the principal stress simplifies to (σ 2′ + 2 σ 3′ ). Figure 10 presents the variation of MR with ϕ for different values of σ 3′ and qmax. It is shown that all values of MR irrespective of σ 3′ and qmax fall within a narrow band. Thus a

Figure 9. (a) cyclic loading curve, showing the maximum and minimum deviator stress, (b) representation of strains during one cycle of load application (Indraratna et al. 2008).

11

Figure 10.

Relationship between resilient modulus and bulk stress (Indraratna et al. 2008).

Figure 11. Variation of BBI and MR with σ3' for cyclic deviator stress of 500 kPa (Indraratna et al. 2008).

Figure 12. (a) Effect of confining pressure and the number of cycles on MR, (b) effect of qmax, cyc on MR (Lackenby et al. 2007).

12

unique relationship between the resilient modulus and bulk stress, given by MR = 40ϕ0.34 (R2 > 0.95) predicts well the resilient action of ballast. 3.2 Resilient modulus and ballast breakage Figure 11 presents the variation of BBI and MR with σ 3′ for a constant maximum deviator stress (qmax) 500 kPa. Also the boundaries of the ballast degradation zones are shown. Here MR increases gradually with σ 3′ in both the DUDZ and ODZ zones. However, there is a marked increase in MR in the compressive (CSDZ) region as σ 3′ exceeds 65 kPa. The percentage increase of MR in this zone was found to be 16% for qmax of 500 kPa. An increased σ 3′ in the CSDZ will increase the stress level where the particles touch whilst restricting internal sliding and rolling (Lackenby et al. 2007; Indraratna et al. 2008), and contribute towards an increase in the resilient modulus. Lackenby et al, 2007 has shown that the resilient modulus (MR) increases with an increasing number of cycles, and a maximum deviator stress magnitude (qmax,cyc) and confining pressure, as shown in Figure 12. 4 USE OF GEOSYNTHETICS FOR STABILIZING A RECYCLED BALLASTED TRACK Geo-synthetics have been widely and successfully used in new rail tracks and track rehabilitation for almost three decades. When appropriately designed and installed, geosynthetics are a cost effective alternative to more traditional techniques. Railway tracks still have several problem areas with ballast; an increase in the bearing capacity of subgrade soil, contamination with subgrade fines, and dissipation of high pore water pressure built up by cyclic train loading. As with other geotechnical engineering projects, the application of geosynthetics within railway construction can be subdivided into (1) separation, (2) reinforcement, (3) filtration, (4) drainage, (5) moisture barrier/waterproofing and (6) protection. In order to reduce the accumulation of discarded ballast, minimise the cost of track maintenance and reduce the environmental degradation caused by quarrying more fresh ballast, selected waste ballast may be cleaned, sieved, and reused. However, because the angularity of recycled ballast was diminished by the degradation of sharp corners in previous loading cycles, recycled ballast will deform laterally and settle faster than fresh ballast. Therefore its behavior and performance must be investigated to ensure that it complies with the required stability and safety criteria stipulated by various rail authorities before being re-used. An extensive laboratory experimental program using a large-scale prismoidal triaxial rig was carried out at the University of Wollongong to investigate how different types of geosynthetics enhanced the mechanical properties of fresh and recycled ballast. A plane strain finite element analysis (PLAXIS) was also used to simulate the behavior of ballast in a prismoidal tri-axial rig, with and without geosynthetics. This finite element model was then used to obtain the optimum location for geosynthetics in track substructure. The laboratory experiments and finite element analysis, including their findings, are described and explained below. 4.1 Laboratory model experiments A large-scale prismoidal triaxial rig, 800 mm long × 600 mm wide × 600 mm high was built at the University of Wollongong to model the response of ballasted tracks to cyclic loading. Figure 13 shows the rig and Figure 14 shows a schematic view. Further details of this apparatus can be found in Indraratna et al. (2003). Fresh ballast that consisted of sharp angular aggregates of crushed volcanic ballast (latite) was collected from Bombo quarry, situated near the city of Wollongong. Recycled ballast that consisted of semi-angular crushed rock fragments was collected from an existing stockpile at Chullora, in Sydney. The capping layer was a compacted mixture of fine gravel and sand (d50 = 0.26 mm, Cu = 5). All the fresh and recycled specimens of ballast were prepared following a single gradation curve (d50 = 35 mm, Cu = 1.6). A geosynthetic reinforcement layer was placed at the ballast-capping interface. 13

Figure 13.

Large-scale prismoidal triaxial equipment designed at the UoW.

Dynamic actuator Rail segment Timber sleeper

Movable walls

Ballast

50

Capping

Subgrade

150

300

150

Settlement plates

Pressure cells Rubber mat

Figure 14.

Linear bearings

600

Geosynthetics

Schematic view of the large-scale prismoidal triaxial apparatus (Indraratna et al. 2003).

Three types of geosynthetics (i.e. geogrid, woven-geotextile and geocomposite) were used to stabilise both the fresh and recycled ballast. The geosynthetics were all made from polypropylene. The geogrid was bi-oriented with 27 mm × 40 mm rectangular apertures and 420 g/m2 unit mass. Its peak tensile strength was 30 kN/m. The geotextile was a high strength woven polymer with 0.25 mm pores, 450 g/m2 unit mass, and 80 kN/m tensile strength. The geocomposite had a unit mass of 560 g/m2 and was composed of the same geogrid bonded to a non-woven polypropylene geotextile. The purpose of adding the non-woven geotextile to the geogrid was to provide filtration and separation functions that are absent in the geogrid due to its large apertures. In order to simulate real track conditions, the prismoidal triaxial chamber was filled with several layers of ballast and other material; a 50 mm layer of compacted clay on the bottom, a 100 mm capping layer, then a 300 mm layer of load bearing ballast, and 150 mm layer of crib ballast on top. Finally, a 650 mm long × 220 mm wide timber sleeper and a segment of rail were placed above this compacted ballast. The space between the sleeper and the walls was filled with crib ballast. After preparing the specimen, small lateral stresses (σ 2′ = 10 kPa and σ 3′ = 7 kPa) were applied to the walls of the triaxial chamber by hydraulic jacks to simulate shoulder ballast and field confining stresses. A cyclic load was applied with a maximum load intensity of 73 kN to produce the same average contact stress at the sleeper-ballast interface for a typical 25 tonne/axle traffic load. The tests were conducted at a frequency of 15 Hz to simulate a speed of 80 km/h. The total number of load cycles applied in each test was 500,000. More detailed procedures, together with the complete findings and discussions of the tests were reported by Indraratna et al. (2004). Only some of the test results are summarised below. 14

Number of load cycles, N

Number of load cycles, N 0

100000

200000

300000

400000

500000

0

600000

100000

200000

Recycled ballast (dry)

Settlement, S (mm)

Settlement, S (mm)

500000

600000

Recycled ballast (wet)

5

Recycled ballast with geotextile (dry)

Rapid increase in settlement

400000

Fresh ballast (wet)

Fresh ballast (dry)

5

300000

0

0

Recycled ballast with geogrid (dry) Recycled ballast with geocomposite (dry)

10

Recycled ballast with geotextile (wet)

Rapid increase in settlement

Recycled ballast with geogrid (wet)

10

Recycled ballast with geocomposite (wet)

15

20

15 Stabilisation

Stabilisation

25

20

(a) dry samples

(b) wet samples

Number of load cycles, N 0

100000

200000

300000

400000

Number of load cycles, N 500000

600000

0

0

100000

200000

300000

400000

500000

600000

500000

600000

0

Vertical strain, ε1 (%)

Vertical strain, ε1 (%)

2 2

4 Fresh ballast (dry) Recycled ballast (dry) 6

4

6

Fresh ballast (wet) Recycled ballast (wet)

Recycled ballast with geotextile (dry)

Recycled ballast with geotextile (wet)

8

Recycled ballast with geogrid (dry)

Recycled ballast with geogrid (wet)

Recycled ballast with geocomposite (dry)

Recycled ballast with geocomposite (wet)

8

10

(a) dry samples

(b) wet samples

Number of load cycles, N 0

100000

200000

300000

400000

Number of load cycles, N 500000

0

600000

100000

200000

300000

400000

0.0

0.0 (εL is parallel to the sleeper)

(εL is parallel to the sleeper) -0.5

Lateral strain, εL (%)

Lateral strain, εL (%)

-0.5

-1.0

-1.5

Fresh ballast (dry) Recycled ballast (dry)

-1.0

-1.5 Fresh ballast (wet) -2.0

Recycled ballast with geotextile (dry)

Recycled ballast (wet) Recycled ballast with geotextile (wet)

-2.5

Recycled ballast with geogrid (dry) Recycled ballast with geocomposite (dry)

Recycled ballast with geogrid (wet) Recycled ballast with geocomposite (wet)

-3.0

-2.0

(a) dry samples

(b) wet samples

Figure 15. Effect of geosynthetics on the settlement, vertical strain and lateral strain of ballast (Indraratna & Salim 2005; Salim 2004).

Figure 15 shows the effect of geosynthetics on the settlement, vertical strain and lateral strain of ballast under wet and dry conditions. As expected there was less deformation (i.e. settlement, vertical strain and lateral strain) with fresh ballast than with recycled ballast. It is believed that the higher angularity of fresh ballast enables the particles to interlock better and cause less deformation. The test results revealed that wet recycled ballast (without any geosynthetic inclusion) was quite deformed, probably because water acts as a lubricant, reducing frictional resistance and promoting particle slippage. Although geogrids and woven geotextiles decrease the deformation of recycled ballast considerably, the geocomposite (geogrid bonded with non-woven geotextile) stabilise recycled ballast remarkably well. As described by Rowe & Jones (2000), geocomposites can provide reinforcement to the ballast layer and simultaneous filtration and separation functions. This combination of geogrid reinforcement, filtration, and separation by the bonded non-woven geotextile reduces lateral spreading, fouling, and degradation, especially in wet conditions. The geotextile also prevents fines moving up from the capping and subgrade layers (subgrade pumping) to keep the recycled ballast relatively clean. To study ballast breakage in terms of the breakage index Bg as proposed by Marsal (1967), each specimen of ballast was sieved before and after testing, and the changes in percentage retained on each size sieve were recorded. The breakage index values of recycled ballast 15

stabilised with geocomposites in dry and wet conditions were almost the same as fresh ballast (without geocomposites), and approximately 50% lower than recycled ballast without geosynthetics. This clearly indicates the benefits of using geosynthetics to reduce breakage of ballast under both dry and saturated conditions. It is evident from Table 1 that recycled ballast stabilised with geocomposites (Bg = 1.60) is as good as fresh ballast (Bg = 1.63) in terms of breakage assessment. 4.2 Numerical modelling using PLAXIS A layer of geosynthetics could be placed anywhere beneath a sleeper and within the ballast layer to improve its deformation characteristics, but the geosynthetics must be at an adequate depth below the sleeper to allow for tamping and subsequent maintenance of the track (i.e. removal of used ballast and replacing with fresh aggregates). With new tracks, geosynthetics are installed directly on the formation or subballast layer (Raymond, 2002), but with track rehabilitation they are installed on top of the old ballast which has either been trimmed or embedded in the original subgrade formation (Ashpiz et al., 2002). A finite element analysis (PLAXIS) was used to determine its optimum location. The large-scale prismoidal triaxial rig shown in Figures 13 and 14 was numerically discretized using the mesh shown in Figure 16. Due to symmetry, only half the rig was used in the numerical model. The material parameters and constitutive models used for each component of the track section are given in Table 2. Full details on constitutive models summarized in Table 2 and their parameters can be found in PLAXIS manual. A train load was simulated by applying an equivalent, uniformly distributed vertical dynamic load on the sleeper. This dynamic load has the same average contact stress at the Table 1.

Effect of geosynthetics on Marshal’s breakage index (Bg). Breakage index, Bg = ∑(ΔWK > 0)

Type of test

Sample in dry condition

Sample in wet condition

Fresh ballast Recycled ballast Recycled ballast with geogrid Recycled ballast with geotextile Recycled ballast with geocomposite

1.50 2.96 1.70 1.56 1.52

1.63 3.19 1.88 1.64 1.60

Figure 16. Finite element mesh used in PLAXIS for the prismoidal triaxial apparatus (Indraratna et al. 2005).

16

Table 2.

Parameters of the rail track materials used in the finite element analysis. Ballast

Parameter

Fresh

Recycled

Subballast

Subgrade

Timber sleeper

Steel wall

Geogrids

Model γ (kN/m3)

HS 15.3

HS 15.3

MC 21.3

Elastic 17

Elastic –

Elastic –

Elastic –

ref E50 (MPa)

150

70

–

–

–

–

–

ref Eoed ref Eur

(MPa)

(MPa) E (MPa) EA (kN/m) ν νur c (kN/m2) ϕ (degree) Ψ (degree) Pref (kN/m2) m nc

Ko

Rf

150

70

–

–

–

–

–

450 – – – 0.2 0.0 50 0 100 0.5 0.3 0.9

210 – – – 0.2 0.0 45 0 100 0.5 0.3 0.9

– 100 – 0.35 – 0.0 45 0 – – – –

– 40 – 0.4 – – – – – – – –

– 10.55 – 0.33 – – – – – – – –

– 210000 – 0.33 – – – – – – – –

– – 525 – – – – – – – – –

ref HS = Hardening-Soil model, MC = Mohr-Coulomb model, γ = unit weight, E50 = secant stiffness at ref ref 50% strength for loading conditions, Eur = triaxial unloading/reloading stiffness, Eoed = tangent stiffness for primary oedometer loading, EA = elastic normal (axial) stiffness, ν = Poisson’s ratio for loading conditions, νur = Poisson’s ratio for unloading/reloading conditions, c = effective cohesion, ϕ = effective friction angle, Ψ = dilatancy angle, Pref = reference confining pressure, m = stress dependent stiffness facnc tor, ko = coefficient of earth pressure at rest for normal consolidation, Rf = failure ratio.

sleeper-ballast interface as a typical 25 tonne/axle traffic load with a frequency of 15 Hz (speed of 80 km/h). In the finite element analysis, this load was applied over 100 cycles and then the results were compared to the experimental data with the same number of cycles. A laterally distributed static load was also applied to the movable steel wall of the prismoidal rig to simulate a field confining pressure of 10 kPa. Geosynthetics were initially placed 300 mm beneath the sleeper at the ballast capping interface, and then at decreasing intervals of 50 mm so that placement could be examined at 250, 200, 150 and 100 mm deep, respectively. Figure 17 demonstrates that there is a threshold depth (between 150 to 200 mm) below which the geosynthetics contribute no further and provide less assistance for reducing settlement. According to Figure 17, the optimum location of geosynthetics for improving the deformation characteristics of recycled ballast may be taken as 200 mm. Nevertheless, with ballast that is a conventional 300 mm thick, the optimum placement of geosynthetics at 200 mm deep may not be feasible for maintenance reasons, as mentioned earlier. In cases such as these, the layer of geosynthetics may still be conveniently located at the ballast/capping interface. 4.3 Numerical modelling using PFC2D Ballast breakage under repeated loads depends on two major factors, i.e. confining pressure and angularity of the ballast particles. Hossain et al (2007) developed a numerical model using the Discrete Element Method (DEM) to investigate the effect of breakage on the stress-strain behaviour of ballast under different confining pressures. Irregularly shaped particles of ballast were considered and their angularity was modelled by clumping upto nine circular particles together to form single particles of twelve different shapes. Figure 18 shows four different shaped particles used in the analysis. A new subroutine that defines the breakage criteria based on splitting the tensile strength of cylindrical specimens was developed and incorporated in the PFC2D analysis to study and quantify breakage in 17

20 Settlement of ballast (mm)

18 16 14 12 10 8 6 4 2 0 0

50

100 150

200 250 300 350

Placement depth of geogrids (mm) Figure 17.

Optimum location of geosynthetics by the finite elements (Indraratna et al. 2005).

Figure 18.

Particle shape and size considered in the numerical simulation (Hossain et al. 2007).

Figure 19.

Assembly deformation including breakage (Hossain et al. 2007).

relation to the particle size distribution. The particles were within the size range 19–63 mm. Low values of confining pressure were used (upto 50 kPa). The general assembly of angular particles undergoing breakage is shown in Figure 19. Figure 20 shows a comparison between the ballast breakage index (BBI) and laboratory experiments. It verifies that minimum breakage occurs at a confining pressure close to 30 kPa. At low values of σ 3′ (>30 kPa), corner breakage is pronounced due to dilation but at increasing values of 18

Figure 20. Comparison of ballast breakage index (BBI) with different confining pressure (Hossain et al. 2007).

Figure 21.

Breakage of particles at locations near the top plate (Hossain et al. 2007).

σ 3′ (>30 kPa) the granular materials are compressed. At these elevated confining pressures, the granular assembly suffers from corner breakage and splitting. Dilation occurs at low levels of σ 3′ . Nevertheless, in most instances, the breakage zones were closer to the top loading platen due to a lower coordination number between the irregular particles, as shown in Figure 21. Research is currently being carried out at the University of Wollongong to develop a numerical model that uses PFC2D and the effects of frequency (high speed trains) and anisotropy on the behaviour of ballast. 5

FIELD TESTS ON INSTRUMENTED TRACK AT BULLI

In order to validate the results of the elasto-plastic stress-strain constitutive model (Indraratna & Salim, 2002, Salim & Indraratna, 2004) and the results of laboratory experiments (Indraratna & Salim 2005; Salim 2004), field tests were carried out on a real instrumented track. The University of Wollongong provided specifications for the track while funding to build a section of highly sophisticated instrumented track was provided by RailCorp, Australia. The overall track bed thickness was kept as 450 mm including a ballast layer of 300 mm and a capping layer of 150 mm in thickness. The particle size, gradation, and other index properties of ballast used at the Bulli site were in accordance with the Technical Specification TS 3402 (RailCorp, Sydney) which represents sharp angular coarse aggregates of crushed volcanic basalt (latite). Recycled ballast was collected from a recycled plant commissioned by RailCorp at their Chullora yard near Sydney. A physical examination indicated 19

that about 90% of the recycled ballast was semi-angular crushed rock fragments, while the remaining 10% consisted of semi-rounded river gravels and other impurities (Indraratna & Salim, 2005). Most of the semi-angular particles of recycled ballast were almost the same size and shape as fresh ballast, except that these were less angular, had fewer asperities, and fouled with subgrade soils. The concrete sleepers were used. Four sections were constructed, as shown below (see Figure 22). 1. 2. 3. 4.

Fresh Ballast Fresh Ballast and a geogrid/geotextile composite at the capping ballast interface Recycled Ballast and a geogrid/geotextile composite at the capping ballast interface Recycled Ballast

Observations of vertical and lateral deformations and the distribution of cyclic stresses in the ballast layer were made. The performance of each section under the cyclic load of moving trains was observed. Vertical deformations at different sections were measured by pegs and lateral deformations were measured by transducers connected to a data logger. The settlement pegs and displacement transducers were installed beside the rail and at the end of the sleeper, as shown in Figure 23. Figure 24 shows the installation of pressure cells to record vertical and lateral maximum cyclic stresses in the track.

15 metres

15 metres

5 Recycled ballast Figure 22.

4 Recycled ballast with Geocomposite

3 Fresh ballast with Geocomposite

Displacement Transducers

Installing settlement pegs and displacement transducers.

Pressure cells

Figure 24.

2b 2a

15 metres

2 1 Fresh ballast

Layout of the test track on the down main at Bulli on the NSW South Coast.

Settlement Pegs

Figure 23.

15 metres

Installing pressure cells beneath the concrete sleeper.

20

5.1 Ballast lateral deformations Data from the displacement transducers was collected from the data logger at regular intervals. A summary of the final lateral deformations (Sh) is presented in Table 3 to compare with the performance of different sections of track under cyclic loads. It reveals reveal how geosynthetics in the ballast layer significantly affect the lateral deformations of the ballast layer. The performance of fresh and recycled ballast was compared (refer Figure 22 locations 1 and 5) and showed a 12% and 38% decrease in lateral deformation (Sh) beneath the sleepers and ballast, respectively, because recycled ballast was used. This particular recycled ballast performed very well, that is, showed less lateral deformations because it was more well-graded than the fresh ballast. If placed as a well graded mix the corners may not break so frequently because their angularity is less. The layer of geocomposite also reduced the lateral deformation of both fresh and recycled ballast significantly. 5.2 Maximum stresses in ballast Figure 25 shows the maximum stress recorded in the ballast for an 82 class locomotive moving at about 60 km/h. The maximum vertical stress under the rail was reduced by 73% and 20% at the base of the ballast layer and capping layer, respectively. Whereas the maximum vertical stress at end of sleepers showed a reduction of 64% and 45% at the base of ballast layer and capping layer, respectively. However, the horizontal stress decreased marginally with depth, as is evident from Figure 25. Figure 26 shows the maximum stress recorded in the ballast for a coal train with 100T wagons. It confirms the same trend for vertical and horizontal stress recorded under the rail and at end of the sleepers. Figure 27 shows the comparison of lateral strain (ε3) against the number of load cycles (N) plotted in a semi-logarithmic scale with results of laboratory studies reported by Indraratna & Salim (2005) using the prismoidal triaxial apparatus. The lateral strain of ballast layer (ε3) is obtained by dividing the lateral deformation (Sh) by the initial lateral dimension (considered Table 3.

Summary of the final lateral deformation of the ballast layer. Lateral deformation Sh (mm) measured underneath

Locations

Description of section

Sleepers

Ballast

1 3 4 5

Fresh ballast Fresh ballast with geocomposite Recycled ballast with geocomposite Recycled ballast

10 8.2 7.8 8.8

6.5 3.8 5.3 4

Figure 25. Maximum dynamic pressure measured (a) under the rail (b) at end of the sleepers for an 82 class locomotive.

21

Figure 26. Maximum dynamic pressure measured (a) under rail (b) at end of sleepers for 100T coal wagon. Number of load cycles, N

Lateral strain, ε3 (%)

1x103 0.0

1x104

1x105

1x106

0.4

0.8

1.2 Bulli field trial Indraratna and Salim (2005)

Fresh Ballast Recycled Ballast

1.6

Figure 27. Comparison of lateral strain (ε3) with laboratory studies reported by Indraratna & Salim (2005).

as 2.5 m) of the ballast layer. Indraratna & Salim (2005) used a slightly different track bed configuration as described earlier. They used a maximum cyclic vertical stress of 460 kPa corresponding to an axle load of 25 tons and frequency of 15 Hz (Eseveld, 2001). It is observed that the nature of variation of ε3 measured in Bulli test track is in acceptable agreement with those reported by Indraratna & Salim (2005). The well-graded recycled ballast used in the Bulli field trial showed smaller ε3 values compared to those of fresh ballast. The observations recorded in the instrumented section of track at Bulli validate the analytical, numerical, and laboratory investigations carried out at the University of Wollongong and highlight the successful inclusion of geocomposite reinforcement in the rail track structures to significantly reduce the deformation and degradation of ballast. One interesting observation was the impact of a wheel flat where the maximum pressure transmitted to the ballast reached 415 kPa on one occasion. A longer maintenance cycle is possible with the use of geosynthetics in the rail track which in turn help defray the high costs associated with maintaining ballasted tracks. A decision support system (DSS) can serve as a suitable framework to improve the effectiveness and efficiency of decision making to evolve at technically and financially feasible solutions (Lemass & Thompson, 2001). A DSS is defined as an interactive computer-based system that utilises a model to identify and draw upon relevant data in order to aid decision making. Currently, a DSS is being developed to assist industry partners with the selection of appropriate track maintenance cycles. 6

CONCLUSIONS

The performance of ballasted rail tracks with geosynthetic reinforcement has been described through laboratory, theoretical modelling, and numerical simulations. The complex deformation 22

and degradation mechanisms have been modelled by elasto-plastic constitutive relations incorporating dilatancy and particle breakage. The results highlight that particle breakage and confining pressure have a significant influence on the permanent deformation of ballast. The resilient modulus was influenced by the number of cycles, maximum deviator stress, confining pressure, and particle breakage. Ballast breakdown increases with confining pressure, a phenomenon attributed to the inability of the ballast assembly to dilate under high levels of confinement. A new ballast breakage index (BBI) was used to quantify degradation. During cyclic loading, breakage was most significant at low and high values of confining pressure, with minimal breakage at some intermediate value. The degradation of ballast may be characterised into three distinct zones, dilatant unstable degradation zone (DUDZ), optimum degradation zone (ODZ), and compressive stable degradation zone (CSDZ). An increase in confining pressure to an optimal range of 30–75 kPa causes minimum breakage, improves track performance, and reduces the need for costly maintenance. Of several measures used to increase the confining pressure, reinforcing geosynthetics is considered to be more suitable and economically viable. The performance of ballasted track was evaluated when geosynthetic reinforcement was used. This study confirms that numerous forms of geosynthetic layers improve the performance of fresh ballast while its potential use along with recycled ballast was highlighted. It was shown that recycled ballast performs satisfactorily under repeated train loads when reinforced with suitable type of geosynthetics, eg, woven-geotextiles, geogrids and geocomposites. Settlement in fresh and recycled ballast was significantly reduced when geosynthetics were inserted. A numerical model using the finite element approach (PLAXIS) was developed to determine the optimum location for a layer of geosynthetics layer in the ballast bed. It was shown that a threshold depth exists below which the layer of geosynthetics did not contribute to any further benefit and provided less assistance in reducing settlement. It was demonstrated that a layer of geosynthetics can be ideally located at the ballast/capping interface. A numerical model using the DEM approach (PFC2D) was formulated to give a graphic insight into the real behaviour of granular material under cyclic loading. The results highlight that particle breakage and confining pressure have a significant influence on the permanent deformation of ballast. The field tests carried out on the instrumented track at Bulli validated the findings of this study and also proved the benefits of using geosynthetics in rail track to minimise deformation and degradation. Use of geosynthetics in recycled ballasted track also proved to be a feasible and effective alternative. Imperfections such as wheel flat greatly increase the pressure on the ballast which causes deformation and degradation of ballast. Hence, occasional high impact loads stemming from imperfections in wheels and/or tracks are the subject of ongoing research at the University of Wollongong. Also, DSS is being developed from the measured field data to benefit Rail Industry. ACKNOWLEDGEMENTS The authors express their sincere thanks to Cooperative Research Center for Railway Engineering and Technologies (Rail–CRC), RailCorp (Sydney) and Polyfabrics (Sydney). A number of current and past doctoral students, namely, Dr. Daniela Ionescu, Dr. Joanne Lackenby, Dr. Wadud Salim, Dr. Mohamed. Shahin, Dr. Jayan Vinod, Mr Zakir Hossain and Mr. Pramod Thakur have participated to the contents of this paper; and their contributions are greatly acknowledged. REFERENCES Ashpiz, E.S., Diederich, R. and Koslowski, C. (2002). The use of spunbonded geotextile in railway track renewal on the St. Petersburg-Moscow line. In: Proceedings, 7th International Conference on Geosynthetics; 2002; Nice, France: 14–19. Charles, J.A. and Watts, K.S. (1980). The influence of confining pressure on the shear strength of compacted rockfill. Geotechnique, London, U.K., 30(4): 353–367. Chrismer, S.M. and Read, D.M. (1994). Examining ballast and subgrade conditions. Railway Track and Struct., AREA, 39–42.

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Esveld, C. (2001). Modern Railway Track, MRT-Productions, Netherlands. Hicks, R.G. (1970). Factors influencing the resilient properties of granular materials. PhD thesis, University of California. Hossain, Z., Indraratna, B., Darve, F. and Thakur, P.K. (2007). DEM analysis of angular ballast breakage under cyclic loading Geomechanics and Geoengineering: An International Journal, Vol. 2 (3): 175–181. Indraratna, B., Ionescu, D. and Christie, D. (1998). Shear behaviour of railway ballast based on large-scale triaxial tests, Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 124(5): 439–439. Indraratna, B., Ionescu, D., Christie, D. and Chowdhury, R. (1997). Compression and Degradation of Railway Ballast under One-dimensional Consolidation, Australian Geomechanics Journal, December Issue: 48–61. Indraratna, B., Khabbaz, H., Salim, W. and Christie, D. (2003). Geotechnical characteristics of railway ballast and the role of geosynthetics in minimising ballast degradation and track deformation. In: RAILTECH 2003—Railway Technology in the New Millennium; 2003; Kuala Lumpur, Malaysia: 3.1–3.22. Indraratna, B., Khabbaz, H. and Lackenby, J. (2003). Behaviour of railway ballast under dynamic loads based on large-scale triaxial testing. Proceedings of AusRAIL Plus 2003, Sydney, 8p. Indraratna, B, Khabbaz, H, Salim, W, Lackenby, J, Christie D. (2004). Ballast characteristics and the effects of geosynthetics on rail track deformation. In: International Conference on Geosynthetics and Geoenvironmental Engineering, ICGGE; 2004; Bombay, India: 3–12. Indraratna, B., Lackenby, J. and Christie, D. (2005). Effect of confining pressure on the degradation of ballast under cyclic loading. Geotechnique, 55(4): 325–328. Indraratna, B. and Salim, W. (2002). Modeling of particle breakage of coarse aggregates incorporating strength and dilatancy. Geotechnical Engineering, Proceedings of the Institution of Civil Engineers, London, 155(4): 243–252. Indraratna, B. and Salim, W. (2005). Mechanics of ballasted rail tracks—A geotechnical perspective, A. A. Balkema—Taylor and Francis, UK. Indraratna, B, Salim W, Ionescu D, Christie D. (2001). Stress-strain and degradation behaviour of railway ballast under static and dynamic loading, based on large-scale triaxial testing. In: Proceedings, 15th International Conference of Soil Mechanics and Geotechnical Engineering; 2001; Istanbul: 2093–2096. Indraratna, B., Shahin, M.A. and Salim, M.W. (2005). Use of geosynthetics for stabilizing recycled ballast in railway track substructures. North American Geosynthetics Society (NAGS)—Geosynthetics Institute (GSI) Conference, Las Vegas, Nevada. Indraratna, B., Vinod J.S. and Lackenby, J. (2008). Influence of particle breakage on resilient modulus of railway ballast, Geotechnique (in press). Indraratna, B., Wijewardena, L.S.S. and Balasubramaniam A.S. (1993). Large-scale testing of greywacke rockfill, Geotechnique, 43(1): 37–51. Lackenby, J., Indraratna, B. and McDowel, G. (2007). The Role of Confining Pressure on Cyclic Triaxial Behaviour of Ballast. Geotechnique, 57(6): 527–536. Lemass, B.P. and Thompson, P. (2001). Decision Support for the Design of Residential Building Footing Systems. In S. Islam, L. Borle & W. Keerthipala (Eds.), 2nd International Conference on Mechanics of Structures, Materials and Systems, Wollongong, Australia: 193–197. Marachi, N.D., Chan, C.K. and Seed, H.B. (1972). Evaluation of properties of rockfill materials. Journal of Soil Mech. and Found. Division. ASCE, 96(6): 95–114. Marsal, R.J. (1973). Embankment dam engineering—mechanical properties of rockfill, Wiley Publication, New York, 109–200. PLAXIS. PLAXIS 2D Version 8.2—Finite element code for soil and rock analysis. Delft, The Netherlands: A. A. Balkema Publishers, 2004. Raymond, G.P. (1979). Railroad Ballast Prescription: State-of-the-Art. Journal of the Geotechnical Engineering Division, ASCE, 105 (GT2): 305–322. Raymond, G.P. (2002). Reinforced ballast behaviour subjected to repeated load. Journal of Geotextiles and Geomembranes, 20(1): 39–61. Rowe, P.K. and Jones, CJFP (2000). Geosynthetics: innovative materials and rational design. In: Proceedings, GEOENG 2000; Melbourne, Australia: 1124–1156. Salim, W. (2004). Deformation and degradation aspects of ballast and constitutive modelling under cyclic loading. PhD thesis, School of Civil, Mining and Environmental Engineering, University of Wollongong, Wollongonog. Salim, W. and Indraratna, B. (2004). A New elasto-plastic constitutive model for granular aggregates incorporating particle breakage. Canadian Geotechnical Journal, 41(4): 657–671. Selig, E.T. and Waters, J.M., (1994). Track Geotechnology and Substructure Management. Thomas Telford, London.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Airport pavement design for the 21st century Satish K. Agrawal Federal Aviation Administration, William J. Hughes Technical Center, New Jersey, USA

ABSTRACT: In Fiscal Year 2009, we expect U.S. airports to spend several billion dollars on capital improvements, for which FAA will provide more than $2.5 billion in AIP (Airport Improvement Grant) grants. The AIP grants come with some strings: airport operators agree to meet FAA standards for design, engineering, and operations. The Office of the Associate Administrator for Airports within the FAA maintains more than 100 advisory circulars that provide standards and guidance on: airport planning and design, airport equipment and construction, airport lighting and marking, airport pavement design and construction, runway safety, airport fire and rescue, and wildlife hazard mitigation. The R&D programs conducted at the Technical Center provide necessary data for updating advisory circulars and equipment specifications. Today, I will focus my remarks on advances in airport pavement technology. Over the past 15 years, aircraft manufacturers have introduced a new generation of airplanes that are longer, wider, and taller while increasing the number of landing gears to support the extra weight. Pavement design procedures in existence before the introduction of these new aircraft were not adequate for analyzing how these aircraft would affect the design life of existing pavements. Extrapolation of existing criteria indicated that the pavements would need to be strengthened costing approximately $1.7 billion over several years. Federal Aviation Administration undertook a10-year comprehensive R&D program to resolve this dilemma. An essential element of the plan is a comprehensive test and verification program performed on real pavements subjected to full-scale loading. The FAA’s National Airport Pavement Test Facility was built. It is capable of full-scale loading up to 75,000 pounds per wheel on two landing gears with six wheels per gear. The 60-ft wide test sections provide two traffic lanes to compare the performance of 6-wheel and 4-wheel gears simultaneously. In operation since 1999, the facility is providing exciting new information in updating pavement design technologies around the world. With the addition of two more modules on each carriage, the overall capability of the test vehicle has been expanded to permit up to five dual-wheels in tandem on each carriage. This upgrade allows the facility to conduct full-scale pavement tests for current ten-wheel landing gear configurations (Antonov AN-124) and future commercial aircraft that might use either eight or ten wheel landing gear configurations. In addition, the new modules will also be capable of steering up to a maximum of five degrees from the longitudinal centerline of the wheel group. After our 10-year R&D effort, the FAA is set to debut a new software package for airport pavement thickness design. The new program is known by its acronym, FAARFIELD. A substantially rewritten Advisory Circular (AC) will make FAARFIELD the FAA’s standard thickness design procedure for both rigid and flexible pavements, including overlays, and will retire the old nomograph-based design procedures. The FAA is also providing new software products for the aviation community: COMFAA for PCN evaluation; BACKFAA for backcalculation from FWD data; ProFAA for computing pavement roughness indexes; and PAVEAIR, FAA’s forthcoming software for comprehensive airport pavement management. Development of all these products reflects the capabilities of the state-of-the-art facility that will celebrate its tenth anniversary this year.

25

Subgrade soils

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Improving subgrade strength and pavement performance by chemical treating subgrade soils N. Bandara & M.J. Grazioli Michigan Department of Transportation, Metro Region Office, Southfield, Michigan, USA

ABSTRACT: Chemical treatment of subgrade soils to improve unstable soils has historically been done by using lime, cement and other lime/cement by products. The Michigan Department of Transportation (MDOT) generally uses remove and replace option to treat unsuitable, soft subgrade materials for construction facilitation. Based on the results of preliminary soil investigations and successful use of lime treatment for treating similar soils, a provision was included to construct lime stabilized subgrade for I-96/I-75 reconstruction project in Detroit, Michigan. Later, two test sections using Cement Kiln Dust (CKD) to stabilize subgrade were included to investigate the suitability of CKD. Pavement subgrade strength improvement through lime and CKD stabilization was evaluated using Dynamic Cone Penetrometer (DCP) measurements. As anticipated, the DCP measurements showed substantial strength improvements with both lime and CKD stabilization. Pavement performance improvement due to stabilization was investigated using the new Mechanistic-Empirical Pavement Design Guide (MEPDG). This study concludes, although subgrade stabilization was aimed at providing a stable construction platform, some pavement performance improvements can also be expected in terms of joint faulting and smoothness per MEPDG. 1

INTRODUCTION

Subgrade soils are treated with lime, cement and other lime/cement by products to treat weak, unstable subgrades. The Michigan Department of Transportation (MDOT) generally uses remove and replace option to correct unsuitable subgrade material for construction facilitation. Lime has been used successfully in one MDOT reconstruction project on I-96 in 2005 to improve unstable subgrade materials. Based on the knowledge of the native soil in the area and also through geotechnical investigations completed during the design phase of the I-75/I-96 reconstruction project, a provision was made to include lime stabilization to improve unstable subgrade areas. Later two test sections using Cement Kiln Dust (CKD) were included to investigate the suitability of CKD as a subgrade stabilization material. This study was aimed at quantifying the strength gain due to chemical stabilization of soft soils using lime, lime + flyash and CKD and investigating its effect on the pavement performance of Jointed Plain Concrete Pavement (JPCP) using the MEPDG. Lime used in soil stabilization for pavement construction contains calcium oxide (quicklime) and calcium hydroxide (hydrated lime), which are manufactured from burning limestone (calcium carbonate). Lime has been used in the past to treat soils to achieve various objectives including drying, modifying and stabilizing. Soil drying includes rapid reduction in soil moisture content due to the chemical reaction between water and quicklime. Soil modification refers to a reduction in soil plasticity, decrease in maximum dry density and improved strength and stability after compaction. Lime stabilization is a long term process where formation of various cementing agents increases the strength and durability of lime and soil mixture due to a pozzolanic reaction. Cement Kiln Dust (CKD) is a by-product of the Portland cement manufacturing process. The chemical and physical characteristics of CKD mainly depend on the cement kiln process, dust collection facility and properties of the raw material. In general, CKD contains partially calcined and unreacted raw feed, clinker dust and fuel dust. Since CKD is a by-product, the 29

chemical composition is somewhat variable and that affects the engineering properties of stabilized soils. When CKD is applied to soils, stabilization is achieved through one or more of the following mechanisms; direct cementation, reactive silica, ion exchange and moisture content decrease 2

LITERATURE REVIEW

Work related to soil stabilization for pavements dates back to the 1970’s, where Thompson developed a technical report outlining the state of the art developments in soil stabilization for pavement systems (Thompson, 1970). More recent work related to soil stabilization for pavement applications include several studies performed by Little (2008) for the National Lime Stabilization. Little (2008) has developed a Mixture Design and Testing Protocol (MDTP) for Lime Stabilized Soils, where a systematic approach on assessment of soil for lime stabilization, mixture design and testing methods were presented. Little has also performed an evaluation of structural properties of lime stabilized soils and aggregate. In 2001, Little et al. presented an example application of previously developed MDTP to evaluate engineering properties of lime-treated subgrades for mechanistic pavement design and analysis. Most recently, a study performed by Mallela et al. outlined the details on how to incorporate lime-stabilized bases in mechanistic-empirical pavement design (AASHTO, 2004). In general, most of the laboratory and field-based studies concluded, when proper attention is paid to materials, mixture design, proper construction methods, a better pavement performance can be expected through lime stabilization. Most past studies relative to CKD explored whether CKD is a hazardous material relative to use in engineering applications (PCA, 1992 and EPA, 1995). Several studies have been performed on mixture design for soil/CKD mixtures to modify or stabilize pavement subgrade soils. These studies concluded, the same mixture design procedures developed for lime/fly ash can be used for mixture design for CKD/soil mixtures. Performance of CKD as a pavement subgrade stabilizer has been studied by several researchers. Laboratory performance was investigated by Collins and Emery, where 33 CKDs and 12 Lime Kiln Dusts (LKDs) were tested for engineering properties (compressive strength, durability and volume stability) and compared with conventional lime/fly ash/ aggregate mixtures. This study concluded higher percentage of the kiln dusts are required compared to hydrated limes to achieve similar performance (Collins, 1983). Zaman et al. (1992) investigated the effect of freezing/thawing and wetting/drying cycle for the durability of CKD-stabilized clay samples. The test results showed significant strength decrease due to freezing/thawing and wetting/drying cycles (Zaman et al., 1992). Mixed field performance results were reported by several researchers from several states with soil/CKD stabilization and were summarized by Button (2003). Table 1.

Existing subgrade soil properties. Sample 1

Sample 2

Sample 3

Sample 4

Description

1.3 cm of sand over clay (4.2% sand)

7.6 cm of sand over clay (25% sand)

15.2 cm of sand over clay (50% sand)

22.9 cm of sand over clay (75% sand)

% Passing ½" Sieve % Passing #4 Sieve % Passing #40 Sieve % Passing #200 Sieve Liquid limit Plastic limit Plasticity index

100 98 97 84 32 18 14

100 99 96 73 30 16 14

100 99 96 55 29 14 15

100 99 95 42 18 12 6

30

3

PROPERTIES OF EXISTING SOILS AND MIX DESIGN

The subgrade soils for this project consist of varying thickness of fine sands (old sand subbase) underlain by low firm to soft silty clay. Four soil samples were collected from different areas of the project with varying thickness of sand to represent different subgrade soil consistencies expected on the project. The following table lists the soil analysis results for the tested existing subgrade soil samples. Two mix designs were recommended for constructing lime stabilized subgrades that met mix design parameters required in the project specification. These include 5% lime for predominantly clay subgrades and 4% lime + 8% fly ash for sand over clay areas. Fly ash was needed for sand over clay areas to provide additional cementation characteristics to the stabilization process. The CKD mix design called for one mix design with 8% CKD for both clay and sand over clay areas to meet the specification. 4

CONSTRUCTION OF STABILIZED SUBGRADE AND SUBGRADE STRENGTH TESTING

A brief comparison of lime stabilized subgrade and CKD stabilized subgrade in field placement and strength development is shown below. Field placement of lime, lime+flyash and CKD was achieved through in the following order; subgrade preparation, application of lime, lime+flyash or CKD, mixing, compaction and curing. All methods, equipment and tools used for construction of lime, lime+flyash and CKD stabilized subgrade were the same. However, to minimize early setting and dusting construction of CKD stabilized subgrade was completed in smaller areas. CKD is a finer material more prone to dusting with windy conditions. Also, the specification called for compaction within one hour of spreading for these reasons. Subgrade strength improvement due to stabilization was measured through a field testing program using the DCP as per ASTM D 6951. DCP measures the resistance to penetration due to an impact load. The penetration per blow was use to estimate the in situ CBR using correlation developed by US Army Corps of Engineers. DCP measurements also provide a log of thickness of the stabilized layer and insitu soil stiffness based on the resistance to penetration values. The following Figure shows typical DCP plot of a stabilized layer. A substantial increase in average strength was achieved through CKD stabilization as compared to lime stabilized areas as seen from the results shown in Tables 1 and 2. This is especially true for areas that were properly graded during construction, such that surface water did not pond. Areas with surface water ponded measured lesser strength than dry areas. Some researchers have observed through laboratory tests a significant loss of strength due to wetting and drying test cycles. However, continuous performance measurements are necessary to establish this observation. 5

PAVEMENT PERFORMANCE PREDICTION

The current version of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) software was used for the analysis with the original pavement performance models included in the MEPDG software. No locally calibrated pavement performance models are available at this time. However, local calibration is not required to quantify the percentage change of pavement performance indicators due to soil stabilization as investigated in this study. Pavement performance criteria considered in the MEPDG for JPCP pavements include Transverse Cracking, Transverse Joint Faulting and Smoothness (International Roughness Index or IRI). MEPDG considers the influence of traffic, environment and pavement structure to the pavement performance. The summary results of the DCP measurements are shown below in Tables 2 and 3. Traditionally Equivalent Single Axle Load (ESAL) represented the effect of traffic for the pavement design. In the MEPDG, traffic is represented by a “traffic spectra” which include 31

No. of Blows 0.00 0

10.00

20.00

30.00

40.00

50.00

100

Stabilized Layer

Penetration, mm

200

300

400

500

Insitu Soil

600

700

800

Figure 1.

Table 2.

Typical DCP results plot for a stabilized subgrade.

Average CBR results for lime/lime+flyash stabilized areas.

Tested area Mostly clay (5% lime stabilization for 30.5 cm) Mostly clay (5% lime stabilization for 35.6 cm) Mostly clay (5% lime stabilization for 45.7 cm) Sand over clay (4% lime and 8% fly ash stabilization for 30.5 cm)

Stabilized thickness based on DCP cm

Stabilized subgrade CBR %

Insitu soil CBR %

Strength gain

37.1

15.7

2.2

615%

50.3

15.4

2.9

438%

45.0

18.7

1.0

1838%

32.8

15.5

5.2

197%

axle type, distribution of axle weights and daily, weekly, seasonal volume changes. Annual Average Daily Truck Traffic (AADTT) and traffic growth rate were obtained from the traffic estimates developed during the design phase of this project. All other inputs including axle type and weight distributions, daily/weekly traffic volume changes were obtained from the national averages included in the MEPDG software as default values. Climate has a significant effect on the pavement performance. Climatic inputs together with their effects on material properties, layer thickness and drainage were incorporated to the performance prediction through the Enhanced Integrated Climatic Model (EICM) included in the MEPDG software. As with any pavement design procedure, the materials used in the structure, their properties, thickness and sequence are important in pavement performance prediction. The pavement section used in this project was based on 1993 AASHTO pavement design procedures. 32

Table 3.

DCP test results for CKD stabilized subgrade areas.

Tested area Clay (8% CKD stabilization for 30.5 cm) Moist Clay (8% CKD stabilization 30.5 cm) Retest on moist areas (after installing underdrains) Sand over Clay (8% CKD stabilization for 30.5 cm) Moist sand over clay (8% CKD stabilization for 30.5 cm)

Stabilized thickness based on DCP cm

Stabilized subgrade CBR %

Insitu soil CBR %

Strength gain

35.3

29.6

2.3

1195%

30.5

8.0

1.3

513%

30.5

15.6

1.6

789%

43.2

34.7

3.4

915%

41.1

16.9

3.3

412%

This section includes a 33 cm thick jointed plain concrete pavement (JPCP) followed by a 40.6 cm thick open graded drainage course. 5.1 Input parameters for pavement performance prediction The following input parameters were identified as extremely sensitive or sensitive to very sensitive for each pavement performance criteria in a study completed in Iowa (CTRE, 2005). The list included in the Table 4 provides the basis for identifying the effect of soil stabilization to different pavement performance parameters. By observing the above list, it can be noticed that unbound layer modulus (which include both unbound aggregate base and subgrade) was identified as a sensitive parameter on joint faulting and pavement smoothness but not for transverse cracking. Unbound layer modulus is a function of soil stabilization (due to inclusion of subgrade modulus) and pavement performance prediction results should show the effect of soil stabilization on joint faulting and pavement smoothness. The following options were selected for analysis. 1. Pavement section on existing subgrade with observed soil strength values 2. Pavement section on 61 cm of granular material over existing subgrade with observed soil strength values (to simulate the remove and replace option used to treat soft subgrades) 3. Pavement section on lime-stabilized subgrade with different thickness/strength as shown on Table 3 over existing subgrade a. Mostly Clay (5% Lime Stabilization for 30.5 cm) with insitu CBR of 2.2 b. Mostly Clay (5% Lime Stabilization for 35.6 cm) with insitu CBR of 2.9 c. Mostly Clay (5% Lime Stabilization for 45.7 cm) with insitu CBR of 1.0 d. Sand over Clay (4% Lime and 8% Fly Ash Stabilization for 30.5 cm) with insitu CBR of 5.2 4. Pavement Section on CKD Stabilized Areas as shown in Table 3 a. Mostly Clay (8% CKD Stabilization for 30.5 cm) with insitu CBR of 2.3 b. Sand over Clay (8% CKD Stabilization for 30.5 cm) with insitu CBR of 3.4 The stabilized layers were considered as an unbound layer in the analysis due to lack of calibrated performance models in MEPDG for stabilized layers. 5.2 Pavement performance results The analysis indicates subgrade improvement through stabilization or remove/replace option had a significant effect on joint faulting and smoothness. For the transverse cracking the 33

Table 4.

MEPDG input parameters. Sensitive to very sensitive input parameters

Performance model

Extremely sensitive input parameters

Transverse cracking

Curl/wrap effective temperature difference Thermal conductivity Coefficient of thermal expansion PCC layer thickness PCC strength properties Joint spacing

Edge support

Curl/wrap effective temperature difference Doweled transverse joints (load transfer mechanism)

Coefficient of thermal expansion

Curl/wrap effective temperature difference Coefficient of thermal expansion Thermal conductivity

Annual average daily truck traffic (AADTT) Doweled transverse joints (load transfer mechanism) Mean wheel location (traffic wonder) Joint spacing PCC layer thickness PCC strength properties Poisson’s ratio Surface short wave absorptivity Unbound layer modulus Cement content Water to cement ratio

Faulting

Smoothness

Mean wheel location (traffic wander) Unit weight Poisson’s ratio Climate Surface short wave absorptivity Annual average daily truck traffic (AADTT)

Thermal conductivity Annual average daily truck traffic (AADTT) Mean wheel location (traffic wonder) Unbound layer modulus Cement content Water to cement ratio

subgrade improvement had minimal effect and was removed from further consideration. This is evident by examining the input parameters identified as sensitive for transverse cracking where strength of the base/subgrade layer was not identified as a sensitive parameter. However, the input parameters identified for joint faulting and smoothness contain unbound layer modulus as a sensitive parameter. The results shown in Tables 5 include the percentage change in pavement performance from the standard section (the designed pavement section on the subgrade without stabilization or remove/replace treatment). Some improvements were observed on both mean joint faulting as well as on smoothness (IRI) for the JPCP option. The improvements were more evident for subgrade soils with lower insitu CBR values. Since the load carrying capacity of JPCP pavement mostly depends on the thickness of the concrete itself, the effect of soil improvement for JPCP pavements is minimal. Further, due to use of a 40. 6 cm thick open graded drainage course the significance of subgrade strength was further reduced. It can be seen from the above table, both the remove and replace option and stabilization options had a similar effect on performance improvement. It can be concluded that both 34

Table 5.

JPCP pavement performance summary.

Pavement area

Joint faulting % change

Description

Insitu CBR

Stabilized*

Remove/ replace**

Stabilized*

Remove/ replace**

2.2

−3.24

−4.63

−2.05

−2.63

2.9

−2.40

−2.91

−1.46

−1.84

1.0

−8.49

−7.72

−5.23

−4.80

5.2

0.00

−1.03

−0.11

−0.67

2.3

−4.67

−4.21

−2.80

−2.38

3.4

−2.97

−2.48

−2.80

−2.38

Clay—5% lime stabilization for 30.5 cm Clay—5% lime stabilization for 35.6 cm Clay—5% lime stabilization for 45.7 cm Sand over clay—4% lime and 8% fly ash stabilization Clay—8% CKD stabilization for 30.5 cm Sand over clay—8% CKD stabilization for 30.5 cm

IRI % change

*

Stabilized—Stabilization with Lime or CKD with the appropriate mix design for the depth listed. Remove/Replace—Standard treatment for soft soils, this includes removing soft soils for 24″ and replacing with sand. **

remove and replace option and soil stabilization options provide both construction facilitation as well as some pavement performance improvement. However, if the remove and replace option is used for a project, it will only be applied to selected areas. Soil stabilization typically is applied throughout the entire project are and provides more of a universal subgrade improvement methodology. Long-term performance monitoring is underway to potentially include the strength gain from subgrade improvement to the pavement design process. 6

CONCLUSIONS

A field evaluation program was performed to investigate the strength gain due to soil stabilization with lime and Cement Kiln Dust (CKD). A laboratory mix design process was performed to determine the proper lime/soil mixture and proper CKD/soil mixture. A field investigation program to assess the strength gain due to stabilization was performed using Dynamic Cone Penetrometer (DCP). Based on the test results 4 distinct lime stabilized areas and 2 distinct CKD stabilized areas were selected for summarizing field investigation results. These include, three clay areas lime stabilized to different depths, one lime stabilized sand over clay area, one clay area stabilized with CKD and one sand over clay area stabilized with CKD. The following is the summary of the strength improvement results for different subgrade areas. • 963% average strength gain was measured for lime stabilized clay areas • 197% average strength gain was measured for lime/fly ash stabilized sand over clay areas • 1055% average strength gain was measured for CKD stabilized clay or sand over clay areas A significant strength gain in terms of CBR was discovered due to lime stabilization in all tested areas. The strength gain varies from 200% to 1800% for the lime stabilized areas. CKD stabilized areas exhibited a significantly higher strength gain in the dry subgrade areas in the order of 900% to 1200%. Subgrade areas with ponded water during construction indicate relatively lesser strength gain than the dry areas (in the order of 400 % t0 500%). 35

The current version of new Mechanistic-Empirical Pavement Design Guide (MEPDG) was used to evaluate the effect of soil stabilization to the pavement performance predictions. The analysis was performed for a 33 cm thick Jointed Plain Concrete Pavement (JPCP) section over a 40.6 cm of unbound Open Graded Drainage Course (OGDC). This pavement section constructed over previously identified 6 distinct subgrade areas with subgrade stabilization as well as remove and replace of soft subgrade for 61 cm (typical MDOT treatment for soft subgrade areas) were evaluated through the MEPDG software. Comparisons were performed to investigate the remove/replace option and subgrade stabilization option in terms of mean joint faulting and IRI (smoothness). Some pavement performance improvements were observed for JPCP with both remove/ replace option and subgrade stabilization option. Pavement performance improvements were more evident for pavement sections constructed on subgrade soils with lower CBR values. Although the stabilization was intended to provide a stable construction platform, some pavement improvement can be expected in terms of joint faulting and smoothness as predicted by the MEPDG. A long term pavement performance monitoring is underway to investigate the long term performance of both lime stabilized area and CKD stabilized areas. If long term strength gain is achieved through stabilization, a provision may be made to use the subgrade strength improvement through subgrade stabilization for the future pavement design projects. REFERENCES AASHTO Guide for Mechanistic-Empirical Design of new and rehabilitated pavement structures, Final Report Prepared for National Cooperative Highway Research Program (NCHRP), Transportation Research Board, National Research Council, Washington D.C., http://www.trb.og/mepdg/guide. htm, Accessed June 16, 2008. Button, J.W. 2003. Kiln Dust for Stabilization of Pavement Base and Subgrade Materials, Report No. TTI-2003–1, Texas Transportation Institute, College Station, Texas. Collins, R.J. & Emery, J.J. 1983. Kiln Dust-Fly Ash Systems for Highway Bases and Subbases, Report No. FHWA/RD-82/167, Federal Highway Administration, Washington D.C. CTRE, 2005. Implementing the M-E Pavement Design Guide in Iowa, Center for Transportation Research and Education, Ames, Iowa. EPA, 1995. Regulatory Determination on Cement Kiln Dust, Environmental Protection Agency, Federal Register, 40 CFR Part 261. Little, D.N. 1999. Evaluation of Structural Properties of Lime Stabilized Soils and Aggregates, Volume 1: Summary of Findings, National Lime Association, http://www.lime.org/SOIL.PDF, Accessed July 14, 2008. Little, D.N. 2000. Evaluation of Structural Properties of Lime Stabilized Soils and Aggregates, Volume 3: Mixture Design and Testing Protocol for Lime Stabilized Soils, National Lime Association, http:// www.lime.org/SOIL3.PDF, Accessed July 1, 2008. Little, D.N. & Shafee Yusuf, F.A.M. 2001. Example Problem Illustrating the Application of the NLA MDTP to Ascertain Engineering Properties of Lime-Treated Sub grades for Mechanistic Pavement Design/Analysis, National Lime Association, http://www.lime.org/AMDTP.pdf, Accessed June 16, 2008. PCA, 1992. An Analysis of Selected Trace Metals in Cement and Kiln Dust, Serial No. SP 109 T, Portland Cement Association, Skokie, Illinois. Thompson, M.R. 1970. Soil Stabilization for Pavement Systems—State of the Art. Technical Report, Champaign, IL, Department of the Army, Construction Engineering Research Laboratory. Zaman, M., Laguros, J.G. & Sayah, A. 1992. Soil Stabilization Using Cement Kiln Dust, Proceedings, 7th International Conference on Expansive Soils, Dallas, Texas, pp. 1–5.

36

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Study of dry sludge stabilization from Water Treatment Plant (WTP) in Taiaçupeba to use as compacted soil in earthwork ditches R.M. Fortes & J.V. Merighi Mackenzie Presbyterian University, Research Group of CNPq “Mackenzie—Sistemas Viários”, Brazil

D.R. Pauli, M.A.L. Barros, M.H. de Carvalho & N.C. Menetti SABESP—Companhia de Saneamento Básico do Estado de São Paulo, Brazil

Á.S. Barbosa, F.V. Ribeiro & B.B. Bento LENC—Laboratório de Engenharia e Consultoria Ltda, Brazil

ABSTRACT: The present paper is part of a research study that has been carried since 2005 in the Mackenzie University. This research takes part in the Research Group of CNPq denominated “Sistemas viários (Road Systems)” for use of the sludge from the water or sewage disposal treatment. The study involves procedure of dosage with addition of chemical stabilization products as the hydrated lime or the Portland cement and soil for potential use in workmanships of earthwork ditches. Moreover, this research intends to study the technician-economic-environmental viability of the improvement in the dry sludge generated by the water treatment plant of Taiaçupeba, searching for the stabilization of this material to use as compacted soil in earthwork ditches. 1

INTRODUCTION

São Paulo, a city located in the southeast of Brazil, is 1,509 km2 large, with a population of 19 million inhabitants and problems in the same proportion in terms of urban pavements. In many cases, it is found at least six public concessionaire’s companies associated with municipality activities. In downtown, under a plenty of pavements, there are telephonic cables, gas, energy line, TV cable, petroleum, water and sewage disposal facilities, etc. Considering that all the concessionaries need to do the maintenance, it is common, the pavement surface become a mosaic mess, motivated by innumerous repairs (Fortes et al., 2006a). This fact contributes to a substantial increase of the emergencies services of conservation that includes covering holes. The local water and sewage disposal facilities concessionaire, named Companhia de Saneamento Básico do Estado de São Paulo (SABESP), is present in 367 cities of the State of São Paulo, being responsible for the management of the water distribution and sewer system (SABESP, 2008 (a)). The execution of this type of repair involves special cares in the resetting of the structure. On this aspect, it is possible to prevent the water or sewer canalizations, under the pavements, to enlarge the problems of the subgrade consolidation and finally of the pavement structure motivating its rupture and also the pipelines. A planning contemplating all different concessionaries and the city hall is practically unexecutable for many reasons. It is common that, after a rehabilitation or construction of an urban pavement, a concessionaire intervention occurs, because it is impossible to foresee workmanships emergencies that need a ready fix by the concessionaire. Many proposals have been presented in the direction of managing these problems, developing management tools of the pavements, searching to reduce the negative impact of these workmanships, but so far, none has shown effectiveness (Fortes et al., 2008). 37

These repairs are more than 1,500 potholes per day (over than 550,000 per year), due to the water or sewage disposal outflow (Fortes et al., 2005). Considering the water or sewage disposal outflow, the soil used in the earthwork ditches isn`t suitable to be reused, since it is saturated or contaminated, needing to be removed and substituted (Fortes, 2006b). This fact creates the necessity of searching soils deposits, a task which is becoming almost unexecutable considering that the exploration of the available deposits is more and more difficult. On the other hand, the process used in Water Treatment Plants (WTPs) removes suspended particles from water by sedimentation and filtration processes, resulting in waste production (Guerra; Angelis, 2005). The sludge from the water or sewage disposal treatment is considered a solid residue which the final destination has been hardly questioned. The Brazilian standard NBR 10004-Solid waste—Classification (2004) classify it in different danger levels and defines that this residue must be treated. Considering the risks to the environment and to the public health, the NBR 10004 also stabilizes the criteria for final deposition. The development of a sustainability technology for the utilization of this material is significant and vital. The Taiaçupeba sludge is, according to NBR 10004 (2004), classified as Classroom IIA— No Inert. It means that the residue is not considered dangerous. This research intends to study the technician-economic-environmental viability for the improvement of the dry sludge generated by the water treatment plant of Taiaçupeba, searching the stabilization of this material to use as compacted soil in earthwork ditches. 2

WATER TREATMENT PLANT (WTP) OF TAIAÇUPEBA

The water treatment plant of Taiaçupeba is located in Suzano, near São Paulo: it produces almost 12 tons of dry sludge per day. The use of this technology saves the environment and the financial benefits, taking into account the transportation cost and the final disposal of this material, are from US$25 to US$50 per ton (SABESP, 2008a). The Alto Tietê Producing System was conceived in stages because of its complexity. Taiaçupeba was projected in 5 modules of m3/s each. In March of 1992 was implanted the first stage with nominal productive capacity of 5.0 m3/s. Nowadays WTP operates with the nominal capacity of 10 m3/s, treating on average 9.8 m3/s that they supply about 2.5 million resident people of the Great São Paulo east region. Figure 1 shows an aerial sight of the Water Treatment Plant. The currently operation system is composed basically of two consolidation type rotating drum with 60 m3/h and centrifugal condensation of capacity of 30 m3/h each one. This system of sludge condensation and dewatering processes produces daily about 60 tons of dehydrated sludge with in medium18% of total solid. Figure 2 illustrates the condensed and dewatering sludge.

Figure 1.

Aerial sight of Taiaçupeba water treatment plant.

38

Figure 2.

Condensed and dewatering (a); transportation of sludge (b).

Figure 3.

Dewatering sludge localization (a) Drying process (b).

Sludge drying process reduces mass and volume of the product, making its storage and transport (Flaga, 2005). This residue is transported and deposited into two waterproofed landfill cells, for dewatering to obtain almost 50% (or more) of the total possible dry solids (DS) concentration (SABESP, 2008b). The pos dewatering sludge is illustrated in Figure 3. 3

SCOPE OF THE RESEARCH

This research is being developed in mutual cooperation between the SABESP and the Mackenzie Presbyterian University, with the contribution of the LENC (a technological and consultant company) in the execution of the physical and chemical characterization tests. This deal was signed on February, 14th, 2008, when SABESP organized a Sustainability and Innovation Audience about one of most controversial subjects: the final destination of the sludge generated in the water treatment process (SABESP, 2008a). In the physical characterization, the specimens was compacted in the Proctor standard energy according to NBR 7182 (1986), in the small mold. The samples were: “pure” sludge with 50% and 85% of solids content; with addition of 3% and 5% of hydrated lime and 3% and 5% of Portland cement, in two situations: with mixture and immediate compacting and after 3 days of cure, as discriminated in Table1. In this research have been molded cylindrical specimens as determined by the Brazilian Standard Test Method (DNER ME 202/1994) (Figure 4) and carried through the determination of the compressive strength test (NBR 12025/1990; DNER ME 201/1994) and determination of the tension strength of cylindrical specimens submitted to diametrical compression (NBR7222/1994), as a recommendation of Little et al. (2000). 39

Table 1.

Results.

7 days

Tension strength Mini (MPa)* CBR 28 days 28 days (%)**

Expansion (%)**

– – 0.90 0.60 0.66 0.84 – 0.53 0.75

– – 0.76 1.04 0.94 1.05 – – 1.20

0.25 – 0.29 0.19 – – 0.17 0.29 0.17

Compressive strengths (MPa)

Sp

Maximum dry Optimum unit weight moisture (kg/m3) content (%)

1 day

3 days

1 2 3 4 5 6 7 8 9

870 1,290 1,380 1,370 1,210 1,210 1,250 1,410 1,410

– – 0.20 0.50 0.21 0.28 – 0.51 0.76

– – 0.60 0.80 0.46 0.55 – 0.50 0.67

51.0 43.3 26.4 33.1 35.9 33.3 32.6 29.7 27.5

– – 0.02 0.07 0.003 0.03 – – 0.12

12.0 – 25.0 24.9 – – 18.0 23.6 25.2

Sp = Specimen. 1 2 3 4 5 6 7

Sludge with 3% of hydrated lime—mixture and immediate compacting (50% of solids content) Sludge (85% of solids content) Sludge with 3% of hydrated lime—mixture and immediate compacting (85% of solids content) Sludge with 3% of Portland cement—mixture and immediate compacting (85% of solids content) Sludge with 3% of hydrated lime—after 3 days of cure (85% of solids content) Sludge with 3% of Portland cement—after 3 days of cure (85% of solids content) 45% of soil + 50% of sludge + 5% of hydrated lime—mixture and immediate compacting (50% of solids content) 8 Sludge with 5% of hydrated lime—mixture and immediate compacting (85% of solids content) 9 Sludge with 5% of Portland cement—mixture and immediate compacting (85% of solids content) * Determination of the tension strength of cylindrical specimens submitted to diametrical compression (Fortes et al., 2008). ** (Fortes et al., 2006b).

Figure 4.

Specimen molded.

It was also used a mini CBR test, that is similar to the CBR (California Bearing Ratio), different in terms of the specimen size obtained through a compaction procedure called the mini Proctor. The mold has a diameter of 50 mm and a volume of 100 ml. The sample mass is 250 g, and the maximum grain diameter is 2 mm. The diameter of the penetration piston (plunger) is 16 mm, while the loading machine has a capacity and speed of 4.5 kN and 1.25 mm/min, respectively. There are two compactation rammers used for compaction: (a) standard energy rammer weighing 2.27 kg, height of drop 305 mm, blows—10 total or 5 per side and (b) the 40

Percent passing (%)

sieve no.

Particle diameter (mm) – log scale Figure 5.

Particle-size distribution of the sludge.

Figure 6.

Compressive strengths (MPa).

intermediate energy rammer weighing 4.5 kg, height of drop 305 mm, blows—12 total or 6 per side. Soaking time is 24 hours. If not soaked, expansion can be determined as in the CBR test. This test is used in the MCT methodology (Fortes & Merighi, 2003). The specific gravity of the sludge solids (85% of solids content) is 2,715 kg/m3. The particle-size distribution of the sludge is showed in Figure 5. The results are presented in Table 1. It is observed that this material is composed by 66.1% of sand, 30.7% of silt and 3.2 of clay. Figures 6 and 7 present the compressive strengths and the tensile strengths of cylindrical specimens submitted to diametrical compression graphics, respectively. 41

diametrical tension strength (MPa)

0,1

0,08

0,06

0,04

0,02

diametrical tension strength (MPa)

0,12

0 Sludge with 3% of Sludge with 3% of Sludge with 3% of Sludge with 3% of Sludge with 5% of hydrated limePortland cementhydrated limePortland cement- Portland cement mixture and mixture and after 3 days of after 3 days of mixture and immediate immediate cure (85% of cure (85% of immediate compacting (85% compacting (85% solids content) solids content) compacting (85% of solids content) of solids content) of solids content) Specimen

Figure 7.

4

Tensile strengths of cylindrical specimens submitted to diametrical compression.

DISCUSSION OF RESULTS

The Taiaçupeba sludge with 85% of solids content stabilized using 5% of hydrated lime, according to the NBR 10004 (2004) classification change of Classroom IIA—No Inert to Inert, in other words, the addiction of the hydrated lime allows its utilization as compacted soil in earthwork ditches. Furthermore, its mechanical characteristics attend the local specifications satisfactorily, presenting values of California Bearing Ratio of 12%, with 0.25% expansion. The increase of the mechanics strength with bigger additions of air binder, discloses, according to Nún ˘ez et al (2005), the occurrence of a cementation. The values taken for the compressive strength and tensile strength for diametrical compression are acceptable for its use in earthwork ditches. It is important to point out that the use of the dosage with addition of 45% of soil plus 50% of sludge and 5% of hydrated lime, it is relatively important to take into account the mechanical behavior presented in a better performance, beyond presenting a lesser expansion value. Not only does this new dosage brings the advantage to mix this material with soil, but also diminish the heavy mineral presence that can be presented in the sludge, even so the classification has given to Classroom II A—no inert. Bandeira, Merighi and Fortes (2008) presented an analysis through the use of the computational program of finite elements ANSYS, of the structural behavior of airport pavements, considering an aircraft with maximum load of 540 kN (EMB 195), with pressure of application of the tire of 1,083 MPa and wheel load of 125 kN, they obtained 0.5 MPa as the compression strength in 100 mm of depth and tensile strength from the triple state of tension of 0.01 MPa. Analyzing all the studied dosages, it is verified that the same ones had presented better values that one, so it is possible to conclude that on the point of view of the mechanical characteristics, this material can be used in earthwork ditches, or in layers of sub-base of airport pavements, therefore they attend the recommendation of the support capacity (superior to 20%) and expansion values less than 1.0%, beyond the values of compression and tension strengths. In one of these research studies, it was possible to notice that it was carried through the PCA (2003) for clay stabilization with Portland cement addition, the authors searched ten 42

types of different soils, and had found a value of 0.19 MPa to compression strength for A6 soil (8) without no Portland cement addition, being that with 3% of Portland cement in weight, the value passed to 1.44 MPa and with 5% for 2.22 MPa to the 7 days of age. It was observed that with 28 day, this soil presented 1.85 and 2.84 MPa for 3 and 5% of Portland cement in weight, respectively. Also tests with mixed samples and compacting after 24 hours, founding inferior values to the taken ones with the immediate compacting. On top of that it suits standing out that similar values had been found in this present research. The results obtained with addition Portland cement had been more promising that obtained with addition of hydrated lime. However, considering that the samples stabilized with this last binder had presented acceptable values, its use is very interesting, being a kind of air binder and does not require care in its stockage, allowing its preparation foresaw.

5

CONCLUSIONS

Little et al. (2000) affirmed that the reactions between the hydrated lime and the soil are complex. The pozzolan reaction that occurs between the air binder and the silica and/or aluminum of the soil is the solution for an effective and durable stabilization of it. This affirmation strengthens that when adding the hydrated lime or Portland cement to the sludge, its chemical composition is modified, thus, will be carried through chemical analyzes to verify the changes in the composition of the mixture considering the recommendations of NBR 10004 standard (2004). The new steps of this research contemplate an experiment in field using this material stabilized with hydrated lime and lime in earthwork ditch. All these mixtures will be carried through chemical analyses for verification of the presence of solid residues, as iron, aluminum, manganese, and the mixture PH. The samples will be analyzed on the point of view of the mechanical behavior, getting the values of the support capacity with and without immersion, resistance the compression (7 and 28 days) and the diametrical traction (28 days). The proposal of the mixtures with hydrated lime or Portland cement addition study, cure and posterior compacting, inhabits in the preparation easiness that can occur in a plant or the seedbed. The material previously would be prepared, excusing the constructor to add/to dose the binder in the hour to apply, what will prevent losses, beyond providing a bigger technological and quality control of the material to be used in earthwork ditches. The authors are motivated by the promising results, and feel that this research contributes for the environment and sustainability point of view because of rehabilitate a residue conferring the necessary quality for its application in civil constructions. They really believe in the technician-economic-environmental viability of this technology.

REFERENCES Associação Brasileira De Normas Técnicas—ABNT NBR7182 Solo—Ensaio de compactação (Soil— Compaction testing—Method of test). Rio de Janeiro, 01/08/1986. 10p. Associação Brasileira De Normas Técnicas (ABNT). NBR7222 –Argamassa e concreto—Determinação da resistência à tração por compressão diametral de corpos-de-prova cilíndricos (Mortar and concrete—Determination of the tension strength of cylindrical specimens submitted to diametrical compression—Method of test). Rio de Janeiro. 1994, 3p. Associação Brasileira De Normas Técnicas—ABNT NBR 10004—Resíduos sólidos—Classificação (Solid waste—Classification). Rio de Janeiro, 2004. Associação Brasileira De Normas TÉCNICAS—ABNT NBR12025 Solo-cimento—Ensaio de compressão simples de corpos-de-prova cilíndricos (Soil Cement—Compression Testing of Soil-cement specimens—Method of Test). Rio de Janeiro, 30/12/1990, 2p. Bandeira, Alex Alves; Merighi, João Virgilio, Fortes, Rita Moura. A Study of the HMA Layer Thickness Reduction When Applied Over Lateritic Soils Cement Base in Airfield. In Proceeding of 10th International Conference on Application of Advanced Technologies in Transportation—AATT 2008. Athens, Greece. May 27th–31st, 2008.

43

Companhia De Saneamento Básico Do Estado De São Paulo—SABESP. Lodo no processo de tratamento. 2008 (a). Disponível em: http://www.sabesp.com.br/CalandraWeb/CalandraRedirect?temp=6 &proj=sabesp&pub=T&nome=documento_noticias&db=&docid=DD43D7 A22199 AD4E832573F 00073067E Companhia De Saneamento Básico Do Estado De São Paulo—SABESP. O que fazemos\Tecnologia\ Disposição dos lodos. 2008 (b). Disponível em: http://sabesp.com.br/CalandraWeb/CalandraRedirec t?temp=4&proj=sabesp&pub=T&db=&docid=3D233B8527E8304E832571B1006B31FC Departamento Nacional De Estradas De Rodagem DNER ME 201/94—Solo—cimento—compressão axial de corpos de prova cilíndricos. Rio de Janeiro. 1994, 4p. Departamento Nacional De Estradas De RODAGEM DNER ME 202/94—Solo—cimento—moldagem e cura de corpos de prova cilíndricos. Rio de Janeiro. 1994. Departamento Nacional De Estradas De RODAGEM DNER ES 305/97—Pavimentação—base de solo cimento. Rio de Janeiro. 1997, 10p. Flaga A. Sludge Drying. www.lwr.kth.se/forskningsprojekt/Polishproject/Flagasludgedrying73.pdf. Accessed in September, 2008. Fortes, Rita Moura & Merighi, João Virgilio. The use of MCT Methodology for Rapid Classification of Tropical Soils in Brazil IJP—International Journal of Pavements, Vol.2, No.3, September 2003, pp.1–13. Fortes, Rita Moura; Zuppolini Neto, Alexandre; Menetti, Nélson César; Barbosa Jr., Álvaro S. & Merighi, Cecília Fortes “A importância do Controle Tecnológico e de Qualidade na Reabilitação de Pavimentos após a intervenção de concessionárias em São Paulo”. 36ª Reunião Anual de Pavimentação, ABPv—Associação Brasileira de Pavimentação, Curitiba—PR, Brasil, 24 a 26 de agosto de 2005. Fortes, Rita Moura; Zuppolini Neto, Alexandre; Menetti, Nélson César; Barbosa Jr., Álvaro S. Potencial da Utilização do ensaio de penetração dinâmica da metodologia MCT para controle da construção de valas. V Jornada Luso-Brasileira De Pavimentos: Políticas E Tecnologias. Andit, Universidade Presbiteriana Mackenzie, Feup—Faculdade de Engenharia da Universidade do Porto—Portugal, Ca Md. Recife, Pernambuco, Brasil, 5–7 de julho de 2006 (a). Fortes, Rita Moura; Zuppolini Neto, Alexandre; Menetti, Nélson César; Barbosa Jr., Álvaro S. Estudo da dosagem com cal de lodo oriundo do tratamento de água. V Jornada Luso-Brasileira De Pavimentos: Políticas E Tecnologias. Andit, Universidade Presbiteriana Mackenzie, Feup—Faculdade de Engenharia da Universidade do Porto—Portugal, Ca Md. Recife, Pernambuco, Brasil, 5–7 de julho de 2006 (b). Fortes, Rita Moura; Merighi, João Virgilio; Pauli, Dante Ragazzi; Barros, Marco Antonio L; De Carvalho Magda H.; Menetti, Nélson César; Barbosa Jr., Álvaro S.; Ribeiro, Fabio Vaz; Bento, Benicio Bibiano. 02–005—Estudo da estabilização de lodo oriundo da estação de tratamento de água (ETA) de Taiaçupeba para utilização com material em reaterro de valas. 2008 Coninfra—Congresso De Infra-Estrutura De Transportes. Andit—Associação Nacional de Infra-estrutura de Transportes. ISSN 1983–3903. São Paulo, São Paulo, Brasil, 25 a 28 de Junho de 2008. Guerra, R.C.; Angelis, D.F.D. Classificação E Biodegradação De Lodo De Estações De Tratamento De Água Para Descarte Em Aterro Sanitário Arq. Inst. Biol., São Paulo, v.72, n.1, p.87–91, jan./mar., 2005. www.biologico.sp.gov.br/docs/arq/V72_1/guerra.PDF. Accessed in September, 2008. Little, Dallas N.; Males, Eric H.; Prusinski, Jan R. & Stewart, Barry. Cementitious Stabilization. A2 J01: Committee on Cementitious Stabilization—Transportation in the New Millennium. TRB, 2000. http://onlinepubs.trb.org/Onlinepubs/millennium/00016.pdf Núñez, W.P.; Lovato, R.S.; Malysz, R. & Ceratti, J.A.P. Revisiting Brazilian State Road 377: A well-succeded case of lime-stabilized Road base. Second International Symposium on Treatment and Recycling of Materials—TREMTI 2005, Paris, October 24–26, 2005. Communication C036. 11p. Portland Cement Association—Pca. Properties and Uses of Cement-Modified Soil. 2003. Item Code: IS411. 12p. Disponivel em: http://www.cement.org/bookstore/profile.asp?store=&id=273

44

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Alternatives to heavy test rolling for cohesive subgrade assessment D.J. White, P.K.R. Vennapusa, H.H. Gieselman & L. Johanson Earthworks Engineering Research Center (EERC), Iowa State University of Science and Technology, Ames, Iowa, USA

J. Siekmeier Minnesota Department of Transportation (Mn/DOT), Maplewood, Minnesota, USA

ABSTRACT: This paper describes comparison measurements to assess support conditions of compacted cohesive subgrade materials using heavy test rolling, roller-integrated compaction measurements, and light weight deflectometer (LWD) and dynamic cone penetrometer (DCP) point measurements. Results indicate that many of these measurements are empirically related. Further, roller measurement values and LWD/DCP point measurements can reliably indicate the rut depth under test rolling. Target values for QA are developed for these different measurements with respect to the Minnesota Department of Transportation (Mn/ DOT) heavy test rolling criteria for rut depth <50 mm. DCP profiles on compacted subgrade layers show vertical non-uniformity typically with a stiff layer underlain by a soft layer. Support capacities of the subgrade under the heavy test roller were analyzed using a layered bearing capacity solution and compared to measured rut depths at the surface. A simple chart solution is presented to determine target shear strength properties of compacted subgrades from DCP profiles to ensure heavy test rolling rut depths are less than the maximum allowable limit. 1

INTRODUCTION

The performance and durability of pavement structures depend heavily on the foundation layer support conditions. Several in-situ testing methods have been developed over the past five decades to evaluate the support capacities of the subgrade layers in-situ during construction. Recently, there has been growing interest in evaluating alternatives to traditional quality assurance (QA) point measurements and to heavy test rolling for Minnesota Department of Transportation (Mn/DOT) projects. Two different roller-integrated compaction measurement technologies along with comparisons to dynamic cone penetrometer (DCP) and light weight deflectometer (LWD) point measurements are discussed in this paper. Heavy test rolling is a widely used quality assurance (QA) technique on earthwork construction projects in Minnesota for the subgrade pavement foundation (Mn/DOT 2000). Test rolling is performed using a pneumatic wheel roller on a compacted surface and the ruts observed beneath the wheels are measured to assess the support conditions. Test rolling has the advantage of providing a continuous visual record; however, it can be difficult and expensive to setup and operate. Roller-integrated compaction monitoring (also referred to as continuous compaction control or intelligent compaction) aided with global positioning system (GPS) were investigated as alternatives to test rolling because the measurements can be viewed in real-time during the compaction process and the data provides100% coverage. Two different rollerintegrated compaction measurement technologies are discussed in this paper: (1) Geodynamik compaction meter value (CMV) and (2) machine drive power (MDP). Regardless of the type of measurement technology, by making the compaction machine a measuring 45

device, the compaction process can be better controlled to improve quality, reduce rework, maximize productivity, and minimize costs, etc. While compaction monitoring technologies offer significant advantages, to successfully implement the technology it is necessary to develop an understanding of their relationships to conventionally used test measurements—in this case heavy test rolling. The approach for implementation in Minnesota has been to develop material and site specific target roller measurement values and LWD values (see Mn/DOT 2006, White et al. 2008). LWD and DCP are rapid in-situ quality control/assurance (QC/QA) testing tools that are being widely evaluated by several agencies across the globe in earthwork construction practice. LWD testing is relatively rapid compared to DCP testing and has the advantage of providing modulus values which can be related to modulus values used in pavement design. The measurements are typically influenced by material beneath the plate up to a depth equal to the diameter of the loading plate (Kudla et al. 1991). Dynamic cone penetration index (DPI) measured from the DCP test is inversely related to soil strength/stiffness properties and is well discussed in the literature (e.g. McElvaney & Djatnika 1991, Konrad & Lachance 2001). Correlations developed between DPI and undrained shear strength properties are presented later in this paper. A major advantage of the DCP test is that it creates a near continuous vertical record of penetration resistance typically up to a depth of about 1 m, which is critical for detecting vertical non-uniformity in compacted fill materials. In this paper, support capacities of the subgrade under a test roller is analyzed using DCP profiles and classical layered bearing capacity solution proposed by Meyerhof & Hanna (1978). Recent field studies assessing compaction quality for cohesive embankment subgrades in Minnesota and Iowa (see White et al. 2007, Larsen et al. 2008) documented significant vertical non-uniformity in soil strength/stiffness properties. This condition is generally a result of poor moisture control and overly thick lift placement. An example of vertical non-uniformity from US14 construction project in Janesville, MN on compacted glacial till material is presented in Figure 1 (White et al. 2007). DCP tests conducted at five select locations in an area of compacted subgrade showed significant vertical non-uniformity based on undrained shear strength profiles at each point (undrained shear strength su values estimated from DPI using a correlation presented later in this paper). Heavy test rolling performed in this area using a 133.5 kN (15 ton) pneumatic tire roller showed rutting on the order of 50 mm at points 1, 2, and 4 and minimal rutting at points 3 and 5. The comparatively-wet moisture content at the surface and low undrained shear strength conditions have contributed to rutting under the test roller at points 1, 2, and 4. The presence of vertical non-uniformity in the support conditions of subgrades is of consequence as it can potentially affect the performance of the overlying pavement structures. In brief, the key objectives of this paper are to: (a) evaluate empirical relationships between rut depth measurements from heavy test rolling and roller integrated measurement values, and LWD/DCP point measurement values, (b) demonstrate an approach to develop target values for roller and point measurement values relating to conventionally accepted rut depth su (kPa) 0

50

100 150 200 250

0

Point 5 100

Point 1

w = 12%

w = 23%

Depth (mm)

200 300 400 1 2 3 4 5

500 600

Rut Depth > 50 mm

Rut Depth < 50 mm

700

Figure 1.

DCP-su profiles from compacted glacial till subgrade at US14 (White et al. 2007).

46

measurements, and (c) evaluate the effect of vertical non-uniformity in soil shear strength profiles on bearing capacity under the test roller. 2

BACKGROUND

2.1 Roller-integrated compaction measurements A CP-563 12-ton padfoot roller equipped with vibratory or static rolling resistance based MDP system (Fig. 2a) and a CS-683 19-ton smooth drum roller equipped with vibratory accelerometer based Geodynamik CMV system were used in this study (Fig. 2b). Controlled field studies documented by White & Thompson (2008) and Thompson & White (2008) verified that roller-integrated machine drive power (MDP) can reliably indicate soil compaction for granular and cohesive soils. The basic premise of determining soil compaction from changes in equipment response is that the efficiency of mechanical motion pertains not only to the mechanical system but also to the physical properties of the material being compacted. MDP is calculated using Equation 1. ⎛ A⎞ MDP = Pg − WV ⎜ sinα + ⎟ − ( mV + b) g⎠ ⎝

(1)

where Pg = gross power needed to move the machine (kJ/s), W = roller weight (kN), A = machine acceleration (m/s2), g = acceleration of gravity (m/s2), α = slope angle (roller pitch from a sensor), V = roller velocity (m/s), and m (kJ/m) and b (kJ/s) = machine internal loss coefficients specific to a particular machine (White et al. 2005). MDP is a relative value referencing the material properties of the calibration surface, which is generally a hard compacted surface (MDP = 0 kJ/s). Positive MDP values therefore indicate material that is less compact than the calibration surface, while negative MDP values would indicate material that is more compacted than the calibration surface (i.e. less roller drum sinkage). The MDP results presented in this paper (hereafter referred to as MDP*) are adjusted on a 1 to 150 scale. The calibration surface with MDP = 0 (kJ/s) is scaled to MDP* = 150, and a soft surface with MDP = 111.86 (kJ/s) is scaled to MDP* = 1 (Mario Souraty, Caterpillar Inc., October 2007, email comm.). The relationship to calculate MDP* from MDP is provided in Equation 2 (note that as compaction increases MDP decreases and MDP* increases). (a)

(b)

(d)

(e)

(c)

(f)

(g)

Figure 2. (a) CP-563 roller, (b) CS-563 roller, (c) Towed pneumatic dual-wheel test roller with 650 kPa contact tire pressure, (d) Shelby tube sampler, (e) DCP, (f) Zorn 200-mm diameter plate LWD, (g) 6.2 kN capacity static plate load test setup.

47

MDP* = 119.7 − 0.798 × (MDP )

(2)

The CMV technology uses accelerometers to measure drum accelerations in response to soil behavior during compaction operations. The ratio between the amplitude of the first harmonic and the amplitude of the fundamental frequency provides an indication of the soil compaction level (Thurner & Sandström 1980). An increase in CMV indicates increasing compaction. CMV is calculated using Equation 3. CMV = C ⋅

A1 A0

(3)

where C = constant (300), A1 = acceleration of the first harmonic component of the vibration, and A0 = acceleration of the fundamental component of the vibration (Sandström & Pettersson 2004). CMV is a dimensionless parameter that depends on roller dimensions (i.e. drum diameter, weight) and roller operation parameters (i.e. frequency, amplitude, speed). CMV at a given point indicates an average value over an area whose width equals the width of the drum and length equal to the distance the roller travels in 0.5 seconds (Geodynamik ALFA-030). 2.2 Test rolling Test rolling was performed using a pneumatic tire two-wheeled trailer with a 267 kN axle weight (Fig. 2c) in accordance with Mn/DOT specifications (Mn/DOT 2000). The two wheels on the trailer were spaced 1.8 m apart, and the wheels were inflated to approximately 650 kPa. The contact width and length of the wheel were specified as 0.46 m (width) × 0.45 m (length). The depth of the rut beneath the roller wheels was measured from the top of the subgrade. If measured rut depths are ≥50 mm, the subgrade is considered unstable and it is specified to treat the subgrade appropriately (Mn/DOT 2000). 2.3 In-situ point measurements Four different in-situ test methods were employed in this study to evaluate the in-situ support conditions: (1) undisturbed Shelby tube (ST) samples, (2) dynamic cone penetrometer (DCP), (3) light weight deflectometer (LWD), and (4) static plate load test (PLT). Undisturbed samples of compacted subgrade material were obtained by hydraulically pushing 71 mm diameter Shelby tube samples (Fig. 2d). The tube samples were sealed and transported to the laboratory for unconfined compression testing in accordance with ASTM D2166-91 to determine undrained shear strength, su. DCP tests were performed in accordance with ASTM D6951-03 to measure DPI (Fig. 2e). DPI values determined for correlations presented later in this paper are determined as the ratio of 200 mm penetration depth and cumulative number of blows to reach that penetration depth. Zorn LWD tests were performed using a 200 mm diameter bearing plate setup with a 10 kg weight dropped from a height of 50 cm in accordance with manufacturer recommendations. ELWD-Z2 was determined following manufacturer recommendations (Zorn 2003) (assuming Poisson’s ratio ν = 0.4 and shape factor f = π /2). For surfaces with padfoot indentations, a level surface was prepared for testing by removing the material to the bottom of padfoot penetration to ensure repeatable results. Static PLT’s were conducted by applying a static load on 300 mm diameter plate against a 62 kN capacity reaction force. The applied load was measured using a 90 kN load cell and deformations were measured using three 50 mm linear voltage displacement transducers (LVDTs). The load and deformation readings were continuously recorded during the test using a data logger. 3

EXPERIMENTAL TESTING

Tests reported in this paper were collected from two cohesive embankment subgrade construction projects: (1) US14 located near Janesville, MN and (2) TH60 located near 48

Table 1.

Summary of soil index properties.

Parameter Material description Standard proctor maximum dry unit weight γdmax (kN/m3) Optimum moisture content wopt (%) Liquid Limit, LL Plasticity Index, PI USCS group symbol USCS group name

Test method – ASTMD 698-00

ASTMD 4318-93

ASTMD 2487-93/ 2488-93

US14 Janesville, MN

TH60 Bigelow, MN Site A

Site B

Site C

Site D

Brown glacial till –

Brown glacial till 16.35

Brown glacial till 17.19

Brown glacial till 18.24

Dark Brown topsoil 16.72

–

19.3

17.3

13.3

17.3

–

43

39

36

39

–

16

19

15

11

CL

CL

CL

CL

OL

Sandy lean clay

Lean clay with sand

Sandy lean clay

Sandy lean clay

Sandy organic clay

Bigelow, MN. Results from US14 are shown in Figure 1, and soil index properties are presented in Table 1. Four sites (Site A, B, C, and D) were tested on the TH60 project. A summary of soil index properties are provided in Table 1, and a brief summary of site conditions are provided below. Sites A and B consisted of one-dimensional test strips with uncompacted fill material of thickness in the range of about 0.25 to 0.50 m. The fill material was placed with average moisture contents of about 20.0% and 19.2%, respectively. The test strips were compacted using the CP-563 padfoot roller using constant machine amplitude a = 1.87 mm, frequency f = 30 Hz, and speed v = 3.2 km/h. In-situ point measurements (DPI and ELWD-Z2) were obtained in conjunction with the roller compaction measurements. ST samples were obtained after the final pass from the compacted subgrade layer at site A for unconfined compression testing. Site C consisted of a compacted subgrade material with plan dimensions of about 7.5 m × 30 m. The compaction layer was placed at an average moisture content of about 12.5%. The area was test rolled and rut depth measurements were obtained from 11 test locations. LWD and DCP point measurements were obtained at the rut depth locations. ST samples were obtained from select point measurement locations for unconfined compression testing. The area was then mapped using the CS-683 smooth drum roller using constant machine operation settings a = 0.85 mm, f = 30 Hz, and v = 3.2 km/h. Site D was located in a median area with dark brown topsoil material. LWD, DCP, and static PLT measurements were obtained from this site. 4

TEST RESULTS AND DISCUSSION

4.1 Correlations between different QA test measurements Relationships derived from experimental testing described above are summarized in Figure 3. The relationships are first discussed below and then target values are derived based on the relationships and compared with target values used on the project. A non-linear relationship was found between DPI and undrained shear strength, su (Fig. 3a). This relationship was developed based on unconfined compression tests performed on samples obtained from 49

50

Log ( su) = 3.26 - 0.81 Log (DPI)

(a)

McElvanet and Djatnika (1991) Site A Site C

150 100 Log (s u) = 2.95 - 0.67 Log (DPI) ? R 2 = 0.58 n = 23

50

Log (E LWD ) = 2.30 - 0.74 Log (DPI)

(b)

40 E LWD-Z2 (MPa)

su (kPa)

200

R 2 = 0.73 n = 86

30 Site A Site D Site C

20 10

0

0 0

10

20

30

40

50

60

0

50

100

DPI (mm/blow)

250

DPI (mm/blow)

E LWD = 32.87 - 0.12 (Rut Depth)

(c)

40

Site C

R 2 = 0.62 n = 10

30 20 10

40

60

Site B Site A

100

R 2 = 0.35 n = 27

R 2 = 0.65 n = 20 = 14 MDP* =Field 56.48Study + 6.896,E n LWD

60

0 20

MDP* = 136.69 + 0.45 E LWD

120

80

Maximum allowable Rut Depth = 50 mm

0

(d)

140 MDP*

E LWD-Z2 (MPa)

200

160

50

0

80 100 120 140 160

5

10

15

20

25

30

E LWD-Z2(50) (MPa)

Rut Depth (mm) 50

50 CMV = 27.57 - 0.10 (Rut Depth) R 2 = 0.64 n = 10

(e)

40 30

Site C

20 10 0 0

20

40

60

R 2 = 0.70 n = 10

30 20 10

Maximum allowable Rut Depth = 50 mm

(f)

CMV = 6.06 + 0.61 (E LWD )

40 CMV

CMV

150

Site C

0

80 100 120 140 160

0

Rut Depth (mm)

10

20

30

40

50

E LWD-Z2(50) (MPa)

Figure 3. Relationships between: (a) DPI and su, (b) DPI and ELWD, (c) rut depth and ELWD, (d) rut depth and CMV, (e) ELWD and MDP*, and (f) ELWD and CMV.

different depths at the DCP test locations. The relationship showed good correlation with R2 = 0.6. A similar relationship was published by McElvaney & Djatnika (1991) for limestabilized materials as shown in Figure 3a. Data obtained from this project fall slightly below the trend observed by McElvaney & Djatnika (1991). ELWD and DPI showed a non linear relationship with R2 = 0.7 (Fig. 3b). Similar non-linear relationships between elastic modulus and DPI are reported by others (e.g. Chai & Roslie 1998). Relationships between rut depth measurements with ELWD produced R2 = 0.6 (Fig. 3c). Some scatter was evident at rut depths < about 40 mm and the reason is attributed to the differences in the influence depths of the two measurements. A stiff compaction layer of at least 200 mm in thickness typically results in a high ELWD value (determined from a 200 mm diameter plate), while ruts beneath the test roller wheel are a result of subgrade conditions well below the compaction layer. An approach to analyze support capacities of the subgrade under the roller wheel using layered bearing capacity analysis is described later in this paper. Relationships between roller-integrated CMV/MDP and in-situ point measurements are developed by spatially paring the nearest point data using GPS measurements. Correlation between CMV—rut depth and ELWD produced R2 = 0.6 and 0.7, respectively (Fig. 3e, f). MDP* and ELWD correlation showed two different trends for the two sites (Fig. 3d). The MDP* values tend to reach an asymptotic value of about 150 which is the maximum value on the calibration hard surface. The correlations for roller-integrated CMV and MDP with conventional test measurements (e.g. rut depth, ELWD) showed correct trends but with varying degree of uncertainty (assessed by R2 values) in the relationships. This scatter is expected because of the various 50

factors that influence the relationships which include: (a) differences in measurement influence depths, (b) range over which measurements were obtained, (c) influence of moisture content, (d) intrinsic measurement errors associated with the roller MVs and point measurements, (d) position error from pairing point test measurements and roller MV data, and (f) soil variability. 4.2 Bearing capacity analysis on layered cohesive soil stratum DCP profiles were analyzed for bearing capacity under the test roller wheel using analytical layered bearing capacity solutions proposed by Meyerhof & Hanna (1978). For the analysis, the contact area under the tire is assumed as a rigid rectangular flat footing of size 0.45 m × 0.46 m (contact width dimension obtained from Mn/DOT 2000 and length calculated to equal 650 kPa contact pressure under 113.5 kN applied force per wheel), the contact pressure under the tire is assumed to be uniform (i.e. 650 kPa), and the load application is assumed to be vertical. The behavior of soil beneath a wheel is assumed analogous to soil behavior beneath a footing under undrained loading conditions. The footing is assumed to be rigid to simplify the analysis and is considered a reasonable assumption with the relatively high tire inflation pressure and tire carcass stiffness compared to the deformability of the soil (see Bekker, 1960). The analysis can be fine tuned by solving theoretical equations to determine contact area under the roller, considering a possible inclination in footing shape and load, and accounting for flexibility of the rubber tire (see Hambleton & Drescher, 2008). Hambleton & Drescher 2008 summarized theoretical solutions to determine contact area as a function of wheel sinkage which is a sum of both elastic (rebound after the load application) and plastic deformations (measured rut depth) under the wheel. Although plastic deformation is predominant at locations with greater rut depths, locations with minimal rut depths can have considerable elastic rebound, but is difficult to measure. The analysis is simplified herein with an objective of analyzing the effect of vertical non-uniformity on the subgrade bearing capacity under the wheel and obtaining insights on approximate target shear strength properties required to overcome rut failures under the test roller. Meyerhof & Hanna (1978) proposed analytical solutions to estimate bearing capacity of a two-layered soil stratum with stronger soil overlaid by a weaker soil of known soil mechanical properties. If the thickness of the stronger layer (H) is relatively small, a punching shear failure is expected in the top stronger soil layer, followed by a general shear failure in the bottom weaker soil layer. In that case the ultimate bearing capacity qult is a function of the su properties (for φ' = 0 condition) of both top and bottom layers and is calculated using Equation 4. If the thickness H is relatively large, then the failure envelope lies within the top layer only. For that case, qult is a function of top layer su using Equation 5. B⎞ ⎛ ⎛ B ⎞ ⎛ 2c H ⎞ qult = ⎜1 + 0.2 ⎟ 5.14 su 2 + ⎜1 + ⎟ ⎜ a ⎟ ≤ qt L⎠ ⎝ ⎝ L ⎠⎝ B ⎠

(4)

B⎞ ⎛ qt = ⎜1 + 0.2 ⎟ 5.14 su1 L⎠ ⎝

(5)

where B = contact width, L = contact length, su1= undrained shear strength of the top layer, su2 = undrained shear strength of the bottom layer, ca = adhesion determined using theoretical relationship between ca/su1 and su2 /su1 by Meyerhof & Hanna (1978). Rut depth measurements at 11 test locations in comparison with DCP-su profiles at each location are presented in Figure 4. The su values were determined using the DPI-su relationship presented in Figure 3a. As described earlier and similar to previous findings by White et al. (2007) and Larsen et al. (2008), significant vertical non-uniformity in soil shear strength properties is evident from the DCP-su profiles. The reason for this non-uniformity at this project is attributed to variable and thick lifts and variable moisture content. 51

Ruth Depth (mm)

0 50 100

Test Roller

989 kPa

1229 kPa q ult = 1160 kPa

1021 kPa

815 kPa

1093 kPa

980 kPa

2335 kPa

1598 kPa

1056 kPa

1175 kPa

Acceptable Rut Depth = 50 mm (Mn/DOT Specification 2111)

150 200 1

2

3

4

5

6 Point No.

7

8

9

10

11

Depth (mm)

0 H

200 400 600

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

200 400

200 400

200 400

200 400

200 400

200 400 su (kPa)

200 400

200 400

200 400

200 400

200 400

su estimated using DPI-su relationship

Figure 4.

10000

Comparison of DCP-su profiles with rut depth measurements.

Log(q ult) = 3.36 - 0.20Log (Rut Depth) n = 11 2 R = 0.90

200

PASS H = 0.0 m Pass/Fail depending on "H" H = 0. 1 m

su2 (kPa)

q ult (kPa)

150 1000

FAIL

100 H=

Target q

ult

= 1050 kPa

50

(a)

(b)

100 0.1

H

1

10

100

1000

100

200

Rut Depth (mm)

=0

.5

300

H= m

0 .4

400

su1 (kPa)

H=

m

500

0 .2 m

0 .3

m

600

TH60 Fail (Points 2, 3, and 8) TH60 Pass (Points 1, 4, 6, 7, 10, and 11) TH60 Pass (Points 5,9) q ult < target q ult (1050 kPa) TH 14 Fail (Points 1, 2, and 4) TH 14 Pass (Point 5) TH60 Pass (Point 3) q ult < target q ult (1050 kPa)

*Fail: Rut Depth ≥ 50 mm

ExampleCalculation: For s u2 = 75 kPa and H = 0.3m s u1 ≥ 270 kPa for q ult ≥ 1050 kPa and rut depth measurement ≤ 50 mm

Figure 5. (a) Relationship between calculated ultimate bearing capacity and measured rut depth, and (b) influence of undrained shear strength properties of top and bottom layers at different H to achieve a minimum qult = 1050 kPa.

The soil profile at each test location was analyzed as a two-layered soil system using weighted average su values for each layer to determine the qult value at each location. The relationship between calculated qult values and measured rut depth measurements from the test locations is shown in Figure 5 and show a strong non-linear correlation with R2 = 0.9. Based on the acceptable rut depth value = 50 mm, a target qult = 1050 kPa was calculated. This target value can be interpreted as the minimum value required at a location with a two-layered cohesive soil stratum to avoid rut depth failures, i.e. rut depths ≥50 mm. The graph presented in Figure 5b shows relationship between su1 and su2 at different H values to achieve the target qult value. The advantage of viewing the results in this manner is that if su values of the two layers (su1 and su2) are known (for example from DCP test), it can be determined rut depth failures at a given location are expected or not. An alternate way of interpretation is that if su2 is known, the minimum required su1 to avoid rut depth failures (as shown in the calculation in Fig. 5b) can be estimated. A target su value for a homogenous condition (i.e. H = 0, su1 = su2) can be readily determined from Figure 5b which is = 170 kPa. qult values calculated from DCP-su profiles shown in Figure 4 are plotted on Figure 5 to demonstrate the use of the graphical “pass”/“fail” evaluation procedure. A test location is determined as “fail” if the measured rut depth was ≥50 mm and checked if the calculated qult value was < target qult. Nine out of eleven test locations complied with the pass/fail criteria, and the two test locations that did not comply showed qult = 989 kPa with a rut depth = 23 mm and qult = 1093 kPa with a rut depth = 84 mm. Similarly, qult determined from DCP-su profiles from the TH14 project (results presented in Fig. 1) are also plotted in 52

1.2 1.0

200 300

Point A Point B

400 500 600

Applied stress (MPa)

Depth (mm)

0 100

(A) Predicted q

ult

= 0.98 MPa

(A) ELWD-Z2 =26.1 MPa

0.8

Capacity of PLT

0.6 0.4

(B) E LWD-Z2 =3.2 MPa

0.2

(B) Predicted q

ult =

0.12 MPa

0.0 0

100

200

0

300

10

20

30

40

50

Deflection (mm)

su (kPa)

Figure 6. Comparison of estimated qult from layered bearing capacity analysis and static plate load test.

Table 2. Summary of QA target values as an alternative to heavy testing rolling rut depth of 50 mm. Measurement value

Target values from empirical relationships

ELWD-Z2 (MPa) CMV (a = 0.85 mm, f = 30 Hz) MDP* (a = 1.87 mm, f = 33 Hz) DPI (mm/blow) su (kPa)

27 23 149 12 170

Figure 5 for comparison. The test points from that project did not have corresponding rut depth measurements but had visual confirmation of whether or not significant rutting was observed at the test locations. Three out of five test locations from that project complied with the pass/fail criteria. Considering the simplifications and assumptions made in the analysis and inevitable statistical uncertainty associated with empirical relationships used in the analysis, the pass/fail estimations are considered practically acceptable and useful for establishing an alternative method for QA target values. As with any geotechnical engineering application, a chart like this cannot replace thorough testing/analysis and engineering judgment but it can serve as a quick reference guide for field engineers. The validity of the layered bearing capacity analysis analytical solutions was verified by performing 300 mm plate diameter static plate load tests at several test locations. Data from two test locations are presented in Figure 6. One test location was relatively soft (Point B, ELWD = 3.2 MPa) and the other location was relatively stiff (Point A, ELWD = 26.1 MPa) as shown in Figure 6. The applied load was increased at point B until a bearing capacity failure was induced and at point A until the maximum capacity of the PLT system was reached. DCP-su profile data was used to determine qult under the plate (assuming B = L = 0.3 m). The calculated qult = 0.12 MPa at point B was close to the measured qult = 0.13 MPa. The calculated qult = 0.98 MPa at point A appears to fall in line with the trend observed in the loaddeformation curve up to an applied stress of about 0.65 MPa (tire contact pressure). 5

IMPLEMENTATION ASPECTS

An alternate approach to heavy test rolling is to develop regression relationships (as presented above) and target values for other measurements. A summary of QA target values developed based on the empirical relationships presented in Figure 3 are shown in Table 2. The target ELWD-Z2 and CMV measurement values were derived from relationships with rut depth measurements corresponding to a rut depth of 50 mm. The MDP* target value was derived 53

from the relationship developed with ELWD-Z2 from site A (Fig. 3d) for ELWD-Z2 = 27 MPa. The target su value was determined based on the layered bearing capacity analysis. The regression relationships, however, have some uncertainty which can be accounted for using statistical prediction limits at a selected percent confidence. For example, values in a relationship corresponding to the least-squared fit regression line will provide about 50% confidence in the predicted target value. These relationships should be considered specific to the material and project conditions and could vary considerably for other conditions. 6

CONCLUDING REMARKS

Use of roller-integrated compaction measurement technologies (CMV and MDP) and DCP/ LWD point measurements to evaluate the support capacities of subgrade layers in-situ are discussed in this paper. Comparisons were made to heavy test roller rut depth QA criteria specified by Mn/DOT for the upper subgrade layer of a pavement foundation. Correlations developed between roller-integrated CMV and MDP and point measurements show positive trends but with varying degrees of uncertainty in relationships. DCP-su profiles on compacted subgrades showed significant vertical non-uniformity with depth. Test rolling identified deep soft layers with excessive rutting (rut depths ≥50 mm) at the surface. Bearing capacities under the heavy roller wheel were evaluated using layered bearing capacity analytical solutions and DCP-su profiles. The ultimate bearing capacities determined were empirically related to the measured rut depths at the surface. A chart solution was developed for using the layered bearing capacity analysis to determine target shear strength properties of a layered soil to avoid rut failures under the test roller. Considering the significant advantage of roller-integrated compaction monitoring technologies with 100% coverage of compacted areas and positive trends in the relationships, it is concluded that the measurements can serve as a reliable indicator of compaction quality of cohesive subgrades and provide a good alternative to heavy test rolling. A summary of site and project specific QA target values established for the different measurements based on the empirical relationships are provided. ACKNOWLEDGEMENTS The Minnesota Department of Transportation (Mn/DOT) and the Federal Highway Administration (FHWA) sponsored this study under Mn/DOT Contract No. 89256, Work Order No. 2. Numerous Mn/DOT district staff and Mathiowetz Construction Co. personnel assisted the authors in identifying and providing access to grading projects for testing. The authors would like to thank several graduate and undergraduate research assistants who provided assistance with the ISU Geotechnical Mobile Lab in field and lab testing. REFERENCES Bekker, M.G. 1960. Off the Road Locomotion. University of Michigan Press, Ann Arbor, Michigan, USA. Chai, G. & Roslie, N. 1998. The structural response and behavior prediction of subgrade soils using falling weight deflectometer in pavement construction. Proceedings of 3rd International Conference on Road and Airfield Pavement Technology, Beijing, China. Geodynamik ALFA-030. Compactometer, Compaction Meter for Vibratory Rollers, ALFA-030– 051E/0203, Geodynamik AB, Stockholm, Sweden. Hambleton, J.P. & Drescher, A. 2008. Development of improved test rolling methods for roadway embankment construction. Final Report MN/RC 2008-08. Minnesota Department of Transportation, St. Paul, Minnesota, USA. Konrad, J. & Lachance, D. 2001. Use of in-situ penetration tests in pavement evaluation. Canadian Geotechnical Journal, 38: 924–935. Kudla, W., Floss, R. & Trautmann, C. 1991. Dynamic test with plate—Quick method of quality assurance of road layers without binder. Streets and Highways (Strasse and Autobahn), 2: 66–71, Bonn (in German).

54

Larsen, B.W., White, D.J. & Jahren, C.T. 2008. Pilot project to evaluate dynamic cone penetration QC/ QA specification for cohesive soil embankment construction. Transportation Research Record, Journal of the Transportation Research Board, 2081: 92–100. McElvaney, J. & Djatnika, I. 1991. Strength evaluation of lime-stabilized pavement foundations using the dynamic cone penetrometer. Australian Road Research, 21(1): 40–52. Meyerhof, G.G. & Hanna, A.M. 1978. Ultimate bearing capacity of foundations on layered soil under inclined load. Canadian Geotechnical Journal, 15(4): 565–572. Mn/DOT. 2000. Standard Specifications for Construction—Specification 2111 Test Rolling. Minnesota Department of Transportation (Mn/DOT), St. Paul, Minnesota, USA. Mn/DOT. 2006. Excavation and Embankment—Quality Compaction by IC, LWD, and Test Rolling (Pilot Specification for Embankment Grading Materials). S.P. 5305–55, Minnesota Department of Transportation (Mn/DOT), St. Paul, Minnesota, USA. Sandström, A.J. & Pettersson, C.B. 2004. Intelligent systems for QA/QC in soil compaction. Proceedings of the 83rd Annual Transportation Research Board Meeting, January 11–14. Washington, D.C., USA. Thompson, M. & White, D.J. 2008. Estimating compaction of cohesive soils from machine drive power. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 134(12): 1771–1777. Thurner, H. & Sandström, Å. 1980. A new device for instant compaction control. Proceedings of the International Conference on Compaction, Vol II: 611–614, Paris. White, D.J, Jaselskis, E.J, Schaefer, V.R. & Cackler, E.T. 2005. Real-time compaction monitoring in cohesive soils from machine response. Transportation Research Record, Journal of the Transportation Research Board, 1936: 173–180. White, D.J., Thompson, M. & Vennapusa, P. 2007. Field validation of intelligent compaction monitoring technology for unbound materials. Final Report MN/RC-2007-10, Minnesota Department of Transportation, Minnesota, USA. White, D.J. & Thompson, M. 2008. Relationships between in situ and roller-integrated compaction measurements for granular soils. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 134(2): 1763–1770. White, D.J. Thompson, M., Vennapusa, P. & Siekmeier, J. 2008. Implementing intelligent compaction specification on Minnesota TH64: Synopsis of measurement values, data management, and geostatistical analysis. Transportation Research Record, Journal of the Transportation Research Board, 2045: 1–9. Zorn, G. (2003). Operating manual: Light drop-weight tester ZFG2000, Zorn Stendal, Germany.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A comparative subgrade evaluation using CBR, vane shear, light weight deflectometer, and resilient modulus tests N. Garg & A. Larkin Federal Aviation Administration, William J. Hughes Technical Center, New Jersey, USA

H. Brar SRA International Corp., Egg Harbor Township, New Jersey, USA

ABSTRACT: California Bearing Ratio (CBR) is generally used in airport pavement thickness design procedures to characterize subgrade soils. Alternative thickness design procedure based on layered elastic analysis has also been available (LEDFAA) since 1995 which accepts either subgrade CBR or resilient modulus. The CBR value is converted to resilient modulus in psi by multiplying by 1,500. The relationship is based on a correlation between dynamic modulus and CBR measured for soils and aggregates. A strong trend is apparent in the correlation but there is a lot of scatter. Resilient modulus, in combination with a measure of strength such as shear, could displace CBR as a means of characterizing subgrade soils. Therefore, it is necessary to understand and document the relationships between CBR and other methods of characterizing soils. This study summarizes the preliminary results obtained from subgrade characterization testing (CBR, vane shear, light weight deflectometer, and repeated load triaxial tests) at the FAA NAPTF. 1

INTRODUCTION

An airport pavement is a complex engineering structure. Pavement analysis and design involves the interaction of four equally important components, which are often difficult to quantify: (1) the subgrade (naturally occurring soil), (2) the paving materials (surface layer, base, and sub-base), (3) the characteristics of applied loads, and (4) climate. According to Advisory Circular (AC) 150/5320-6D paragraph 302a., “Pavements designed in accordance with these standards are intended to provide a structural life of 20 years that is free of major maintenance if no major changes in forecast traffic are encountered. It is likely that rehabilitation of surface grades and renewal of skid-resistant properties will be needed before 20 years due to destructive climatic effects and deteriorating effects of normal usage.” The Federal Aviation Administration (FAA) pavement design procedure refers to the determination of the thickness of pavement and its components (surface, base, and subbase layers) not to the design of the materials in pavements [e.g., Hot Mix Asphalt (HMA) or Portland Cement Concrete (PCC) mixes]. The material and construction requirements are specified in AC 150/5370-10A “Standards for Specifying Construction of Airports.” The thickness design of flexible airport pavements for FAA-sponsored projects has, until recently, been done according to the CBR method. An alternative design procedure based on layered elastic analysis has also been available for flexible pavement thickness design for FAA-sponsored projects since 1995 (implemented in computer programs LEDFAA 1.2 and 1.3). CBR or resilient modulus is used for characterizing the subgrade, although, internally, the computer program operates exclusively on the numerical value of the modulus. In the future, it is possible that the capability for measuring resilient modulus of soils will become more common and resil-ient modulus, in combination with a measure of strength such as shear, could well displace CBR as a means of characterizing subgrade soils. This latter circumstance would also lead to a more rational methodology if adopted for use in Federal 57

Aviation Administration Rigid and Flexible Iterative Elastic Layer Design (FAARFIELD) for thickness design of flexible pavements. But before this can be seriously contemplated, it is necessary that the relationships between CBR and other methods of characterizing soils be firmly understood and documented so that backward compatibility can be maintained. This is a long-term study and a start was made during the subgrade construction for Construction Cycle 5 (CC5) pavement test items at the FAA National Airport Pavement Test Facility (NAPTF). The subgrade was characterized by CBR, vane shear, dirt seismic properties analyzer (DPSPA), light weight deflectometer (LWD), and repeated load triaxial tests. This study summarizes the preliminary results obtained from subgrade characterization testing at the FAA NAPTF. 2

USE OF CBR FOR SUBGRADE CHARACTERIZATION IN AIRPORT PAVEMENTS

CBR is used for characterizing subgrade materials for airport pavement design. Ahlvin (1991) documents the origins of using CBR for airport pavement design. Responsibility for design and construction of military airfields was assigned to the Corps of Engineers in 1940. At that time, the promising methods used bearing capacity of the subgrade as the basic design input. However, the means of determination of bearing capacity remained in question. The war emergency forced the Corps of Engineers to select CBR for characterizing subgrade for the following reasons – • The CBR method has been correlated with pavement service behavior and construction methods. • Could be quickly adapted to airfield pavement design for immediate use. • Method was thought to be reasonable and as sound as any of the methods investigated. • Had been successfully used in California and two other states. • CBR could be assessed using simple portable test equipment in the laboratory or in the field and under moisture-density conditions existing under the pavements. The FAA has developed new computer software for airport pavement thickness design FAARFIELD that will supersede LEDFAA 1.3 as the standard design procedure in the next revision of AC 150/5320-6 in the near future. In LEDFAA 1.3 and FAARFIELD, the

Figure 1. Relationship between dynamic modulus and CBR (Green and Hall, 1975) (1 psi = 6.89 kPa). 58

180,000 LEDFAA / AASHTO1993 AASHTO-2002 / TRL AL-DOT O-DOT USACE CSIR NAPTF-CC1 SHELL

160,000

Resilient Modulus, psi

140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 0

20

40

60

80

100

120

CBR

Figure 2. Relationship between dynamic modulus and CBR developed by different agencies (1 psi = 6.89 kPa). COMPREHENSIVE LITERATURE REVIEW

SAMPLING AND TESTING

FIELD SAMPLING AND TESTING LABORATORY TESTING

Figure 3. Table 1.

PROCURE LABORATORY TESTING EQUIPMENT

ESTABLISH CONTACTS AT AIRPORTS

Subgrade characterization—Project outline. List of tests for subgrade characterization.

Laboratory tests

Field tests

– Atterberg Limit (LL, PL, PI of soils) – Grain size analysis (hydrometer tests and sieve analysis) – Modified Proctor Tests (moisture-density relationship) – Unconfined compressive strength tests (shear strength of cohesive soils) – Triaxial shear tests (shear strength parameters for cohesionless soils) – Dynamic Triaxial Tests (resilient modulus and permanent deformation behavior)

– – – –

59

CBR (ASTM D4429) Vane shear (ASTM D2573) LWD DSPA

CBR value is converted to resilient modulus in psi by multiplying by 1,500. The relationship is based on a correlation between dynamic modulus and CBR measured for soils and aggregates over the range of 2 to 200 CBR. A literature review showed a strong trend (see Figures 1, 2) in the correlation between CBR and modulus, but there is a lot of scatter, indicating that the value of CBR for a given soil is strongly dependent on more than one of the underlying characteristics of the soil. The FAA is studying other ways to characterize subgrade and develop relationships between CBR and these methods. The purpose is to understand and document these relationships so that backward compatibility can be maintained. The project outline is shown in Figure 3. The tests that are being considered are listed in Table 1. Preliminary results from the study are presented in the following sections. 3

USE OF VANE SHEAR FOR SUBGRADE CHARACTERIZATION

Vane shear is widely used to measure the undrained shear strength of soft cohesive soils. The shear strength is computed from the torque required to induce shear failure in the soil. Vane shear is normally used for field tests, but the technique can also be adapted for laboratory-compacted samples. Vane shear tests were conducted extensively at NAPTF in conjunction with CBR tests during the CC2-OL (construction cycle 2 overlay—HMA overlay over rubblized concrete pavement) post traffic tests and CC5 (construction cycle 5—flexible pavements) subgrade construction. The objectives for using vane shear were to study the uniformity of subgrade and develop the relationship between shear strength and CBR. The relationship between vane shear and CBR (developed based on test results from DuPont Clay) is shown in Figure 4. In both series of tests (CC2-OL and CC5), DuPont clay was used as the subgrade. DuPont clay is a CH soil, with a liquid limit of 66 percent, and a plasticity index of 33 percent. As per ASTM D1557 (Method C), the optimum moisture content and corresponding maximum dry density for DuPont clay were 19% and 102.1 pcf, respectively. The relationship is fairly strong for the subgrade tested. Additional test data are needed to study if the relationship between CBR and shear strength is soil type specific (clays, silty clay, silts, etc). Shelby tube samples

16 CBR = 0.0018*(Shear Strength)1.6926 R2 = 0.92

14

Soil - DuPont Clay (CH Soil) Liquid Limit - 66% Plasticity Index - 33%

12

CBR

10 8 6 4 2 0 0

25

50

75

100

125

150

175

200

225

250

Shear Strength (from vane shear), kPa

Figure 4.

Relationship between shear strength and CBR developed using NAPTF data. 60

were also collected from the subgrade for triaxial tests (SHRP P46 resilient modulus tests and shear strength tests). When the results from the laboratory test program are obtained, an attempt will be made to study the relationship between vane shear and resilient modulus and triaxial shear strength. 4

SEISMIC MODULUS FOR SUBGRADE CHARACTERIZATION

DSPA is a portable device that measures modulus of unbound materials in the field. It consists of two transducers (receivers) and a source (Figure 5). The device operates from a computer. The operating principle of DSPA is based on generating and detecting stress waves in a layered medium. The data collected by DSPA is processed by spectral analysis to determine the mod-ulus of the layer. The modulus value obtained from DSPA is low-strain elastic modulus. A more detailed explanation on theory and equipment can be found elsewhere (Nazarian, et al. 1993, 1995, 2002, 2003). The test is nondestructive in nature, repeatable, rapid, and easy to perform. The major advantage of using seismic modulus for subgrade characterization is that it is a fundamentally correct parameter (linear elastic modulus). However, the state of stress during seismic tests differs from state of stress under actual pavement loads (Williams, et al. 2007). Williams, et al. (2007) also reported that seismic moduli are roughly twice the unconfined low-strain resilient

SOURCE

Figure 5. Table 2.

RECEIVERS

Dirt seismic property analyzer. Summary of seismic moduli for CC5 subgrade from DSPA tests.

Minimum Maximum Mean Standard Deviation COV, %

Seismic modulus psi

Resilient modulus psi

Predicted CBR (from E = 1500 * CBR)

Acceptance tests, CBR

–5481 17127 –9873 –2837 28.7

2740 8564 4937 1418 –

1.8 5.7 3.3 0.9 –

2.7 3.8 3.0 0.2 6.1

No. of DSPA tests = 34; No. of CBR tests = 13; COV—Coefficient of variation. 61

modulus, and this relationship is independent of the type of material used. In the absence of any laboratory testing data, this relationship can be used to convert seismic modulus to resilient modulus. Apart from seismic modulus, the DSPA results can also be used for studying subgrade uni-formity. During CC5 subgrade construction, DSPA tests were performed on the finished sub-grade surface. The test results are summarized in Table 2. The acceptance test CBR values (for acceptance of constructed subgrade) listed in the table are from CC5 subgrade construction. DSPA results showed higher variability compared to CBR tests. Preliminary analysis on the limited amount of data collected showed that E (psi) = 1500 * CBR is fairly reasonable for the DuPont clay tested. More test data on different soil types is needed to study the validity of CBR-modulus relationship. 5

LWD TESTS FOR SUBGRADE CHARACTERIZATION

Falling weight deflectometer (FWD) tests have been routinely used in pavement engineering. During FWD tests, pavement surface deflections are recorded under a given load. The deflection basin obtained is used for backcalculating the modulus of the pavement layers. LWD is a hand- held portable device (Figure 6) generally used on unbound materials (subgrade, subbase, and aggregate base layers). In the LWD equipment, the magnitude of impact force is measured by a load cell and the peak center deflection is measured through a hole in the loading plate by a seismic transducer (geophone). The drop height is adjusted by a movable release handle. The standard drop weight is 97.9 N or 22 lbf (146.8 N or 33-lbf and 195.7 N or 44-lbf drop weights are optional). There is an option to add two additional geophones. The in situ layer moduli can be obtained using the Boussinesq equation: 2 ⎡1 − υ 2 ⎤⎦ qa E= ⎣ δ

(1)

where E is the elastic modulus, υ is the Poisson’s ratio, q is the uniform pressure, a is plate radius, and δ is the deflection under the center of the plate.

Drop Weight

Loading Plate with Geophone at the Center Additional Geophones

Figure 6.

Dynatest light Weight Deflectometer setup with additional geophones. 62

In addition to estimating elastic modulus of the subgrade layer, the LWD measurements can be used to study uniformity within the subgrade, and effect of compaction on stiffness and modulus. Table 3 summarizes the results from LWD testing on completed CC5 subgrade. Figure 7 shows the elastic modulus of the subgrade as a function of vertical stress applied. The stress applied was varied by adjusting the drop height of the load. The results in Table 3 and Figure 7 show that higher variability in modulus is observed at low stress levels. One of the possible reasons for this could be the effect of the soil condition closer to the subgrade surface since at lower stress levels, a low volume of soil is mobilized. The vari-ability reduces at higher stress levels since a larger volume of soil is mobilized and local effects are reduced (more of a global compaction/moisture effect). Another observation from Figure 7 is the stress-softening behavior of cohesive subgrade soil. Modulus decreases with the increase in applied stress. Also included in Figure 7 are the resilient modulus test results (labeled LAB-DuPONT) from laboratory tests on thin-wall Shelby tube samples (at 14 kPa or 2 psi confining pressure). Laboratory tests were performed following the SHRP P46 test protocol. The laboratory test results correlate very well with the LWD test results.

Table 3. Summary of deflection measurements and elastic moduli for CC5 subgrade from LWD tests (1 mil = 0.0254 mm and 1 psi = 6.89 kPa). Peak center deflection, mils

Elastic modulus, psi

Vertical stress

6.6 psi

12.3 psi

22.9 psi

6.6 psi

12.3 psi

22.9 psi

Minimum Maximum Mean Standard Deviation COV, %

4.3 17.6 10.1 3.3 32.5

9.8 35.4 23.5 7.7 32.9

43.0 100.0 75.8 16.8 22.1

3553 14429 7075 2916 41.2

3286 11820 5698 2421 42.5

2156 5008 3008 778 25.8

COV—Coefficient of Variation. 20000 20-25N 60-CL 200-15N 270-25N LAB-DuPONT-3

18000

20-15N 60-25S 200-15S 270-15S

40-25N 115-CL 250-25N 270-25S

40-15N 135-15N 250-15S LAB-DuPONT-1

60-15N 200-25N 250-25S LAB-DuPONT-2

Elastic Modulus, psi

16000 14000 12000 10000 8000 6000 4000 2000 0 0

5

10

15

20

25

30

Stress, psi

Figure 7. Elastic modulus of subgrade from LWD tests on the top of completed subgrade [the numbers in the legend represent the testing location; e.g. 20–25 N means Station 20 ft (6.1 m) and 25 ft (7.6 m) offset north of pavement centerline] (1 psi = 6.89 kPa). 63

The stress states used in SHRP P46 test protocol are representative of stress states occurring in the subgrade under highway loads. Higher vertical subgrade stresses are common under aircraft wheel loads (also demonstrated by limited subgrade stress measurements made at NAPTF). This suggests that higher stress states (specially deviator stresses) should be used when testing subgrade samples for airport pavements. Results from Table 2 (moduli from DSPA) and Table 3 (moduli from LWD) show that DSPA and LWD showed similar variability in moduli values (coefficient of variation values of 25 to 28 percent). 6

SUMMARY

CBR is generally used in airport pavement thickness design procedures to characterize subgrade soils. The FAA has undertaken a long-term study to look at alternate methods for subgrade characterization. It is necessary that the relationships between CBR and other methods of characterizing soils be firmly understood and documented so that backward compatibility can be maintained. This paper presented test results from NAPTF subgrade construction wherein different test methods such as vane shear, DSPA, LWD, and laboratory resilient modulus tests were used to characterize a CH soil (DuPont clay) with a liquid limit of 66 percent and a plasticity index of 33 percent. The study demonstrated the application potential of different techniques. The results presented in this paper only pertain to low CBR values and one soil type. More testing on different soil types (clays, silts, and sands) is required before reaching any significant conclusions. ACKNOWLEDGMENTS/DISCLAIMER The work described in this paper was supported by the FAA Airport Technology Research and Development Branch, Dr. Satish K. Agrawal, Manager. Thanks to Dr. Gordon F. Hayhoe, NAPTF Manager, and Mr. Jeffrey Gagnon, Manager Pavement Sub-Team, for their support during the test planning and organization. The authors would also like to acknowledge the help of Ken Marshall of SRA International Corp. during the tests. The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the data presented within. The contents do not necessarily reflect the official views and policies of the FAA. The paper does not constitute a standard, specification, or regulation. REFERENCES Ahlvin, R.G. 1991. Origin of Developments for Structural Design of Pavements. Technical Report GL-91-26. Vicksburg, Mississippi, USA: Department of the Army, Waterways Experiment Station, Corps of Engineers. FAA, Office of Airport Safety and Standards, “Standards for Airport Pavement Design and Evaluation,” AC 150/5320-6D, US Department of Transportation, 1995. FAA, Office of Airport Safety and Standards, “Standards for Specifying Construction of Airports,” AC 150/5370-10A, US Department of Transportation, 1989. Green, J.L., and Hall, J.W., Jr. 1975. “Nondestructive Vibratory Testing of Airport Pavements.” Report No. FAA-RD-73-205, Volume I. NTIS, Washington, D.C., USA. Nazarian, S., Baker, M.R., and Crain, K. 1993. “Fabrication and Testing of a Seismic Pavement Analyzer.” SHRP Report H-375. SHRP, National Research Council, Washington, D.C. Nazarian, S., Yuan, D., and Baker, M.R. 1995. “Rapid Determination of Pavement Moduli with Spectral-Analysis-of-Surface-Waves Method.” Report Research Project 0-1243, Center for Geotechnical and Highway Materials Research, University of Texas at El Paso, El Paso, TX. Nazarian, S., Yuan, D., and Arellano, M. 2002. “Quality Management of Base and Subgrade Materials with Seismic Methods.” Transportation Research Record No. 1786, Washington, D.C. Nazarian, S., Williams, R., and Yuan, D. 2003. “A Simple Method for Determining Modulus of Base and Subgrade Materials.” ASTM STP 1437, ASTM, West Conshohocken, PA. Williams, R.R., and Nazarian, S. 2007. “Correlation of Resilient and Seismic Modulus Test Results.” Journal of Materials in Civil Engineering, ASCE. December 2007.

64

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Stabilization of clays using liquid enzymes Y. Yilmaz Department of Civil Engineering, Kirikkale University, Kirikkale, Turkey

A.G. Gungor & C. Avsar Technical Research Department, General Directorate of Highways, Ankara, Turkey

ABSTRACT: The potential of three different liquid enzymes to stabilize CL and CH type of soils is evaluated. The evaluation involved the determination of the geotechnical properties of clay soils in their natural state as well as when mixed with three different liquid enzymes, separately. The parameters tested included the particle size distribution, Atterberg limits, compaction characteristics (optimum moisture content and maximum dry unit weight) under standard Proctor compaction energy effort, swell percentage and California bearing ratio (CBR). All tests of the treated samples were repeated after 1-day, 7-day and 28-day curing periods. Results showed that the geotechnical parameters of clay soils are improved very little by the addition of liquid enzymes; plasticity and optimum moisture content were reduced around 5% to 10%, maximum dry unit weight is reduced as negligible as 1%. But, swell percentages and CBR values are increased by 5% to 350% and 5% to 70% depending on the curing period and type of soil treated, respectively. These results imply that although liquid enzymes provide some beneficial effects in CBR values, it is unlikely to be a substitute for CH type of soil as swell percentage increased dramatically. 1

INTRODUCTION

For many years, there has been intensive research on the usability of additives such as lime, cement, fly ash, and sometimes cement kiln dust to improve the quality and/or stability of pavement subgrade soils and base materials. Laboratory and field performance tests have approved that the addition of 2% to 10% of such treatment may increase the strength and stability of soils (Puppala et al. 1996, Prusinski & Bhattacharja 1999, Miller & Zaman 2000, Shafee Yusuf et al. 2001, Parsons & Milburn 2003, Sivapullaiah et al. 2003, Arora & Aydilek 2005, Barstis & Metcalf 2005, Rao & Shivananda 2005, Si & Herrera 2007, Sreekrishnavilasam et al. 2007). On the other hand, the cost of introducing these conventional additives has also increased in recent years. That is why several companies have developed and introduced other types of costeffective liquid soil stabilizers (e.g. enzyme, ionic, polymer types) as alternatives. But, few studies (Rauch et al. 2002, Santoni et al., 2002, Santoni et al., 2005, Tingle & Santoni 2003) in the literature have evaluated the effect of these nontraditional liquid stabilizers on the engineering properties of soils. The objective of the current paper is to present the results of standard laboratory soil tests conducted to measure changes in the engineering properties such as Atterberg limits, maximum dry unit weight, optimum moisture content, CBR and swell characteristics of three clay soils when treated with three different commercially available liquid enzymes. The details of the experimental program and the findings are presented below. 2

GEOTECHNICAL PROPERTIES OF SOILS USED IN THE STUDY

The physical properties of soils, including particle size distribution, consistency limits and specific gravity are determined in accordance with ASTM D 422-63, ASTM D 4318-00 and ASTM D 854-02 standards, respectively. The particle size distribution curves of the soils are 65

100 90 80

Percent finer by weight

70 60 50 40 30 20

Soil A Soil B

10

Soil C 0 0.001

0.010

0.100

1.000

10.000

100.000

Grain size, D (m m )

Figure 1.

The particle size distribution curves of the soils.

Table 1.

Some geotechnical properties of the soils.

Property

Soil A

Soil B

Soil C

Specific gravity, Gs Liquid Limit, LL Plastic Limit, PL USCS class symbol

2.68 35 16 CL

2.67 59 26 CH

2.67 31 19 CL

shown in Figure 1. The test results and Unified Soil Classification System (USCS) class symbols of the soils according to ASTM D 2487-00 are tabulated in Table 1. 3

PREPARATION OF SOIL SAMPLES AND LIQUID ENZYME SOLUTIONS FOR TESTING

Soil samples taken from open-cut excavations are initially kept at room temperatures of 20°C to 35°C. After air drying, they are broken into small pieces and then certain amounts of which passing through U.S. Standard No.4 (4.75 mm) sieve are collected in a pan. Prior to compaction, air dried soils are mechanically mixed thoroughly to satisfy homogeneity of the samples throughout the experimental program. Three different commercially available liquid enzymes are used in the experiments. Liquid enzyme solutions are prepared by diluting 3 ml of each liquid enzyme in 1000 ml distilled water, separately. Since, the aim of this study is not to distinguish between the liquid soil stabilizers but to investigate the effect of such additives on the different type of soils. Each soil is tested with only one liquid enzyme. Soil A, Soil B and Soil C are tested with liquid enzyme Type 1, Type 2 and Type 3, respectively. Throughout the text, the liquid enzymes are called as Type 1, Type 2 and Type 3 instead of their commercial names to keep away from commercialism. 4

STANDARD PROCTOR TESTS

Soil samples are initially mixed with around 10% of distilled water or liquid enzyme diluted water and then stored in a closed plastic bag for a few days to minimize flocculation. Thereafter samples are remixed with suitable amount of distilled water or liquid enzyme diluted 66

Table 2. Effect of liquid enzyme solutions on the optimum water contents and maximum dry unit weights of the soils (ASTM D698). 1 day curing

1 week curing

4 weeks curing

Name of soil

Liquid enzyme

wopt (%)

γdrymax. (kN/m3)

wopt (%)

γdrymax. (kN/m3)

wopt (%)

γdrymax. (kN/m3)

Soil A Soil B Soil C

Type 1 Type 2 Type 3

10.7 24.4 12.1

19.81 15.19 19.42

10.2 24.5 11.4

19.72 15.12 19.50

10.3 23.8 11.5

19.70 15.18 19.38

Table 3.

Effect of liquid enzyme solutions on the dry CBR and wet CBR values of the soils. 1 day curing

1 week curing

4 weeks curing

Name of soil

Liquid enzyme

Dry CBR (%)

Wet CBR (%)

Dry CBR (%)

Wet CBR (%)

Dry CBR (%)

Wet CBR (%)

Soil A Soil B Soil C

Type 1 Type 2 Type 3

24.1 22.9 22.0

9.5 4.1 13.4

32.3 32.0 28.2

11.0 5.5 12.5

41.1 26.0 34.7

12.9 6.1 13.6

water and then compaction tests are carried out according to Method B of ASTM D 698-00a standard by imparting an energy level of 600 kN-m/m3. When distilled water used optimum water contents and maximum dry unit weights of the soils are obtained as 10.4%, 24.8%, 12.4% and 19.76 kN/m3, 15.24 kN/m3, 19.41 kN/m3 for Soil A, Soil B and Soil C, respectively. On the other hand, when liquid enzyme solutions are used instead of distilled water, the optimum water contents and maximum dry unit weights of the soils are tabulated in Table 2 for different curing periods. When the optimum moisture content and maximum dry unit weight of the treated and untreated soils are compared. It is clear from Table 2 that optimum water content of the soils decreases very slightly with increasing curing period. On the other hand, maximum dry unit weight of the soils remains almost the same. 5

CALIFORNIA BEARING RATIO (CBR) TESTS

The soil samples are compacted in CBR molds at the maximum dry unit weights and optimum water obtained from standard Proctor compaction tests. Then California Bearing Ratio (CBR) tests are carried out according to ASTM D 1883-99 standard. When distilled water used dry CBR and wet CBR values of the soils are obtained as 23.6%, 23.9%, 21.7% and 9.7%, 4.6%, 10.3% for Soil A, Soil B and Soil C, respectively. On the other hand, when liquid enzyme solutions are used instead of distilled water, the dry CBR value and wet CBR value of the soils are tabulated in Table 3 for different curing periods. When the dry CBR values and wet CBR values of the treated and untreated soils are compared it is seen that dry CBR values of the treated samples increase remarkably with increasing curing period (Table 3). For example, dry CBR value of Soil A at the end of 28-days curing period increases as high as around 70%. On the other hand, wet CBR values of the treated samples does not exhibit considerable increase or decrease with increasing curing period. 6

SWELL PERCENTAGE FROM OEDOMETER TEST

Samples compacted at optimum moisture content are subjected to swell percentage tests using oedometer test apparatus having rigs of 75.2 mm in diameter and 20.0 mm in height. 1.0 kPa surcharge pressure is adopted for swell percentage measurements. 67

Table 4.

Effect of liquid enzyme solutions on the swell percentage of the soils. Swell percentage

Name of soil

Liquid enzyme

1 day curing

1 week curing

4 weeks curing

Soil A Soil B Soil C

Type 1 Type 2 Type 3

1.5 3.3 2.3

1.7 9.2 3.8

3.2 11.6 4

When distilled water used swell percentages of the soils are obtained as 0.66%, 3.2%, and 1.8% for Soil A, Soil B and Soil C, respectively. On the other hand, when liquid enzyme solutions are used instead of distilled water, the swell percentages of the soils are given in Table 4 for different curing periods. From Table 4 it may be stated that as the curing period increases swell percentage tends to increase gently for Soil A and Soil C (CL class soils). On the other hand, swell percentage of Soil B (CH class soils) increases dramatically. At the end of 28-days curing period, swell percentage of the Soil B increases as high as 350%. 7

CONCLUSION

In this study, the effect of some nontraditional soil stabilizers on the swell percentage and CBR values of low plasticity and high plasticity clay soils at the end of different curing periods are investigated. The main conclusion drawn from this study is that liquid enzymes provide some beneficial effects in CBR values. But, due to their negative influence on the swell percentage they are unlikely to be a substitute for CH type of soils. Moreover, before using these liquid stabilizers in the field, it is recommended to carry out independent laboratory tests with higher application rates on the project-specific soils. REFERENCES ASTM D 422-63. 2002. Standard Test Method for Particle-Size Analysis of Soils. Annual Book of ASTM Standards, American Society for Testing and Materials, West Conshohocken, PA 1–8. ASTM D 698-00a. 2002. Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Standard Effort (12,400 ft-lbf/ft3(600 kN-m/m3)). Annual Book of ASTM Standards, American Society for Testing and Materials. West Conshohocken, PA 1–7. ASTM D 854-02. 2002. Standard Test Method for Specific Gravity of Soil Solids by Water Pycnometer. Annual Book of ASTM Standards, American Society for Testing and Materials. West Conshohocken, PA 1–7. ASTM D 1883-99. 2002. Standard Test Method for CBR (California Bearing Ratio) of LaboratoryCompacted Soils. Annual Book of ASTM Standards, American Society for Testing and Materials. West Conshohocken, PA 1–8. ASTM D 2487-00. 2002. Standard Practice for Classification of Soils for Engineering Purposes (Unified Soil Classification System). Annual Book of ASTM Standards, American Society for Testing and Materials. West Conshohocken, PA 1–12. ASTM D 4318-00. 2002. Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils. Annual Book of ASTM Standards, American Society for Testing and Materials. West Conshohocken, PA 1–14. Arora, S. & Aydilek, A.H. 2005. Class F fly-ash-amended soils as highway base materials. Journal of Materials in Civil Engineering 17(6): 640–649. Barstis, W.F. & Metcalf, J. 2005. Practical approach to criteria for the use of lime-fly ash stabilization in base courses. Transportation Research Record n 1936: 20–27. Miller, G.A. & Zaman, M. 2000. Field and laboratory evaluation of cement kiln dust as a soil stabilizer. Transportation Research Record n 1714: 25–32. Parsons, R.L. & Milburn, J.P. 2003. Engineering Behavior of Stabilized Soils. Transportation Research Record n 1837: 20–29.

68

Prusinski, J.R. & Bhattacharja, S. 1999. Effectiveness of portland cement and lime in stabilizing clay soils. Transportation Research Record n 1652: 215–227. Puppala, A.J., Mohammad, L.N. & Allen, A. 1996. Engineering behavior of lime-treated Louisiana subgrade soil. Transportation Research Record n 1546: 24–31. Rao, S.M. & Shivananda, P. 2005. Compressibility behaviour of lime-stabilized clay. Geotechnical and Geological Engineering 23(3): 309–319. Rauch, A.F., Harmon, J.S., Katz, L.E. & Liljestrand, H.M. 2002. Measured effects of liquid soil stabilizers on engineering properties of clay. Transportation Research Record n 1787: 33–41. Santoni, R.L., Tingle, J.S. & Webster, S.L. 2002. Stabilization of silty sand with nontraditional additives. Transportation Research Record n 1787: 61–72. Santoni, R.L., Tingle, J.S. & Nieves, M. 2005. Accelerated strength improvement of silty sand with nontraditional additives. Transportation Research Record, n 1936, p 34–42. Shafee Yusuf, F.A.M., Little, D.N. & Sarkar, S.L. 2001. Evaluation of structural contribution of lime stabilization of subgrade soils in Mississippi. Transportation Research Record n 1757: 22–3. Si, Z. & Herrera, C.H. 2007. Laboratory and field evaluation of base stabilization using cement kiln dust. Transportation Research Record n 1989: 42–49. Sivapullaiah, P.V., Lakshmi Kantha, H. & Madhu Kiran, K. 2003. Geotechnical properties of stabilised Indian red earth. Geotechnical and Geological Engineering 21(4): 399–413. Sreekrishnavilasam, A., Rahardja, S., Kmetz, R. & Santagata, M. 2007. Soil treatment using fresh and landfilled cement kiln dust. Construction and Building Materials 21(2): 318–327. Tingle, J.S. & Santoni, R.L. 2003. Stabilization of Clay Soils with Nontraditional Additives. Transportation Research Record n 1819: 72–84.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The effect of moisture hysteresis on resilient modulus of subgrade soils C. Khoury School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, USA

N. Khoury Department of Civil and Environmental Engineering, Temple University, Philadelphia, Pennsylvania, USA

ABSTRACT: This study evaluates the effect of moisture hysteresis on resilient modulus (MR) of a subgrade soil. Cylindrical specimens were prepared at near optimum moisture content and maximum dry unit weight. The moisture content in each compacted specimen was altered to achieve a target moisture content following a drying-wetting-drying path (i.e. hysteresis). Specimens were then tested for MR to study the effect of moisture hysteresis. The laboratory results revealed that the MR values following the drying curve differ significantly from the corresponding MR values on the wetting curve. The relationship between MR and moisture content exhibits a hysteretic behavior similarly to the SWCC; specimens subjected to drying exhibited higher MR values than specimens subjected to wetting. The findings from this study provided useful information on MR hysteretic behavior with differing moisture content, which would be helpful in predicting the changes in bearing capacity of pavements due to seasonal variations. 1

INTRODUCTION

The changes in subgrade moisture conditions play an important role in the in-service performance of a pavement. These conditions are sensitive to a rise in the water table, precipitation, freeze-thaw cycles, and wet-dry cycles, among others (AASHTO, 2008). The AASHTO design guides (i.e., 1986, 1993 and 2002) have recognized the impact of moisture changes on the bearing capacity of a pavement structure. The 1986 and 1993 design guides accounted for the impact caused by moisture variation by introducing the effective roadbed resilient modulus (MR) of subgrade soils. The new mechanistic-empirical pavement design guide (ME-PDG), AASHTO 2002 design guide, used a different approach by incoporating these variables through models based on previously published ones (Rada & Witczak, 1981; Li and Selig, 1994; Drumm et al., 1997; Santha, 1994) that predict the changes in MR due to changes in moisture and/or temperature. These studies (Rada & Witczak, 1981; Li and Selig, 1994; Drumm et al., 1997; Santha, 1994) and others (Yuang & Nazarian, 2003; Khoury & Zaman, 2004; Yuang et al., 2005; among others) looked at resilient modulus in compaction moisture content, degree of saturation, and post-compaction due to wetting or drying. However, the literature review revealed no studies that addressed the influence of moisture hysteresis on MR values of subgrade soils. Knowledge of these effects is needed to design better pavements, since a compacted subgrade layer could be subject to changes in moisture content due to seasonal variations. This study is designed to assess the hysteretic effect of drying-wetting-drying path on MR values of a subgrade soil. 2

LITERATURE REVIEW

Several studies have addressed the influence of moisture changes on MR values of subgrade soils in the laboratory and field. Table 1 shows a summary of relevant studies related to the 71

Table 1.

A summary of relevant studies.

Reference

Procedure

Parameter

Results

Comments

Drumm et al. (1997)

Evaluated the effect of post-compaction moisture content on MR values of sub-grade soils in Tennessee.

Resilient All soils, ranging from A-4 to modulus A-7-6 in accordance with AASHTO classification, exhibited a decrease in MR values with an increase in the degree of saturation. The degree of reduction in MR values varied with soil types. Consequently, they presented a method for correcting MR values due to an increase in degree of saturation.

The study did not address the effect of drying or combination of drying and wetting on M R.

Yuan and Investigated the effect Seismic Modulus values decreased due Nazarian of compaction and modulus to wetting and increased due (2003) post-compaction to drying. moisture content (w) on the modulus of base and sub-grade soils. They adopted a new laboratory procedure to evaluate the effect of wetting and drying on the modulus. Seismic modulus tests were performed on specimens subject to wetting or drying.

Study lacks knowledge on MR values; design input parameter in the ME-PDG. Hysteric effect of moisture was not observed

Khoury and Zaman (2004)

Resilient MR decreased with an increase Moisture hysterNew laboratory procein moisture content and modulus esis was not dures developed to increased with a decrease in examined evaluate the effect of moisture content as expected. wetting and drying on The change in MR values due both resilient modulus to wetting and drying varied and soil suction. They from one soil to another. prepared specimens at different moisture contents and then either raised or lowered the moisture content prior to testing for MR.

Yuang et al. (2005)

Resilient Evaluated the variamodulus tions of MR with the post-compaction moisture content for subgrade soils. A new laboratory procedure for wetting was employed. Specimens were compacted at optimum moisture content and then saturated to equilibrium moisture content prior to testing for MR.

Study, however, did not address the effect of drying or combination of drying and wetting on MR values fo subgarde soils.

(Continued ) 72

Table 1.

(Continued )

Reference

Procedure

Parameter

Liang et al. Proposed a math(2008) ematical model for predicting the effect of moisture variations on MR, using the effective stress concept and assuming the pore air pressure equal to zero.

Results

Comments K2

⎛ θ + χw ⋅ψ m ⎞ ⎛ τ oct ⎞ M R = K1 × Pa × ⎜ + 1⎟ ⎟ ⎜ P P a ⎝ ⎠ ⎝ a ⎠

K3

Model requires the evaluation of soil suction.

effect of seasonal variation on resilient modulus of subgrade soils. There are no studies in the literature, to the authors’ knowledge, that addressed the influence of moisture hysteresis on the MR of sub-grade soils. This study is thus designed to understand these effects. 3

LABORATORY APPROACH

3.1 Soil classification and moisture-density tests The soil used for this study belongs to the Renfrow series. The soil taxonomy of the Renfrow series is fine, mixed, superactive, thermic Udertic Paleustolls (OSD, 2008). The taxonomy classification for Renfrow series indicates the following: 1. Fine is a particle size classification that means, soils with clay content less than 60 percent in the fine earth fraction. 2. Superactive is soil with a ratio of cation-exchange capacity (by NH4OAc at pH 7) to clay (% by weight) of 0.60 or more. 3. Thermic is a mean annual soil temperature classification range of 15 to 22oC. 4. Udertic Paleustolls have cracks, which are 5 mm or more wide, through a thickness of 30 cm or more and also have slickensides or wedge-shaped aggregates in a 15-cm thick layer whose upper bound is located within 125 cm from the soil surface (OSD, 2008); more information is described by USDA (2006). Grain size distribution tests, both sieve analysis and hydrometer, were conducted in accordance with the ASTM C 136-84 and ASTM D 422-63 test methods, respectively. The liquid limit and plastic limit tests were performed in accordance with the ASTM D 4318-95 test method. Laboratory test results showed that Renfrow is classified as a CL in accordance with the Unified Soil Classification System (USCS) with a liquid limit of approximately 35 and a plasticity index of 15. The moisture-unit weight relationship was determined in accordance with the ASTM D 698-91 test method. The maximum dry unit weight was found to be 16.6 kN/m3 (105.5 pcf) and the optimum moisture content 16.5%. 3.2 Specimen preparation and drying & wetting procedures Resilient modulus specimens were prepared at near optimum moisture content and maximum dry unit weight in accordance with the laboratory procedure described by Khoury & Zaman (2004). The procedure enhances water flow through the compacted specimens during wetting, thereby making the distribution of moisture more uniform. Specimens were subject to drying, wetting and then drying to examine the effect of hysteresis moisture variation on resilient modulus. Khoury & Zaman’s (2004) drying procedure was used in this study: (a) placing a rubber membrane around the specimen after compaction; (b) placing a circular plastic sheet on each end of the specimen; (c) placing two platens on the top of the 73

Ending Point of MDC Starting Point of MWC

Resilient Modulus

Ending Point of MDC Drying Starting Point of IDC Wetting Drying Ending Point of MWC Starting Point of MDC Moisture Content Figure 1.

Typical MR-moisture hysteresis relationship.

plastic sheet; (d) sealing off the membrane from the platens with a masking tape; (e) placing the specimen in an oven at 41°C (105°F); (f) weighing the specimen at a designated time interval. The resilient modulus tests were performed after the desired moisture content was achieved. This procedure provides specimens with a fairly uniform distribution of moisture with height and radius, within approximately 0.5% point of the average value. The wetting procedure used by Khoury & Zaman (2004) was also employed: 1) injecting a specified amount of water into the specimens, 2) then testing the specimens for resilient modulus. 3.3 Resilient modulus testing The MR tests were performed in accordance with the AASHTO T 307-99 test method, the most recent test protocol. The resilient modulus test consisted of applying a cyclic haversine-shaped load with a duration of 0.1 seconds and rest period of 0.9 seconds. For each sequence, the applied load and the vertical displacement for the last five cycles were measured and used to determine the resilient modulus. The load was measured by using an internally mounted load cell with a capacity of 2.225kN (500 lbf). The resilient displacements were measured using two linear variable differential transformers (LVDTs) fixed to opposite sides of and equidistant from the piston rod outside the test chamber. The LVDTs had a maximum stroke length of 19.0 mm (0.75 in). 3.4 Establishing the MR-moisture hysteresis relationship (drying-wetting-drying path) In this study the MR-Moisture hysteresis curve (MR MC) consisted of three paths as shown in Figure 1. 3.4.1 Initial drying curve (IDC) A starting point on the IDC was established by conducting MR test on specimens prepared at OMC. The second point was determined by conducting MR test on specimens prepared at OMC and dried to a lower moisture content level. The process was repeated at lower moisture content levels of OMC until the IDC was complete; it is important to note that 74

specimens were dried up to OMC–4%, no data is available for moisture content levels lower than OMC–4%. 3.4.2 Main wetting curve (MWC) The starting point on the MWC was the turnaround point where the drying of specimens (IDC) stops and wetting commences. The second point was established by preparing specimens at OMC, drying them to OMC–4%, wetting them back to a higher moisture content level and then performing the resilient modulus. The process was repeated by increasing moisture content level until reaching a value of approximately OMC+4%. 3.4.3 Main drying curve (MDC) The starting point on the MDC was the turnaround point where the main wetting curve ended (OMC+4%) and drying recommenced. The second point was established by preparing specimens at OMC, drying them to OMC–4%, wetting them to OMC–4%, drying them again to a lower moisture content and then performing the resilient modulus. The process was repeated at lower moisture content levels until the curve was complete. It is important to note that the authors are currently studying specimens that are subjected to additional wetting and drying cycles and different paths of wetting and drying, which will lead Table 2.

Model parameters and MR values.

Specimen No.

w (%)

k1

k2

k3

R2

MR ( M P a ) *

MR ( M Pa ) * *

OMC-21-1 OMC-21-2 OMC-21-3 OMC-21-4 OMC-21-5 OMC-21-6 OMC-21-7 OMC-21-8 OMC-21-9 OMC-21-10

15.4 13.8 13.0 15.4 16.3 19.9 18.3 17.1 14.7 12.7

1161 1361 1441 825 786 427 605 800 1329 1905

0.125 0.189 0.194 0.390 0.502 0.677 0.549 0.406 0.168 0.105

–0.767 –0.637 –0.448 –2.374 –2.878 –3.457 –2.925 –2.559 –1.114 –0.177

0.92 0.99 0.98 0.98 0.98 0.96 0.96 0.97 0.99 0.95

113.2 138.4 150.3 74.1 69.6 38.0 54.3 70.7 126.5 197.6

100.5 118.9 130.0 51.2 43.6 20.7 33.0 47.9 107.3 183.4

OMC-23-1 OMC-23-2 OMC-23-3 OMC-23-4 OMC-23-5 OMC-23-6 OMC-23-7 OMC-23-8 OMC-23-9

12.9 14.3 17.0 18.9 20.4 19.5 18.5 15.7 14.1

1736 1017 616 519 403 427 592 964 14.11

0.195 0.365 0.612 0.632 0.563 0.577 0.575 0.247 0.146

–0.615 –1.986 –3.080 –3.140 –2.642 –2.886 –3.020 –1.776 –0.683

0.99 0.98 0.97 0.96 0.93 0.94 0.96 0.98 0.97

177.5 94.7 55.8 47.0 37.7 39.0 53.2 87.6 140.1

152.1 67.8 32.3 26.8 23.0 23.3 31.6 68.2 123.3

OMC-24-1 OMC-24-2 OMC-24-3 OMC-24-4 OMC-24-5 OMC-24-6 OMC-24-7 OMC-24-8 OMC-24-9 OMC-24-10

14.6 12.7 13.9 17.3 19.0 20.8 19.9 19.0 16.4 14.7

1321 1664 1033 603 518 422 392 556 946 1297

0.193 0.187 0.309 0.600 0.664 0.611 0.598 0.576 0.244 0.182

–0.859 –0.571 –1.716 –3.119 –3.260 –2.972 –2.965 –2.944 –1.800 –1.129

0.97 0.99 0.98 0.97 0.97 0.94 0.94 0.96 0.98 0.99

131.0 170.5 97.0 54.1 46.9 38.7 35.8 50.4 85.6 124.0

111.0 147.2 73.0 31.5 26.1 22.6 21.0 30.1 66.8 104.2

OMC-29-1

17.1

749

0.241

–1.861

0.87

67.2

52.4

* θ = 154.64 kPa & τ =13.0 kPa (Drumm et al., 1997). ** θ = 83 kPa & τ = 19.3 kPa (Gupta et al., 2007).

75

200.0 IDC 180.0

MWC MDC

160.0

IDC M R ,

140.0

M P a

100.0

120.0

80.0

MDC

60.0

MWC 40.0 20.0 12

13

14

15

16

17

18

19

20

21

22

w(%)

Figure 2. MR-moisture hysteresis (MR calculated at θ = 154.64 kPa and τ = 12.99 kPa).

200.0 IDC

180.0

MWC 160.0 M R ,

MDC

140.0 120.0

IDC 100.0

M P a

80.0 60.0

MDC

40.0

MWC

20.0 0.0 12

13

14

15

16

17

18

19

20

21

22

w(%)

Figure 3.

MR-moisture hysteresis (MR calculated at θ = 83 kPa and τ = 19.3 kPa).

to develop MR MC scanning curves similar to the scanning curves of a soil water characteristic curve (SWCC). 4

PRESENTATION AND DISCUSSION OF RESULTS

The effect of hysteresis moisture variations was evaluated on the MR values determined at two different stress levels: (1) a bulk stress of approximately 154.6 kPa (22.5 psi) and a octahedral stress of 13.0 kPa (1.9 psi) as suggested by SHRP Protocol P-46 (Drumm et al., 1997), and (2) at a bulk stress of approximately 83.0 kPa (12.0 psi) and octahedral 76

stress of 19.3 kPa (2.8 psi), as suggested by NCHRP 1-28 A (Gupta et al., 2007). The new mechanistic-empirical pavement design guide (ME-PDG) MR-Stress Model shown below was used for this purpose: ⎞ θ k2 ⎛ τ M R = k1 pa × ×⎜ + 1⎟ pa p ⎝ a ⎠

k3

(1)

In this model, the resilient modulus (MR) is expressed as a function of bulk stress (θ ) and octahedral stress (τ3). Model parameters and MR values at the aforementioned stresses are summarized in Table 2. 4.1 MR-moisture hysteresis relationship The MR-moisture (MR MC) hysteresis relationship for MR calculated at θ = 154.6 kPa (22.5 psi) and τ = 13.0 kPa (1.9 psi) is graphically illustrated in Figure 2. Results showed that for a given moisture content the MR values along IDC and MDC were higher than the corresponding values on MWC. For example, the average MR value on IDC at OMC–2% (i.e., 14.5%) was 130 MPa (18,800 psi) compared to approximately 90 MPa (13,000 psi) on MWC. It is an indication that the MR-moisture relationship of compacted subgrade, due to wetting and drying, is hysteretic. This behavior is similar to the hysteresis of the soil water characteristic curve reported in various studies (e.g. Fredlund & Rahardjo 1993; Tinjum et al. 1997; Pham et al. 2003; Khoury and Zaman (2004); and Miller et al. 2008; among others). Moreover, it is noteworthy that beyond 20% moisture content on MWC, there was no significant decrease in MR values. The effect of moisture hysteresis on the resilient modulus at a bulk stress of approximately 83.0 kPa (12.0 psi) and octahedral stress of 19.3 kPa (2.8 psi) is shown in Figure 3. The same qualitative trends and hysteresis behavior was observed. Specimens subjected to drying cycles exhibited higher MR values than specimens subjected to wetting. In addition, results showed that MR values on IDC increased by approximately 60 MPa as the moisture content (w) decreased from OMC to OMC–2% and by approximetly 110 MPa as w decreased up to OMC–4%. On the other hand, specimens wetted from OMC–4% to OMC and to OMC+4% exhibited a reduction in MR values of approximately of 120 MPa and 140 MPa, respectively. This indicates that the extent of drying and wetting is an important factor in assessing the behavior of MR with moisture variations. Moreover, Figures 2 and 3 show that, in general, the MR values on MDC are bounded by the corresponding values on the IDC curve. 5

CONCLUSIONS

In view of the aforementioned results, the following conclusions can be drawn: 1. The resilient modulus increased as the moisture content decreased and decreased as the moisture content increased. 2. The relationship (MRMC) between moisture content and MR values of a compacted subgrade soil exhibits a hysteretic behavior due to drying and wetting. The MR values on the wetting curve are lower than the corresponding values on the drying curves. 3. The extent of drying and wetting play a critical role in evaluating the behavior of MR with moisture variations. This investigation was limited to evaluating the effect of moisture hysteresis on the resilient modulus of one type of subgrade soils. The authors are involved in a study to perform additional tests to establish the MR-moisture hysteresis relationships for various soils, which will enrich the database of resilient modulus behavior with moisture changes. 77

REFERENCES American Association of State Highway and Transportation Officials (AASHTO) (2008). http://www. mrr.dot.state.mn.us/pavement/PvmtDesign/designguide.asp, accessed April, 2008. Drumm, E.C., Reeves, J.S., Madgett, M.R. and Trolinger, W.D. (1997) Subgrade Resilient Modulus Correction for Saturation Effects, Journal of Geotechnical and Geo-environmental Engineering, 123(7). Fredlund, D.G. and h. Rahardjo (1993), Soil Mechanics for Unsaturated Soil, John Wiley & Sons, Inc. ISBN 0-471-85008-X, 517 pages. Gupta, S, Ranaivoson, A., Edil, T., Benson, C. and Sawangsuriya, A. (2007). Pavement Design Using Unsaturated Soil Technology, Minnesota Department of Transportation, St. Paul, Minnesota, 1–104. Khoury, N.N. and Zaman, M. (2004) Correlation Among Resilient Modulus, Moisture Variation, and Soil Suction for Subgrade Soils, Transportation Research Record, Journal of the Transportation Research Board, Geology and Properties of Earth Materials, No. 1874, pp. 99–107. Li D. and Selig, E.T. (1994) Resilient Modulus for Fine-Grained Subgrade Soils, Journal of Geotechnical and Geoenvironmental Engineering, 120(6). Liang, R., Rabab’ab, S. and Khasawneh, M. (2008) Predicting Moisture-Dependent Resilient Modulus of Cohesive Soils Using Soil Suction Concept, Journal of Transportation Engineering, 134(1), 34–40. Miller, G.A., Khoury, C.N., Muraleetharan, K.K., Liu, C. and Kibbey, T.C.G. (2008), Effects of Solid Deformations on Hysteretic Soil Water Characteristic Curves: Experiments and Simulations, Water Resources Research, 4. Official Soil Description (OSD, 2008), http://www2.ftw.nrcs.usda.gov/osd/dat/R/RENFROW.html, accessed September, 2008. Pham, H., Fredlund, D. and Barbour, L. (2005) A study of hysteresis models for soil-water characteristic curves, Can. Geotech. J. 42, 1548–1568. Rada, G. and Witczak, M.W. (1981) Compressive evaluation of laboratory resilient moduli results for granular material, Transportation Research Record 810, TRB, National Research Council, Washington, D.C., 23–33. Santha, B.L. (1994) Resilient Modulus of Subgrade Soils: Comparison of Two Constitutive Equations, Transportation Research Record 1462, TRB, National Research Council, Washington D.C., pp. 79–90. Tinjum, J.M., Benson, C.H., Blotz, L.R. (1997) Soil–water characteristic curves for compacted clays Journal of Geotechnical and Geoenvironmental Engineering, ASCE 123: 1060–1069. USDA (2006), Key to Soil Taxanomy, 10th edition, 2006. Yuang, D. and Nazarian, S. (2003) Variation in Moduli of Base and Subgrade with Moisture, Transportation Research Board, CD-ROM publication, Washington D.C. Yuang, S.H., Huang, W.H. and Tai, Y.T. (2005) Variation of Resilient Modulus with Suction for Compacted Subgrade Soils, Transportation Research Board, CD-ROM publication, Washington D.C.

78

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Dynamic properties of a full weathering granite subgrade and other pavement materials studied by model tests J. Zou Hunan Communications Polytechnic University, Changsha, P.R. China

Z. Li Hunan Communications Research Institute, Changsha, P.R. China

X. Cao School of Civil Engineering, Southwest Jiaotong University, Chengdu, P.R. China

ABSTRACT: Subgrade and pavement mainly bear the vehicle loads. The vehicle loads are dynamic loads and cyclic in nature. Subgrade produces residual plastic deformations under cyclic dynamic loads. The residual plastic deformations accumulate according to the strength of subgrade filling materials and the level of applied dynamic stress. Through the full size model tests, the variation laws of dynamic strain and stress and total deformation of the subgrade, which was a fill material with the full weathering granite, the cement stabilized soil and the reinforced soil with geogrid are discussed in this paper. Then, strength and modulus design norms of these three filling materials are described. According to the results of the model tests, the reliability and application scope of full weathering granite, cement stabilized soil and reinforced soil with geogrid in highway subgrade were assessed. The treatment effects were evaluated and the quality control standards of the subgrade were proposed. 1

INTRODUCTION

Many research studies on dynamic characteristics of subgrade soils and pavement materials can be found worldwide. Cao & Cai (1996, 2001) investigated the critical dynamic stress and permanent deformation of subgrade soils under repeated loads. Meanwhile, full size model tests on dynamic characteristics of railway subgrade soils and the surface layer of subgrade with graded detritus and soil reinforced with geogrid and geonet were made. Tang & Jiang (1994) analyzed the dynamic response of dilatable laterite railway subgrade soils and the dynamic response of the model subgrade bed was analyzed with the model test results. Lijun & Li (1995) converted train loading into an index form containing swing and frequency by adopting wave-passing elements and complete energy transfer boundary. Through a Fourier series, they conducted finite-element analyses on the dynamic response of high speed railway subgrade when the subgrade carried different wheel groups at different times and positions. Subgrade was influenced by a critical speed for vertical dynamic displacement response. The smaller the subgrade stiffness was, the lower was the critical speed. This influence was obvious. The vertical acceleration at the bottom of sleeper grew larger with the increase of speed. It also increased linearly with the increase of vehicle vibration frequency. In Japan, Sunaga (1990) tested the dynamic stress and settlement of the soft clay subgrade bearing the train loads. In Germany, Leykauf & Mattner (1991) tested subgrades with different stiffnesses under wheel loads. A highway in China having full weathering granite zone, more than 90 km in length, is discussed in this paper. The full weathering granite is the remaining granite debris after being weathered physically and chemically. Because of its special engineering characteristics, it might be affected greatly by vehicle loads when used as a fill material in subgrade. Therefore, model tests were utilized to investigate the dynamic properties of the subgrade and the pavement. 79

The stability of full weathered granite subgrade and the effects of cement stabilized and geogrid reinforced full weathering granite at the top of subgrade are evaluated systematically. 2

MODEL TEST DESIGN

In the subgrade and pavement structure model test, the model size is critical. As to the semi-rigid asphalt pavement, both the theoretical calculations and the measured deflections decrease with the increase of the distance from the centre of load. Deflections at the load center are 5 times higher than those 180 cm away from load center. Vehicle load is a dynamic load, which acts on the road and passes to the subgrade and foundation through the pavement, base course, and subbase course. Dynamic stresses are produced in the structural layers during this process. The vertical and radial stresses decrease with the increase of depth. If a uniform load, whose radius and magnitude denoted by a and q, acts on a semi-infinite homogeneous object, the vertical stress is about 0.055q at the depth of 5a. Because the moduli of pavement and base course are much greater than that of the subgrade, the stress attenuation in the structure of subgrade and pavement is faster than that in infinite homogeneous object. So this test model size was designed as 2.3 m in length, 3.6 m in horizontal width at bottom, 2.0 m at top, and 1:1 in slope gradient. Double-round loading boards were used to simulate the double-wheel ground load. The diameter of each board was 21.3 cm, which is equal to the diameter of an equivalent circle for single-wheel bearing surface. The distance between two board centers is 1.5d. and a single wheel load is assumed to be 100 kN. A tire pressure of 0.7 MPa was assumed to exist as the standard static pressure intensity between the loading board and road. The dynamic impact coefficient was introduced, varying from 1.3 to 1.5. The frequency of loading at any point on the subgrade and pavement is subjected to the time when the wheel load acts on it. Through changing that frequency, the effect on the subgrade and pavement dynamic structure characteristics was analyzed. That effect was brought out by the change of vehicle speed. The largest test loading frequency was 8 Hz. The pressure on the soil and the deformation of the soil layer were studied. The strains in the base course and the pavement surface were measured. 3

TEST PROGRAM

3.1 Test grouping The road pavement was built with factory mixed AC-16I asphalt concrete, 18 cm in thickness. The base course contained three layers of cement stabilized detritus. Each layer was 20 cm in thickness. The test was divided into three groups according to the type of subgrade used. The first group was filled with full weathering granite in the subgrade; the second group was Table 1.

The physical properties of the granite fill material.

Soil type

CBR (%)

Specific gravity

CL

8.9

2.70

Table 2.

Liquid limit (%)

Plastic limit (%)

Index of plasticity

Optimum water content (%)

Max. dry density (kN/m3)

34.1

24.6

9.5

10.2

19.44

The physical and mechanical properties of geogrid.

Material

Size (mm)

Thickness (mm)

Unit mass (g/m2)

Extension strength (MPa)

Weld joint pull strength (N/cm)

HDPE

200*200

2

660

21

100

80

covered with a 10-cm high geogrid reinforced layer on the top of subgrade; and in the third group, cement stabilized full weathering granite was mixed into the top of subgrade. Properties of full weathering granite are reported in Table 1. Granite samples were compacted according to the construction required compaction degree. The physical and mechanical properties of the geogrid used are reported in Table 2. 3.2 Test equipment A passage servo tester was chosen. This tester mainly consists of the hydraulic source, load servo actuator and control system. The maximum output load is 1000 kN. Control system can generate different wave signals. The servo actuator can apply 100 kN load. The pressure and deformation of the soil were measured in the layer. The strains of the base course and the pavement of road were also measured. Displacement was measured by the method of using sedimentation pole. The sedimentation was measured by eddy-current displacement gauge. 3.3 Test steps Each group was divided into 5 steps; the first step was static load test, denoted by ST, and the testing load increased from 0 to 50 kN in 10 steps; The second step was variable dynamic load test, denoted by DT and the wave shape of load was half-sine, which was programmed by the FCS test system’s signal generator. Each class load was repeatedly applied for 103 times. The dynamic response of the subgrade and pavement was studied. The third step was repeated loading test, which is referred to as CT. The fixed range of dynamic load was from 5 kN to 75 kN and the frequency was 8 Hz. The load was repeatedly applied 106 times to simulate the vehicle load. Then, the changes of subgrade and pavement structural characteristic parameters were measured with the changing loading time. The fourth step was static test, which is referred to as ST-2. The testing load increased from 0 to 150 kN in 10 steps. The fifth test step was a variable load test, DT-2 for short. The frequency was fixed at 5 Hz. The low value was 5 kN, while the peak load increased from 15 kN to 150 kN in 10 steps. Each load level was repeated 103 times. Over-loading was simulated in this stage. 4

TEST DATA AND ANALYSIS

4.1 Stress The dynamic stress is the stress under repeated load, while the static stress is the stress under static load. Figure 1 shows the relationship between dynamic stress and testing load in the first group test (DT-1). The static or dynamic stress has linear relationship with the load.

σ d ( s ) = kd ( s ) pd ( s ) Depth

1.20

0 0.18 0.48 0.78 1.68

1.00

Stress/MPa

(1)

0.80 0.60 0.40 0.20 0.00 -0.20 0

20

40

Load/kN Figure 1.

The relationship of stress and loading.

81

60

80

Table 3.

Ratio of kd/ks.

Depth/m

0.0

The first group (ST-2/DT-2) 0.17

0.18

0.48

0.78

0.08

0.38

0.68

0.28

0.08

0.2

0.06

0.06

0.07

Depth

1.2

Stress/MPa

1

10 30 45 60 75

0.8 0.6 0.4 0.2 0 0

0.5

1

1.5

2

Depth/m Figure 2.

The change of stress with depth (m).

where σd(s) denotes the stress of the subgrade and pavement under the dynamic or static load (MPa), subscript d represents the dynamic stress, and s represents static stress; kd(s) denotes the fitting parameter; pd(s) denotes the peak load (kN). Ratios of static stress fitting parameters (ks) and dynamic fitting parameters (kd) in the first test group are reported in Table 3. All of the ratios are larger than 1.0. The minimum one is 1.06 while the maximum one is 1.28. And the maximum value in the subgrade is 1.2. It shows that the static stress is smaller than the dynamic stress when dynamic load equals to the peak value of dynamic load. Consequently, conversion factor of dynamic load can be assumed as σd = 1.3σs in highway design. The relationship curve between the dynamic stress and the depth is shown in Figure 2, which is fitted with the exponent function:

σ d ,h = α ′σ d ,0e − β h

(2)

where σd,h denotes the dynamic stress at a depth of h (MPa); σd,0 represents the dynamic stress of pavement (MPa); α 1, β 1 are test parameters; h denotes depth (m). The stress decreases with the increase of depth. The stress at the top of the subgrade decreases with the increase of the horizontal distance from loading point. The dynamic stress at the top of the subgrade grows to 44 kPa under the dynamic loads ranged from 5 to 75 kN, which was greater than the full weathering granite dynamic strength. Therefore, the use of full weathering granite as a fill material in subgrade was unfavorable. 4.2 Deformation 4.2.1 Static deformation The deformations of subgrade, base course and pavement are reported in Table 4. Generally, the deformation has nearly linear relationship with load, when the whole structure of subgrade and pavement keeps in a flexible state. Through analyzing the test results of ST-1, the ratios of the deformations at different depths in the second and third test groups to that at the same depth in the first group are calculated to be from 23.98% to 89.29%. Through analyzing the test results of ST-2, those ratios range from 39.15% to 70.58%. All ratios are smaller than 82

Table 4.

The static deformations (in mm).

Depth/m Group 1(ST-1) Group 1(ST-2) Group 2(ST-1) Group 2(ST-2) Group 3(ST-1) Group 3(ST-2)

50 150 50 150 50 150

0.0

0.18

0.48

0.78

1.08

1.38

0.247 0.480 0.206 0.331 0.150 0.240

0.197 0.360 0.166 0.251 0.109 0.206

0.156 0.304 0.124 0.202 0.082 0.146

0.118 0.245 0.094 0.155 0.062 0.097

0.085 0.185 0.068 0.112 0.036 0.073

0.057 0.147 0.044 0.081 0.014 0.061

1.0, and moreover, the ratios of the third group are even smaller than those of the second group. It is indicated that the use of both geogrids and cement stabilized full weathering granites can enhance the stiffness of subgrade and reduce the deformation. 4.2.2 Accumulated permanent deformation The study of accumulated permanent deformation included two parts: the first one is to investigate the change of residual deformation in each structural layer, when the repeated loads accumulate from 1 to 106 cycles; the other is to research the change of residual deformation by recording the deformation before and after loading in the variable load test (DT-2), when the repeated load application is fixed at 103. Figure 3 gives the relationships of the accumulated permanent deformation and the applied load in the dynamic load test. Figure 4 shows the accumulated permanent deformations at every structure layer, when the loading times is fixed. That change, subjected to the change of load, can be explained in the power function: S p,i = S p 0,i Pdχ

(3)

where Sp,i denotes the accumulated permanent deformation after loading at fixed 103 times (mm); i is the structure code; i is assumed as 1 for the pavement and 2 for the base course and so on; Pd is dynamic peak load (kN); ψ is test parameter; Sp0,i is the test parameter denoting the accumulated permanent deformation under a dynamic load, which is loaded 103 times at 1 kN. Table 5 gives the fitting parameters of the DT-1 group test. χ is larger than 1, showing that the status of the subgrade and pavement was changed after being loaded 106 times. Table 6 lists the accumulated permanent deformations in different constructed layers. The accumulated permanent deformations of all groups, except group 1 in DT-2 are obviously smaller than those in DT-1. Moreover, in the DT-1, when the load grows from 0 to 75 kN, compared to the first group, the accumulated permanent deformations in all five layers of the second group are 62.92%, 90.23%, 63.52%, 63.26%, 84.53% of the first group deformations; and the third group are 62.83%, 71.48%, 74.65%, 25.31%, 42.88%. Similarly, in the DT-2, when the load changes from 0 to 75 kN, the second group are 35.86%, 70.61%, 63.60%, 33.81%, 43.50%; and the third group are 18.54%, 36.46%, 38.11%, 18.06%, 34.00%. Table 6 shows the method of stabilizing the subgrade and pavement with cement or reinforcing it with geogrids succeeded in reducing the accumulated permanent deformation. The fixed load was 5–75 kN in size and 8 Hz in frequency during the repeated load tests. Figure 5 shows the change in accumulated deformations in every layer, which is subjected to repeated load applications. It can be described as a function as follows: S pd = S p 0 N δ

(4)

where Spd denotes the accumulated residual deformation; N is the times of loading; Sd0 and δ are test constants; Sd0 is the initial deformation; δ reflects the increasing speed of deformation, which is subjected to the times of loading. 83

0.5

Depth

0.45

Deformation/mm

0.4

0 0.18 0.48 0.78 1.08 1.38

0.35 0.3 0.25 0.2 0.15 0.1 0.05 0 0

20

40

60

80

60

80

Load/kN

Figure 3.

Permanent deformation accumulation with loading.

0.16

surface foundation course bottom course

Deformation/mm

0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 0

20

40 Load/kN

Figure 4.

Accumulated permanent deformation of structure and loading.

Table 5.

Fitting parameter Sp0,i (×10–4) and ψ. Name

Surface

Base course

Bottom course

30 cm under surface

30–60 cm under surface

Group number

i

1

2

3

4

5

Group 1(DT-1)

Sp0,i ψ

1.427 1.587

6.019 1.170

3.675 1.225

1.548 1.427

1.234 1.299

After 108 repeated loading times, the accumulated deformations in the five structural layers in group 2, from the top down, are 87.15%, 94.68%, 74.10%, 60.26%, 82.78% of those in group 1; and group 3 are 83.00%, 91.36%, 53.20%, 23.35%, 36.91%. It is obvious that the accumulated deformations were reduced significantly after the stiffness of subgrade had been enhanced by improving it with subgrade cement or geogrids. 84

Table 6.

Accumulated permanent deformations of the structural layers (in mm). Name

Surface

Base course

Bottom course

30 cm under surface

30–60 cm under surface

Group number

i

1

2

3

4

5

Group 1 (DT-1) Group 1 (DT-2)

75 75 135 75 75 135 75 75 135

0.1289 0.1795 0.3964 0.0811 0.0644 0.1277 0.0810 0.0333 0.0832

0.0997 0.0854 0.1504 0.0899 0.0603 0.0999 0.0712 0.0311 0.0732

0.0704 0.0682 0.1096 0.0447 0.0434 0.0661 0.0525 0.0260 0.0414

0.0695 0.0751 0.1227 0.0440 0.0254 0.0426 0.0176 0.0136 0.0288

0.0380 0.0422 0.0702 0.0321 0.0184 0.0413 0.0163 0.0144 0.0269

Group 2 (DT-1) Group 2 (DT-2)

Deformation/mm

Group 3 (DT-1) Group 3 (DT-2)

2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Depth 0 0.18 0.48 0.78 1.08 1.38

0.E+00

Figure 5.

3.E+05

5.E+05 8.E+05 Loading times/kN

1.E+06

1.E+06

Accumulated permanent deformations and loading times (group 1). Table 7.

Maximum tensile stresses and strains.

Group

1

2

3

ST-1 ST-2

26.86 69.90

22.34 49.17

10.26 26.54

Maximum tensile stresses DT-1 (kPa) DT-2

39.94 66.31

29.21 54.94

16.15 29.30

DT-1 DT-2

35.66 57.47

24.75 47.61

16.15 27.30

Static-load strains (με)

Radial strain (με)

4.3 The tensile strain at the bottom of the subbase Because of existing stiffness difference between subbase and subgrade, the tensile stress and strain appear at the bottom of the subbase when the subgrade is bearing vehicle loads. Once the tensile stress exceeds the tensile strength, cracks will appear at the bottom of the subbase. The cracks will continue expanding upwards until the entire road surface structure is damaged. Table 7 lists maximum tensile stresses and strains. Compare the tensile strain of every group under dynamic and static load; firstly, the tensile amplitude produced by dynamic load has almost the same value as that produced by dynamic 85

Strain/με 120 100 80

Group 1 Group 2 Group 3

60 40 20 0 1000

Figure 6.

10000

100000 Loading times

1000000

Accumulating strains of subgrade and loading times (Dynamic state CT).

load when the peak dynamic load equals to the static load in a same group. Secondly, the greater the stiffness difference between subgrade and base course is, the larger is the tensile strain at bottom course. When a static 50 kN load is loaded, the static tensile strains in group 2 are 82.85%, 57.34% of that in group 1. When the load changes into a static 150 kN one, those percentages change into 70.35% and 37.97%. When the dynamic load is 75 kN, the maximum tensile strains in group 2 are 73.13%, 40.44% of those in group 1, and the radial strains in group 2 are 69.41%, 45.29% of those in group 1. When the dynamic load increases to 150 kN, the maximum tensile strains in group 2 are 82.85%, 44.19% of those in group 1, and the radial strains in group 2 are 82.85%, 47.50% of those in group 1. Under the traffic loads, the fatigue failure of a cement treated base course will occur due to the repeated flexural-tensile deformation. Figure 6 shows tensile strains graphed with the loading times. If the limit strain of cement stabilized graded gravel is assumed as 250 με, the fatigue lives of the base course in three testing groups are 2.89 × 106, 5.31 × 106, 7.59 × 106. Obviously, the fatigue life of the base course is prolonged by enhancing the strength of subgrade. Moreover, the fatigue life of cement stabilized soil is the longest. 5

CONCLUSIONS

Through implementing full size model tests, the dynamic properties of the subgrade and pavement were studied under vehicle loads. The following conclusions can be drawn: 1. Under the static load, the stress and deformation in each pavement structural layer and the tensile stress at the bottom of the subbase have linear relationships with load levels. The smaller the resilient modulus is, the larger the stress and the deformation. Similarly, in the dynamic load test, the maximum dynamic stress and radial strain in every structural layer and the tensile stress at the bottom of the subbase have also linear relations with the loads. The smaller the resilient modulus is, the larger the dynamic stress. When the static load and the dynamic load have the same peak values, the stresses and deformations in the layers and the tensile strains at the bottom of subbase under dynamic loading are greater than those under static loading. 2. With the increase of the subgrade modulus, the dynamic properties and load-bearing status of the subgrade and pavement are improved. The life of the road is prolonged. 3. When the subgrade bears the same load, the accumulated permanent deformations of the layers in the subgrade and pavement exhibit power relationships with the peak levels of the dynamic load. 86

4. The results show that it is unfavorable to use the full weathering granite as fill material in the subgrade. The resilient modulus of the subgrade was increased by 50% after placing geogrid on the top of the subgrade. Meanwhile, the dynamic properties and stability of full weathering granite subgrade were improved, and the bearing capacity of subgrade was enhanced greatly as well. The accumulated residual deformation under vehicle loads was also reduced by 40%. As for the base course, the number of repeated load application was increased by 84% when the tensile limit strain was reached. 5. The full weathering granite was used in subgrade as a fill material after being stabilized with cement. In that case, the resilient modulus of subgrade was increased by 100%, the dynamic stress became smaller, the accumulated deformations were reduced significantly, the tensile strain at the bottom of base course decreased and the life of the subbase was prolonged by 163%. In conclusion, the cement stabilized full weathering granite was desirable as a fill material in subgrade.

REFERENCES Cao Xin-wen, CAI Ying. The model test of railway subgrade dynamic properties. Journal of Southwest Jiaotong University, 1996, 31 (1). Cao Xin-wen, Su Qian, CAI Ying .The model test of the geogrid and geonetmorker improved subgrade dynamic properties. Journal of Southwest Jiaotong University. 2001, 36 (4). Tang Kang Min, JIANG Zhong-xin. The dynamic response analysis on expansive laterite railway subgrade. Journal of Southwest Jiaotong University. 1994, 29 (1). Lijun Shi, Li Kezhao. The finite element analysis on high-speed railway subgrade dynamic response. Railway. 1995, 17 (1). Sunaga, Makoto. Vibration behavior of subgrade on soft grounds under train load. Quarterly Report of RTRI, 1990, (31): 29–35. Li, D., and Selig, ET Resilient Modulus for Fine-grained Subgrade Soils. J. Geo. Eng., ASCE, 1994 120 (6). Leykauf, Gunther & Mattner, Lothar. Elastisches Verformungsver-Halten des Eisenbahnoberbaus. Eisenbahnigenieur, 1991, 41 (3): 111–119. Li Zhiyong, The research of dynamic properties and stabilization to the full weathering granite subgrade, Research report of Hunan research Institute of traffic science and technology [R]. 2003. Zhang Jun, Li Zhiyong. The model test research of dynamic properties to the full weathering granite subgrade. Road. 2004. (5).

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The use of geofiber and synthetic fluid for stabilizing marginal soils K. Hazirbaba The University of Alaska Fairbanks, Alaska, USA

B. Connor Alaska University Transportation Center, Alaska, USA

ABSTRACT: Construction of airfields and roadways in Western and Northwestern Alaska is expensive, not only because of the remote location, but also because gravel sources are scarce. Consequently, the readily available silts and sands are used to the greatest extent possible. Any required gravel is barged in at costs in excess of $300/m3. Engineers continually look for methods which allow the increased use of local materials. A newly developed soil stabilization technique was investigated through a systematic experimental study. In this technique, two non-traditional stabilizer agents, geofibers and synthetic fluid, are used to improve the bearing capacity of the soil. The effectiveness of the technique was tested on a silty sand through CBR tests. Additionally, the performance and strength of the soil before and after improvement were evaluated through triaxial compression tests. Based on this initial laboratory study, it was found that the addition of geofibers and synthetic fluid can significantly increase the strength and bearing capacity of silty sands. 1

INTRODUCTION

Many soils encountered in Alaska, especially Western Alaska, are typically marginal in that they lack the required engineering properties for use for pavement base courses, subbase courses, subgrades, and as a foundation supporting layer under buildings and various structures. Alternatives include importing quality soils, which is often extremely costly, and stabilizing locally available soils. Traditional stabilization techniques require large amounts of additives to improve the engineering properties of soils (Tutumluer et al. 2004). Moreover, many of these techniques require specialized skills and equipments to ensure adequate performance. Recently, geofibers and synthetic fluid have been used to improve very loose sandy soils (Hazirbaba et al. 2007). This technology is new, non-traditional, and requires minimal installation equipments. While the use of geofibers has been researched to some extent (e.g. Gray & Maher 1989, Fletcher & Humphries 1991, Tutumluer et al. 2004, Li 2005), the literature on stabilization of soils through non-traditional fluid stabilizers is limited. Scholen (1992) described the non-traditional stabilizers in five categories: 1) electrolytes, 2) enzymes, 3) mineral pitches, 4) clay fillers and 5) acrylic polymers. Santoni et al. (2002) performed tests on silty-sand material with traditional (cement, lime, asphalt emulsion) and nontraditional stabilizers (polymers, tree resin); they found that the nontraditional stabilizers gained strength quicker than the traditional stabilizers. Newman & Tingle (2004) used emulsion polymers for soil stabilization of airfields. Researchers found that all of the polymers used increased the unconfined compressive strength over that of unmodified soil after 28 days of cure time for both the wet and dry testing. The synthetic fluid used in this study can simply be described as wax feedstock consisting of carbon chains. Through synthesis, these carbon chains rearrange into isoparaffinic branched groups, which cannot organize into crystals. Similar fluids have been used as dust controlling agent, however the literature review showed that no documentation exists on the strength gain and bearing capacity improvement through synthetic fluids. Additionally, this 89

study is the first research effort that investigates the use geofibers and synthetic fluid for soil stabilization purposes. 2

EXPERIMENTAL PROGRAM

2.1 Materials tested The soil investigated in this study was brownish silty sand (USCS class: SM) obtained from Bethel, Alaska. The index properties of this material are summarized in Table 1 and its gradation is presented in Figure 1. The geofiber selected was black, 70 mm long polypropylene tape with aspect ratio of 260. Table 2 presents the material properties for the geofibers. The synthetic fluid used in this study was colorless (clear, bright) with a specific gravity of 0.863 and viscosity index of 70. The pertinent index properties for the synthetic fluid used are presented in Table 3. 2.2 Testing program and test procedures The aim of this study was to evaluate the use of geofibers and synthetic fluid with silty sand (SM type) in terms of bearing capacity improvement and strength gain through a systematic experimental study. To meet the objective of this study, the following set of questions will be investigated: • What is the optimum fiber content? • What is the optimum synthetic fluid content? Table 1.

Index properties of Bethel silty sand.

Index property Specific gravity, Gs Coefficient of uniformity, Cu Coefficient of curvature, Cc Fines content, % Optimum moisture content, % Maximum dry density, kg/m3 Plasticty index of fines USCS classification * Non-plastic.

Figure 1.

Gradation of the Bethel silty sand.

90

2.59 1.973 0.926 10 11 1780 NP* SM

Table 2.

Properties of geofibers used.

Table 3.

Property Type Shape Color Moisture absorption Specific gravity Aspect ratio Tensile strength, kPa Young’s modulus, kPa Length evaluated, mm

Properties of synthetic fluid used.

Property Tape Flat Black Nil 0.91 260 275,790 4,136,850 70

Specific gravity, Gs Viscosity, cSt at 40 ºC Viscosity, cSt at 100 ºC Viscosity index Color Flash point, ºC Pour point, ºC

0.863 10.7 2.6 70 Clear, bright 175 –33

• What is the strength contribution of each of these additives? • What additional strength can be expected from the combination of geofiber and synthetic fluid? The experimental program to address these questions consisted of CBR (California Bearing Ratio) tests and unconsolidated-undrained (UU) triaxial compression tests at varying moisture, geofibers, and synthetic fluid contents. All tests were performed in accordance with the appropriate ASTM or AASHTO test procedures in the University of Alaska laboratories. Soil improvement was evaluated in terms of CBR values and triaxial compressive strength, in accordance with ASTM or AASHTO testing protocols. The CBR tests were performed in accordance with ASTM D1883-05, with compactive effort in accordance with ASTM D1557-02. Unconsolidated-Undrained (UU) triaxial compression tests were performed in accordance with AASHTO T296-05. Tests were conducted on the following: 1) native (i.e., unmodified) soil samples; 2) samples of soil reinforced with geofibers only; 3) samples of soil stabilized with the synthetic fluid only; and 4) samples of soil stabilized with a combination of geofibers and synthetic fluid. Weight measurements were obtained using a digital scale with 0.1 g accuracy. Water, synthetic fluid, and geofiber contents were measured to 0.1 g of the target value. The soil samples were hand-mixed thoroughly and stored in sealed containers for a minimum of one hour before compaction. Compaction was performed by a SoilTest Mechanical Soil Compactor (model CN-4235). A sectional foot was used on the mechanical rammer for compaction of all CBR test samples. The CBR test apparatus was a SoilTest G-900 VersaLoader, having a maximum capacity of 44,500 N. For CBR testing, the soil samples were tested immediately following compaction without soaking. The UU triaxial compressive strength tests were performed on samples compacted into 101.6 mm inner diameter mold. A minimum height to diameter ratio of 2 was achieved for all of the triaxial samples. The triaxial set-up used was a digitally controlled MTS type hydraulic system. A nomenclature was adopted for identifying samples: “SFC/MC/GFC”, where SFC is the synthetic fluid content as a percentage of dry soil weight, MC is the moisture content as a percentage of dry soil weight, and GFCF is the geofiber content as a percentage of dry soil weight. For example, a sample identified as “3/6/0.5” had a synthetic fluid content of 3% of dry soil weight, a moisture (water) content of 6% of dry soil weight, and a fiber content of 0.5% of dry soil weight. Similarly, samples identified as “0/11/0” contained a moisture (water) content of 11% of dry soil weight and no synthetic fluid and geofibers. 3

RESULTS

3.1 Optimum geofiber content To evaluate the optimum goofiber content at the optimum moisture content of 11%, soil samples with various geofiber contents, ranging from 0.15% to 3.25% by weight of dry soil, were subjected to Modified Proctor testing. Figure 2 shows the results of these tests. The density 91

Figure 2.

Investigation of optimum fiber content for Bethel silty sand.

Figure 3.

Investigation of the optimum fiber content for Bethel silty sand through CBR tests.

essentially remained approximately constant for geofibers content of about 0.200 to 1.000%. For geofibers content larger than 1%, the density decreased significantly. In an effort to better evaluate the range where the density remained constant (i.e. 0.200 to 1.000% geofiber content), CBR tests were performed at 0.000, 0.375, 0.500, and 0.625% geofiber content. The results of these tests are shown in Figure 3. As can be seen, the addition of geofibers significantly improves the CBR. The data suggest that the maximum improvement occurs at 0.500% geofiber content. The data also show that as the penetration of the plunger increases, so does the improvement. This indicates that the penetration mobilizes the fibers, which results in an increase in soil strength. For example, at 0.000% fiber, the maximum CBR value of 31 occurs at 5.08 mm and drops off after that. However, at 0.500% fiber the CBR values continue to increase to the limit of the loading device at 12.70 mm. The reported CBR at 5.08 mm is 63, about twice the maximum value with no fiber. To put this in perspective, typical CBR value for gravels is about 60. Crushed base course has a CBR of 90 or higher. Consequently, the optimum fiber content was estimated to be about 0.500% by weight of dry soil. 92

Figure 4. Investigation of the optimum synthetic fluid content for Bethel silty sand through CBR tests.

3.2 Optimum synthetic fluid content Initial efforts to determine the optimum synthetic fluid content proved difficult. The first approach was to try to use the synthetic fluid in lieu of water for compaction. Adding the synthetic fluid to dry soil proved nearly impossible. The results of the compaction tests with dry soil and synthetic fluid and no water were inconclusive. However, mixing the synthetic fluid with moist soil provided a more uniform soil-fluid mixture and better workability. In an effort to find the appropriate and optimum synthetic fluid content it was decided to continue the investigation at the total liquid (moisture plus synthetic fluid) content of 11%. For example if the in-situ moisture content is anticipated to be 6%, the amount of synthetic fluid added was 5%. Three synthetic fluid/water ratios were investigated; 3/8, 5/6 and 7/4. Despite the differences in fluid to water ratios, the estimated dry densities of the two compaction tests resulted in a difference of less than 1.6 kg/m3. Figure 4 presents the results from CBR tests on these mixtures along with those obtained from samples compacted at the optimum moisture content of 11% with no synthetic fluid added. The data presented in Figure 4 suggest the synthetic fluid had little impact on the strength and bearing capacity of the soil when no geofibers included. 3.3 Improvement in CBR values with the use of geofibers and synthetic fluid In order to determine how fiber and fluid work together in soil, CBR tests were performed. The water content was maintained at 6% (anticipated in-situ moisture content) and the geofibers content was maintained at 0.5%. Samples were prepared at 5% synthetic fluid content. Figure 5 presents the results of CBR testing. The CBR value improved from 32 to 38 at 5.08 mm depth of penetration with addition of 5% synthetic fluid and 0.5% geofiber content. When the same test were conducted on samples that were aged in air for 10 days, a significant increase in strength, as shown in Figure 5, was obtained. Aging the samples prepared at the 5/6/0.5 synthetic fluid/water/geofibers combination essentially tripled the CBR of the untreated soil at any penetration depth. 3.4 Improvement in cohesion and friction angle with the use of geofibers and synthetic fluid The strength of the soil was also evaluated in terms of cohesion and friction angle. Unconsolidated-undrained triaxial compressive strength tests (AASHTO T 296-05) were performed on native soil samples compacted at optimum moisture content, geofiber-reinforced samples at optimum moisture content and samples improved with a combination of geofiber and 93

Figure 5.

Aging effect on soil improvement with geofibers and synthetic fluid.

a) Response of the 0/11/0 sample

b) Response of the 5/6/0.5 sample Figure 6. Stress-strain response of the unimproved (0/11/0) and improved (5/6/0.5) samples through UU triaxial testing.

94

Figure 7. Observed failure mechanisms during triaxial testing; distinct failure plane from the 0/11/0 sample and excessive bulging from 5/6/0.5 sample. Table 4.

Summary of the UU triaxial testing results

Soil sample (SFC/MC/GFC)*

Friction angle (degrees)

Cohesion (kPa)

0/11/0 0/11/0.5 3/6/0.5 5/6/0.5 7/6/0.5

41.8 43.7 48.5 53.6 55.6

20 162 96 77 34

* SFC: synthetic fluid content, MC: moisture content, GFC: geofiber content.

synthetic fluid. Three soil samples were prepared for each group. Testing was performed at confining pressures of 17, 34, and 68 kPa. Figure 6a shows the stress-strain response for the soil compacted at the optimum moisture content of 11% with no additives. The stress-strain curve at all confining pressures goes through a peak with a following drop, which indicates the soil is strain softening. Figure 6b presents the stress-strain response of the improved soil at the 5/6/0.5 combination. The soil in this case exhibited strain hardening behavior, typical of dense granular materials. The strain hardening tendency can be attributed primarily to the reinforcement by the geofibers. Figure 7 shows the failure types observed in triaxial testing. The soil sample with no geofibers failed on a distinct failure plane whereas the sample with 0.5% geofibers content failed in excessive bulging with no distinct failure plane. The results of the triaxial testing are summarized in Table 4. Under saturated conditions, UU triaxial tests should refer to zero friction angle. However, in this study although the drainage valve was kept closed during testing, due to partially saturated condition, there was internal drainage leading to an increase in effective stress thereby the increase in strength. Therefore, the friction angle and cohesion values measured from the triaxial tests in this study are not the true strength parameters, and will only be used for comparison purposes between the improved and unimproved soil samples. Unimproved samples prepared at optimum moisture content of 11% appeared to be the weakest among all the triaxial testing samples, with 20 kPa cohesion and 41.8º friction angle. The largest cohesion (162 kPa) was obtained from the sample reinforced with geofiber only, where the friction angle was found to increase slightly to 43.7º. The largest friction angle (55.6º) occurred with the 7/6/0.5 sample. Based on the triaxial test results, one can argue that the optimum combination would be 5/6/0.5 for the soil tested. This combination was found to yield a cohesion of 77 kPa and a friction angle of 53.6º. 95

4

CONCLUSIONS

The improvement in bearing capacity of a SM class silty sand with additions of geofibers and synthetic fluid was studied through CBR tests, and the performance and strength characteristics were investigated triaxial compression tests. Evaluation of the silty sand, through CBR tests, showed marginal to significant improvement when stabilized by geofibers or combination of geofibers and synthetic fluid. The native soil at optimum moisture content, which was found to be about 11%, displayed average CBR test values of 31 at 5.08 mm depth of penetration. This CBR value falls within the typical range (20–40) for SM type silty sand. Addition of 0.5% geofibers increased the CBR values to 62 at 5.08 mm depth of penetration and to much larger values at greater depths of penetration, indicating 100% or larger improvement. With these increased CBR values, the geofiber-reinforced soil fall within the range (60–80) for well-graded gravel or sandy gravel soils. Addition of the synthetic fluid alone did not provide a noticeable improvement in the CBR values. In general, the CBR values obtained from the soil samples improved with synthetic fluid were very similar to those obtained from unimproved native soil samples at optimum moisture content. However, aging soil samples by approximately 10 days resulted in significant improvement in the CBR values. The improvement in the CBR value with aging, for the combination of 5%-synthetic fluid/6%-water/0.5%-geofibers was found to be on the order of 340%; the CBR increased from 36 (in the case of a non-aged sample) to 124 (in the case of an aged sample). In terms of soil-strength characteristics, the triaxial compression tests indicated a friction angle of 41.8° and a slight cohesion of 20 kPA for the native (no stabilizer added) soil samples compacted at the optimum moisture content of 11%. When 0.5% geofiber was added to the soil, the cohesion increased significantly, from 20 kPa to 162 kPa, while the friction angle increased by about 2° only. However, the addition of synthetic fluid along with geofiber showed a less pronounced increase in cohesion with a more significant improvement in the friction angle. The cohesion and friction angle for this case were 77 kPa and 53.6°, respectively. This appeared to be the optimum combination for the improvement of the soil investigated. Based on this limited laboratory effort, it is clear that the geofiber and synthetic fluid can significantly increase the bearing capacity and strength of SM type silty sands. However, to better evaluate the effectiveness of these non-traditional stabilizing materials further research is needed. REFERENCES Fletcher, C.S. & Humphries, W.K. 1991. California bearing ratio improvement of remolded soils by the addition of polypropylene fiber reinforcement. Transportation Research Record 1295, TRB, National Research Council, Washington, DC: 80–86. Gray, D.H. & Maher, M.H. 1989. Admixture stabilization of sands with random fibers. Proc. 12th International Conference on Soil Mechanics and Foundation Engineering, Vol. 2: 1363–1366, Rio de Janerio, Brazil, Rotterdam: Balkema. Hazirbaba, K. et al. 2007. The use of geofiber and synthetic fluid for stabilizing marginal soils. Final Report, INE Project Number RR07.03, University of Alaska Fairbanks. Li, C. 2005. Mechanical response of fiber-reinforced soil. Ph.D. Dissertation, The University of Texas at Austin. Newman, K. & Tingle, J.S. 2004. Emulsion polymers for soil stabilization. Proc. 2004 FAA Worldwide Airport Technology Transfer Conference, FAA, Atlantic City, NJ. Santoni, R.L. et al. 2002. Stabilization of silty-sand with nontraditional additives. Transportation Research Record 1787, TRB, National Research Council, Washington, DC: 33–41. Scholen, D.E. 1992. Nonstandard Stabilizers. Report FHWA-FLP-92-011, Federal Highway Administration, Washington, DC. Tutumluer, E. et al. 2004. Modulus anisotropy and shear stability of geofiber-stabilized sands. Transportation Research Record 1874, TRB, National Research Council, Washington, DC: 125–135.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Subgrade modification—practitioner’s experience T. McCleary Illinois Department of Transportation, Ottawa, Illinois, USA

ABSTRACT: Weak subgrade soils have been modified in one form or another for centuries. This paper focuses on experiences with lime and fly ash as modifiers and stabilizers in Illinois. Recent Illinois Department of Transportation projects in McLean and Grundy Counties in Illinois are highlighted to discuss the need for proper testing prior to using these stabilizers in the field to ensure satisfactory results. The paper also discusses through case histories the consequences of not performing both the necessary tests and providing adequate monitoring during construction. 1

INTRODUCTION

Stabilization by mixing has been used as a tool for creating a uniform base on which to build a pavement since the 1920’s (Rodriguez, Castillo and Sowers, 1988). While the equipment and the chemicals have changed, the principals remain the same. The mixing of soils no matter if it was just with other soils with more desirable properties or with chemicals such as cement, lime or fly ash, the intent has always been to improve the properties of the in situ soils. The word lime can mean a variety of products such as quicklime (calcium oxide—CaO), hydrated lime (calcium hydroxide—Ca[OH]2), lime slurry which is a suspension of hydrated lime in water, and can be made from either hydrated lime or quicklime or lime kiln dust (National Lime Association, 2004). Fly ash, on the other hand, is a by-product of coal manufacturing. Besides the chemical makeup of these materials, the differences of their reactions set them apart from each other. Lime typically needs a minimum amount of clay to react with to result in a favorable outcome. Fly ash does not need the clay but the amount of fly ash needed to achieve the same result can be as high as 3 to 4 times that of lime. Because fly ash does not need the clay to react, it is well suited for granular soils. This paper first gives a historical review of engineering practice in subgrade soil modification at the Illinois Department Transportation (IDOT). Then, several case histories are described in detail on the successful use of lime and fly ash as modifiers in highway projects sponsored by IDOT District 3 office located in Ottawa, Illinois. The paper finally gives concluding remarks on how to perform necessary tests on determining the type of stabilizer to use and the importance of providing adequate monitoring during construction. 2

HISTORICAL REVIEW OF PRACTICE

The practice of soil modification within the boundaries of the Illinois Department of Transportation (IDOT) District No. 3 has been primarily with hydrated lime. Quicklime can be very harsh to workers skin and respiratory systems and contractors routinely shy away from it. The main problem with the use lime slurry has often been the uneven distribution on the job site. The use of hydrated lime peaked for District 3 during the construction of the subgrade of Interstate 39 (I-39) in the 1980’s and early 1990’s. The surficial soils on this alignment were primarily cohesive in nature with areas of silt and fine sand. At the time, the practice was to construct fill sections with a local cohesive material with clay content greater than 15% and with a plasticity index (PI) greater than 12. The cut sections meeting these criteria were disked and dried and ultimately lime modified to a depth of 30.5 cm (12 in.) along with the 97

constructed fill sections. Soils with less clay content were often replaced with aggregate and geosynthetics. Some areas were treated to depths as deep as 61.0 cm (24 in.). While the standard subgrade treatment was lime modification, the field work routinely encounter soils that were non-reactive with lime and were undercut. The typical undercut at that time was to remove 45.7 cm (18 in.) of subgrade soil, place a geotextile type fabric and backfill with 30.5 cm (12 in.) of crushed limestone meeting IDOT’s CA-7 gradation and 15.2 cm (6 in.) of crushed limestone meeting IDOT’s CA-6 dense graded base gradation. Silts and sands with less than 12% clay showed poor performance after treatment with lime. This threshold was elevated to 15% to ensure there was enough clay content in the soil to be modified. Prior to treatment, the subgrade soils were brought up to grade in approximately 20.3-cm (8-in.) thick compacted lifts. The moisture content was not to exceed 110% of optimum moisture content and the density was to be 95% of the standard Proctor density. There has been some discussion as to why the top lifts were compacted prior to tilling together with lime. This is to ensure that there is enough pre-treated material within the prescribed depth of treatment. This also goes toward the goal of uniformity. There is no practical way to get a subgrade to be of all the same material with the same strength or modulus but specifications require controlling the moisture content and compacting the material to achieve a uniform subgrade. Large tillers were used to incorporate lime with subgrade materials as evenly and thoroughly as possible. In some instances, the tillers made multiple passes to blend the material together. At the time, the treatment depths were 30.5 cm (12 in.), 45.7 cm (18 in.) and 61.0 cm (24 in.) depending on the depth of weak material. The equipment effectively treated to a maximum depth of 35.6 cm (14 in.), therefore, to reach the depths desired in the plans, such as the 61.0 cm (24 in.), the top 25.4 cm (10 in.) of soil was removed and the lower 35.6 cm (14 in.) was treated. The material previously removed was returned to its original location and treated with lime in the same manner as the previous lift. Today’s practice has not changed much from that of 20 years ago but the modifying agents have. Today, the industry commonly uses lime, fly ash and cement as modifiers and stabilizers. In choosing the proper agent, one must ask what is to be accomplished by modifying or stabilizing the soil. Is it lowering the liquid limit of expansive clays, producing an improved subgrade for pavement design or simply producing a working platform to pave on considered as the objective? Modification and stabilization of subgrade soils has been tied to increasing the stability of the subgrade. The level of improvement has been checked by nuclear density gauges, dynamic cone penetrometers and proof rolling. Typically, it is a combination of two or more of these methods. By specification, IDOT runs nuclear density tests and dynamic cone penetrometer (DCP) tests for acceptance. Proof rolling is used in IDOT District 3 to locate areas in question to test with the DCP. The success of a soil modification project is dependent on the insitu soils and the modifying materials available. Another factor greatly affecting the results of the project is the level of experience of the designer, inspector and contractor. The designer needs to insert the proper specifications and quantities into the plan documents. The proper application rates of the modifying agent and water need to be stated in the plans. These rates may be altered in the field by the inspector who has experience in doing so. It is desirable for all parties to have similar expectations of the end result. The designer wants a subgrade strong enough to build the pavement upon. The contractor wants the subgrade to be strong enough to hold up to the construction traffic and the inspector should ensure the owner of the project is getting what they are paying for. 3

CASE HISTORIES

A project that suffered from the lack of experience of an inspector is the widening and reconstruction of County Highway 29 in McLean County, Illinois. The county hired a consultant to oversee the construction of this project which included widening the roadway from two 98

lanes to five lanes. Construction of storm sewer, curb and gutter and new ditches was also included in the project scope. The liming operation was completed in early fall of 2000. It was reported afterwards that the inspector was not getting passing density readings with the nuclear gauge in the lime treated subgrade. Recognizing this, the inspector decided to proof roll the subgrade. No signs of instability were reported during the proof roll which resulted in the subgrade being approved by the inspector. The following February, numerous ridges in the bituminous pavement were noticed, some as high as 5.1 cm (2 in.) formed across the pavement. As a courtesy to the county, IDOT took pavement cores and samples of the subgrade soil and found the soil did not meet the Department’s frost susceptible threshold. The Department’s criteria for a soil to be considered frost susceptible warranting some form of remediation follows the U.S. Army Corps of Engineers frost class F4. IDOT defines it closer as a soil is not considered to be frost susceptible unless the level of capillary rise is within the depth of frost penetration, 65% silt and fine sand, according to AASHTO T 88 and the plasticity index is less than 12 (Illinois Department of Transportation, 1999). This is not to say that frost heave will not occur in soils with less silt and fine sand but it is less likely. Figures 1 through 3 show the results of the grain size analyses of soil samples gathered from six locations along the project. These samples were gathered from various depths within the modified subgrade and below. The specimen identification columns in each of these three figures show the location number and the depth in feet (1 ft = 30.5 cm) from which the sample was taken. The intended depth of treatment was 30.5 cm (12 in.). Therefore, it was assumed that the soil samples from depths greater than 30.5 cm (12 in.) were not treated with lime. This was confirmed by spraying phenolphthalein on the soil samples. A closer visual observation of the soil samples revealed that the soil had free lime or unused lime in the matrix. This was not determined by any other means than a visual inspection of the samples. This was in the top 30.5 cm (12 in.) of the subgrade directly beneath the pavement. The recommendation from IDOT to the County was to mill the new bituminous pavement and resurface it. The County chose to simply mill the ridges or bumps smooth. The amount of free lime in the matrix during the next year’s winter would be negligible. The question that remained was to determine why so much free lime was left in the soil. After interviewing the County’s engineers, the contractors and the consultant inspector, it was determined only half the water needed for the operation was used. The subgrade had adequate stability but not density. Unfortunately, the stability observed was a dry-condition stability since not enough water was used when processing the lime. Accordingly, the failure was noticed in late winter and early spring. The temperatures in Fahrenheit were in the 40’s (single digits above 0 degrees Celsius) during the day and in the 20’s (negative single digits in Celsius) at night. The snow melt drained into the subgrade through the bituminous pavement. The subgrade accepted the water readily as it had an abundance of free lime that was starving for moisture. With the moisture held in the upper 30.5 cm (12 in.) of the subgrade, even a relatively shallow freeze could cause a problem. Water expands up to 10% of its volume. This is compounded by the freeze thaw cycles each day rearranging the soil-water-air matrix. The inspector moved from the poor density readings to proof rolling without checking to see how much water had been used. If the water was monitored and the appropriate amount had been used, the heaving problems may not have occurred. When the correct moisture content is achieved, the soil can be squeezed into a ball. When this ball is squeezed between the thumb and the forefinger it should pop apart. If the ball does not pop apart but rather the thumb and finger simply push into the ball, the moisture content may be too high. If the ball is not formed easily by squeezing the soil with one hand, the moisture content may be too low. The moisture content may be checked by many methods, nuclear gauge or speedy moisture tester but the true moisture content should be determined with an oven meeting the specifications of AASHTO T 265. Another project that didn’t reach the results expected was Illinois Route 53, through Gardner, Illinois where the road crosses a railroad track at the south edge of town of Gardner. 99

Figure 1. Properties of soil samples 1 and 2 collected from County Highway 29, McLean County, IL.

This project involved removing the existing structure and building a new bridge with approximately 91.4 cm (3 ft) additional clearance. To do so, the profile grade was raised and the slopes were widened. Four soil samples were obtained from two test pits excavated from the proposed borrow pit, tested and approved for use with 4% lime for modification at subgrade level. This 4% design value was obtained by running an immediate bearing value (IBV) test, which is similar to running an unsoaked California Bearing Ratio (CBR) test. The IBV tests 100

Figure 2. Properties of soil samples 3 and 4 collected from County Highway 29, McLean County, IL.

gave values between 10.0 and 12.0, which met IDOT’s strength acceptance criteria for lime modified soils (Illinois Department of Transportation, 1999). The new profile grade line went from the original ground to approximately 914.4 cm (30 ft) above original ground at the new structure. When asphalt was placed late in the fall of 2000 and in early spring of 2001, several locations heaved as much as 7.6 cm (3 in.). Capillary action could bring moisture up to this height above the water table. The height of capillary 101

Figure 3. Properties of soil samples 5 and 6 collected from County Highway 29, McLean County, IL.

rise is a function of suction potential influenced by the soil type or grain size and the depth to ground water table. Another source of moisture in the soil is from above through the pavement. This is quite possible as the late winter days brought snow in the night and thawed during the day with temperatures in Fahrenheit at mid to upper 30’s (slightly above 0 degrees Celsius). 102

Figure 4.

Properties of soil samples collected from Illinois Route 53 near Gardner, Illinois.

The soils approved for use from the borrow pit were not considered frost susceptible in that they did not meet IDOT’s definition of frost susceptible. However, the soil found in the subgrade was not texturally the same as that tested prior to construction. The material found under the pavement was 71.1% silt and fine sand with a plasticity index of 11 and field moisture of 38%. It is possible and quite probable the silt content was increased with the chemical reaction that took place during the curing of the lime modified mixture. Adding lime to clay 103

Ice Lenses

Figure 5. Ice lenses in sample taken from problem subgrade of Illinois Route 53 near Gardner, Illinois.

will often lower the liquid limit and in turn may lower the plastic index, PI of the soil. This subgrade was reported as being extremely difficult to drive forming pins into and it did not deflect during the paving operations. The excessive moisture and resulting instability came after the bituminous surface layer was paved. It is believed the inspector did not monitor the material being taken from the borrow pit and placed in the upper 61.0 cm (24 in.) of the embankment. The material was very close in color to what was approved but had higher silt content. Had this material been caught before it reached the subgrade and the proper material placed, the heaving problems may have never taken place. The properties of the soil samples collected and tested after the heaving problem are shown in Figure 4. It has been an unwritten policy to only lime modify soils with clay contents greater than 15% and preferably greater than or equal to 20%. As indicated in Figure 4, there is plenty of clay content to have reacted with the lime. The amount of water was monitored and the planned quantity was used. As mentioned earlier, it is possible and quite probable that the silt content was increased with the addition of the lime. Adding lime to clay will often lower the liquid limit and in turn, may lower the plastic index, PI of the soil. The permeability may have increased with the addition of lime allowing for moisture to penetrate the soil-lime mixture. Figure 5 shows ice lenses in a sample taken from the problem subgrade of Illinois Route 53 project. The heaving areas were rather larger compared to the limited areas observed in the previously discussed McLean County project. These areas did not always go across the entire pavement and were in excess of 152.4 cm (5 ft) long. The heaving areas seen on the McLean County project were abrupt ridges approximately 30.5 cm (12 in.) long and about 2.5 cm (1 in.) in height. The remedy for this project was to install transverse under drains across the pavement to take as much moisture away from the subgrade as possible, mill the existing bituminous surface and repave. To date, this remedy has worked in that there is no heave problem. Fly ash has been primarily used as a drying agent in IDOT District 3. In addition, it was also used in winter months to generate heat to reduce the amount of frost during the process of building embankments. In this case, the fly ash was mixed with non-frozen but relatively wet soil in an open field area, collected and deposited on site with scrapers. During the night time, the area was covered with plastic to retain the heat. Each morning, the plastic was removed 104

and the same process of mixing and placing continued. Only two percent (2%) fly ash was used in this process. Typically, the fly ash amounts used are near 10% but the desired result in this case was to dry the soil and create heat and not to provide a large strength gain. In areas where it is readily available, fly ash is being used to modify silts and sandy soils. The IDOT specifications currently restrict the type of fly ash used in soil modification to be class C. Other types have been used as an embankment material but are not approved as a modifier. In one instance, when very fine sand was encountered in the subgrade of a subdivision street in Coal City, Illinois, the stability of these soils was in question well before the concrete trucks were having mobility problems due to sinkage. Nevertheless, that brought it to the attention of the owners of the concrete company and construction companies involved in the project as they could no longer reach the areas they desired to work in. The subgrade was basically fine sand found just below the topsoil. The topsoil was removed from the subgrade but the depth of the sand was too great to remove it all and the cost of aggregate was too great for the developer to add to the project. Fly ash was chosen because of its availability and relative low cost when compared to the removal and replacement with aggregate. The immediate bearing values, IBV, as determined in the field with the DCP averaged 7.6-cm (3-in.) penetrations per blow into the loose fine sand. After modifying with fly ash, the IBV’s averaged near 20. This is a significant increase in strength with only 11% fly ash mixed with soil. Fly ash, unlike lime does not require clay for the modification to be successful and therefore lends itself to modification of silts and sandy soils. Fly ash may not provide the needed strength gain to be considered for stabilization of a soil, therefore, undercutting or other remedy may have to be incorporated if stabilization requirements are to be met. Lime modification and stabilization may be used with soils having clay contents greater than 20% and have been successfully used with soils having 15% clay content. Lime, fly ash and even cement have little long term effect on top soils. 4

CONCLUDING REMARKS

The preconstruction design should include sampling and testing the soils to determine their strength, in situ moisture content and soil classification based on a particle size analysis. This will determine the pavement design parameters, the level of frost susceptibility and whether or not the soil should be treated or removed and replaced with a better soil or aggregate. With any modifying agent, laboratory testing should be performed to define the appropriate application rate of agent and water. The particle size analysis of the soil is to be determined according to AASHTO T-88. A pre-agent Proctor test should be performed using AASHTO T-87 and T-99 (Method C) and a penetration test according to AASHTO T-193 immediately after compaction without soaking in water should be performed. The soil should be mixed with the desired percentage of agent and a post mixture Proctor and penetration test should be performed using the same test methods as before the mixture. The IBV calculations should be performed according to AASHTO T 193. If the desired IBV is obtained, the laboratory testing is deemed complete. If laboratory IBV is too high or too low, the percentage of agent used should be adjusted accordingly and the post mixture testing resumes as described above. During construction the inspecting staff should be checking quantities for errors and ensuring the proper amounts of each ingredient is being used to produce the target strength, stability and density values. The inspectors should be collecting the truck tickets from each shipment of modifying agent and verifying weights if desired. The inspectors should routinely monitor the water meter at the source of water. The inspectors need to measure each area of treatment and determine the proper quantity of agent and water used as well as the design depth of treatment before going to the next area. Before completion, the particular construction parameters should be checked and confirmed whether on they meet specifications. For Illinois Department of Transportation, this includes density check with the nuclear gauge and stability check with the dynamic cone penetrometer. Most importantly, the inspector should use common sense. If the nuclear gauge says that the area has the 105

required compaction, yet, the construction traffic is causing significant rutting and mobility challenges, there is a problem and needs to be addressed. REFERENCES Rodriguez, A., Castillo, H. & Sowers, G.F. 1988. Soil mechanics in highway engineering. TransTech Publications. National Lime Association, 2004. Lime-treated soil construction manual, lime stabilization & lime modification, January. Illinois Department of Transportation, 1999. Geotechnical manual. Bureau of Materials and Physical Research, Springfield, Illinois.

106

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

“Baku Bayil Yard Site” soil improvement geotechnical works E. Guler Bogazici University, Istanbul, Turkey

A. Gure Tekfen Engineering, Istanbul, Turkey

E. Cetin ELC Group, Istanbul, Turkey

ABSTRACT: Bayil Yard is located to the south of Baku—Azerbaijan and is allocated as a fabrication yard for top portion of oil platforms in the Caspian Sea. The owner is AIOC who is a consortium founded for Azerbaijan Oil Contracts led by BP (British Petroleum). For the heavy cranes working on this site a soil improvement project was realized to increase the bearing capacity. Two different loads were considered. One area would be exposed to cranes which apply a maximum load of 600 kPa through their crawlers. A second area was for cranes which apply at the maximum a load of 200 kPa through their crawlers. For the 600 kPa area a stone column and a geogrid reinforced top layer was implemented. For the 200 kPa area only a geogrid reinforced layer was used. The stone columns also helped eliminate the liquefaction risk at this area.

1

INTRODUCTION

Baku Bayil Yard is located to the south of Baku—Azerbaijan and is allocated as a fabrication yard for top portion of oil platforms in Caspian Sea. The owner is AIOC who is a consortium founded for Azerbaijan Oil Contracts led by BP (British Petroleum). All engineering and site works were executed under the supervision of Halliburton-KBR who was the consultant to the owner. The main contractor was a joint venture between AMEC-UK and AZFEN— Turkish-Azerbaijan Company. This paper presents the geotechnical works designed for the Baku-AZFEN yard site as part of the site infrastructure construction. On this site very heavy off-shore platforms were planned to be constructed. To increase the speed of construction some parts were planned to be assembled in the shop and transferred directly to the assembly zone. The actual structure was assembled on a platform which had piled foundations. For the area where crawler cranes will be operating, soil improvement was required. The area where crawler cranes will be operating was divided into two sections. The first area is an area where very heavy cranes will operate and here the maximum load applied by the crawler is specified as 600 kPa. A second area has been specified, where lighter cranes will operate and in this area the maximum load applied by the crawler was specified to be 200 kPa. The bearing capacity was problematic since the upper soil layer consists of loose sand and below this sand there is a thick soft clay layer as explained in detail later on. The upper layer had also a liquefaction risk. So, the following work items have been identified and analyzed: 1) surficial soil improvement, 2) deep soil improvement to provide sufficient bearing capacity and eliminate liquefaction risk. 2

SOIL PROPERTIES

Many borings were conducted on the site. Three of these borings are close to this site and all these boreholes are 40 m deep. An idealized geotechnical cross-section of the site was 107

Figure 1. General layout of site (grey area indicates stone columns and darker dots indicate bored piles).

developed based on the information gathered from the borehole logs and laboratory test data provided in the geotechnical report (Anon., 2000). Soil layers and associated properties given below were used in all of the subsequent analysis. Loose SAND: The thickness of the sand layer is 8 m. This layer is mixed up with shell, clay material. In the SPT tests conducted, the representative average SPT blow number values are between N = 4 and N = 10 and corresponding properties are as follows: Unit weight: Friction angle: Cohesion: Modulus of elasticity: Poisson ratio:

16 kN/m3 31º 5 kPa 12,500 kPa 0.30

Soft CLAY: The average thickness of the soft clay layer is 9 m. The logs indicated that this layer is mixed up with sand. Representative average SPT blow number values are between N = 4 and N = 7 and corresponding properties are as follows: Unit weight: Friction angle: Cohesion: Modulus of elasticity: E from consolidation: Poisson ratio:

17.5 kN/m3 0º 20 kPa 5,000 kPa 1,500 kPa 0.30

Hard CLAY: This layer is encountered at the base of the alluvial deposits starting from a depth of 15 ∼ 22 m below ground surface; all the boreholes were completed within this layer. Representative 108

Figure 2.

A general view of the site.

average SPT N value is 50. Based on this N value and laboratory test results, properties were selected to be as follows: Unit weight: Friction angle: Cohesion: Modulus of elasticity: Poisson ratio:

3

20 kN/m3 0º 200 kPa 75,000 kPa 0.35

LOADS TO BE TRANSFERRED FROM CRANES

The heavy crawler crane system that is operated on the site is DEMAG CC 400. At the area in which DEMAG CC 400 crawler crane will be operated, the maximum load to be transferred to the soil from this crane is 600 kPa. Outside of 600 kPa crane running area the land is designed to resist a load of 200 kPa since lower capacity crawler cranes will be operated in this zone. 4

PROPOSED GEOTECHNICAL WORKS FOR THE 200 kPa LOAD AREA

On the area where maximum pressure of 20 t/m2 will be operating it was decided to conduct three plate load tests to simulate the effects of the load that will be applied by the crawler cranes and to decide whether the soil is usable as it is. This simulation will not be reflecting the real condition completely, because the load of the crawler cranes will be applied several 10’s or 100’s of times, where the load applied by the plate load test will be of static nature. However, to make the simulation as realistic as possible, a plate size of 1.35 m × 1.35 m was used. To consider the effect of dynamic loading it was demanded that the ratio of the elastic modulus of the soil does not increase by more than 2.2 times from the first loading to the second loading. This will help to insure that the soil does not deteriorate under repeated loading conditions. To provide a reasonable soil that can firmly support the crawler cranes, it was also requested that the Elastic Modulus of the soil should not be less than 60 MN/m2. In addition to be bearing capacity and excessive settlement problem, a liquefaction problem in the upper sand strata exists. A liquefaction analysis was conducted for the 109

Table 1.

Results of plate load tests.

Plate load test no

SB 01

SB 02

SB 03

Ev1 (kN/m2) Ev2 (kN/m2) (Ev2)/(Ev1)

19,370 48,600 2.51

17,180 43,800 2.55

28,100 44,700 1.59

sand layer in the area. The factor of safety values against liquefaction range between 0.33 to 0.77 and are significantly lower than 1. However no measure against liquefaction was recommended in the area, since earlier it was decided by the owner, that the liquefaction risk in this area is tolerable. The Elastic Modulus values using the linear portions of the load settlement curves are calculated using the following formula: Ev = 0.89 × (Δp/Δs) × L, where Ev is the Elastic Modulus, 0.89 is a constant considering shape and rigidity of the loading plate Δp is the pressure difference, Δs is the settlement corresponding to Δp and L is the square root of the plate surface area. Using the above given formula, following Elastic Modulus values have been calculated for the initial loading (Ev1) and for the second loading (Ev2). The results are given in Table 1. As can be seen from the above given values all Elastic Modulus values are below 60,000 kN/m2 and two of the (Ev2)/(Ev1) ratios out of three are above 2.2. Therefore based on the test results it was concluded that the natural ground does not provide the necessary surface for the crawler cranes to operate on the field safely for a reasonable time period and an improvement in the ground is necessary. 4.1 Final design In order to provide enough bearing capacity for the crawlers of the cranes and prevent uncontrolled settlements, a geosynthetic reinforced base was chosen as the most suitable technique in terms of performance and cost. The geosynthetic reinforced base consisted of a geosynthetic reinforced granular fill of a total thickness of 0.50 m. Since the natural soil is of granular nature, a separation geotextile was not necessary. However before laying out the geogrid on the site, where clayey soils were encountered a simple geotextile was laid out on the field as a separator to prevent the fines to fill in the voids of the clean granular fill. The next step was laying out a 25 cm thick granular material and compacting it. The detail of the design is given in Figure 3. The geogrid reinforcement was laid out on this gravel layer. To provide the lateral stability of the granular fill on the top, a single layer of high strength (PET) geogrid reinforcement was found to be necessary. This type of reinforcement was chosen because of its high Elastic Modulus, which allows it to take upon itself the maximum load with minimum strain. The characteristics of the proposed geogrid are given below: Tensile strength (ISO 10319):

Machine direction: Cross-machine direction: Elongation (ISO 10319): Machine direction: Cross-machine direction: Tensile strength at 2%: 15 kN/m Tensile strength at 3%: 19 kN/m Creep limited strength (120 years): 42 kN/m Aperture size: in both directions in the order of magnitude of 25 mm

80 kN/m 80 kN/m 15% 15%

For the last 25 cm of the fill granular material with smaller grain size has been used to provide a better rolling surface for the cranes as well as the regular vehicles moving on the field. The specifications of both fill materials are given below. 110

25

40

25 cm Gravel Layer

25

Geogrid Layer

25 cm Gravel Layer

Natural Ground

Concrete

Geogrid Layer VARÝABLE

25

25

200

20 t/m 2 LOAD AREA

Geogrid Layout detail Next to Pile Head

Figure 3.

Typical Cross section of the 200 kPa loaded area with geogrid reinforcement.

Figure 4.

Finite Element model of the 200 kPa loaded area.

The grain size distribution of the first (or lower) layer of granular material was specified to be between the limits provided below: Sieve opening (mm) % Passing

50 100

37.5 80–100

25 60–90

9.50 30–70

4.75 25–55

2.00 15–40

0.425 8–20

0.075 2–8

The granular material specified above had also to satisfy the following criteria: The flatness index should be lower than 40%. The material compacted to 98% of modified Proctor energy should have a minimum wet CBR value of 100%. The granular material to be used in the second and uppermost layer was specified to consist of smaller sized particles and shall contain a reasonable amount of fines in order to provide a smoother rolling surface. The grain size distribution of the granular material to be used in the uppermost layer satisfied the limits provided below: Sieve opening (mm) % Passing

25 100

19 80–100

9.50 60–100

111

4.75 50–85

2.00 40–70

0.425 20–45

0.075 0–12

The granular material specified above should also satisfy the following criteria: The flatness index should be lower than 40%. The material compacted to 98% of modified Proctor energy should have a minimum wet CBR value of 100%. A typical cross-section of the proposed design is given in Figure 3. This design was made as an empirical design. Some simple limit equilibrium analysis was conducted to verify the design. However the appropriateness of the design was verified by Finite Element analysis. The model used in the FE analysis is given in Figure 4. 5

PROPOSED GEOTECHNICAL WORKS FOR THE 600 kPa AREA

It was determined that in this area two problems exist. One is a bearing capacity problem and the second is a very serious liquefaction problem. Therefore the soil improvement must be able to reduce the amount of settlement, increase the bearing capacity and prevent liquefaction. For eliminating the liquefaction problem and providing enough bearing capacity a combination of two soil improvement schemes was planned. The geotechnical works that were developed given the soil profile encountered at the site comprised of: Geosynthetic reinforcement applications and soil improvement by installing stone columns. These techniques will be used to improve the soil conditions for the area that will support the 600 kN/m2 load. This was necessary because an excessive settlement under the crane crawler during the lifting of a heavy weight will cause a leaning of the crane tower and in consequence this sudden deformation will endanger the stability of the crane. 5.1 Stone column design Installation of stone columns using the vibroflotation technique was proposed as a soil improvement in this area. In this technique a vibrator is lowered into the ground with the help of pressurized water (Figure 5). Than stones are fed from the top and compacted in-situ with the help of the vibroflot. The vibroflot during this process does not only compact the stone column itself but also the surrounding soil around it. By working its way upward in this manner, a stone column with a densified soil surrounding it was obtained. Providing a soil improvement scheme of installing stone columns using the vibroflotation technique will automatically eliminate the liquefaction risk. For a square grid the dimensions of the grid is determined with the following formula (Anon., 1998): X = [((1 – e0) × As)/(e0 – e1)]1/2 where; X = pile distance; e0 = soil void ratio; e1 = soil void ratio after planned improvement; As. Considering the heavy loads and high demand on soil improvement, the diameters of the Stone Columns are chosen to be 0.80 m. The maximum and minimum void ratios possible have been used for the determination of void ratio reached as a result of improvement (e1) made on the site. For this purpose the following maximum and minimum void ratios have been used (Anon, 1998): emax = 0.02Fc + 1.0; emin = 0.008Fc + 0.6 Fc in this formula is the fine particle ratio in the soil (material passing No: 200 sieve). As a result of sieve analysis tests conducted it is understood that fine particle ratio is on the average 15%. From this point emax and emin are respectively found to be: emax = 1.30 and emin = 0.72. Considering definitions of boreholes drilled in the section where the heavy cranes will transport heavy parts and the results of SPT values within dominant sand formation, the natural soil void ratio has been foreseen, based on values given in the literature for these types of soils as: e0 = 1.30. When the extreme loads to be applied by the cranes and the possible soil problems under these loads are considered, it is concluded that the sand after improvement shall be as dense as possible. Therefore the void ratio after soil improvement was chosen to be equal to the minimum void ratio that was calculated based on the empirical approach. It was therefore concluded that e1 = 0.72 is an appropriate value. When all these values are placed in the formula, the stone column spacing is calculated to be ∼1.40 m. It is known that when a 112

Figure 5.

Tip of the Vibroflot = area of pile.

Figure 6. Relative Shear Shading (Darker areas indicate higher shear stress).

Figure 7. Deformation Shading (Darker areas indicate bigger deformation).

triangular path is chosen the side of the triangular grid can be larger by a coefficient of 1.075. After this preliminary design, a finite element analysis was conducted to check the bearing capacity problem and calculate the settlements expected under the given load conditions. To represent the conditions as truly as possible the crane was modeled as having a main frame and two crawlers. Also the position of the crane on the field can have an affect, because part of the crawler will be sitting on the stone columns itself and part of the crawler will sit on the soil improved by the stone columns. Investigating the geometry indicates that there is basically two positions of the crawler that will be most critical. Therefore two separate analyses were conducted for those two positions and these analyses are named as Position 1 and Position 2. 113

The 0.8 m diameter stone columns placed with a spacing of 1.4 m must reach the base of the sand strata and on the average the net length of the stone columns was 8 m. The deformations caused by a 600 kPa stress on the improved soil was 35 mm based on numerical simulations in Position 1 and 45 mm based on numerical simulations in Position 2. Some results of the Finite Element Analyses are shown in Figures 6 and 7. In Figure 6 the ratio of shear stresses to the shear strengths are shown as shading. It can be seen that shear stresses are concentrated in the stone column and dense sand which has been densified by the stone column installation. Figure 7 gives the amount of deformations under the eccentrically loaded crane. It can be noted that the maximum deformation is contained within the top half of the stone column area, however the soft clay layer also contributes to the maximum settlement. 5.1.1 Quality control/quality assurance issues To assure that the above described soil improvement scheme of stone column construction using the vibroflotation technique was successful, the application of the soil improvement scheme was tested. Since the purpose of the soil improvement is not to install stone columns alone, but also densify the loose soil around it, this fact was verified. For this purpose five Dynamic Cone Penetration Tests (DCPT) have been conducted in the evaluation area of the Stone column installation. The DCPT results were converted to CPT cone resistance values using correlations. The so determined cone resistance value is normalized using the relation: qc1 N = (qc – σv0 /Pa)(Pa/σv0) and is hence a unitless value. The individual Normalized Cone Resistance values (qc1 N) obtained and their averages are given below. The averages are given both for each test and each depth. The table consists of two portions. Since the correlations

qc1 N values assuming the strata is all sand: Test no:

Average values

DP1

DP2

DP3

DP4

DP5

Average values

411

731

602

377

326

489

295

364

281

183

198

264

189

221

182

122

204

184

197

234

274

133

264

221

158

186

182

204

282

203

201

152

141

183

255

186

206

232

163

100

261

192

225

294

227

169

238

231

235

302

256

184

254

qc1 N values assuming the strata is all silty sand: Test no:

Average values

DP1

DP2

DP3

DP4

DP5

Average values

308

548

451

283

245

367

221

273

211

137

149

198

142

166

137

92

153

138

148

176

205

100

198

165

119

140

137

153

212

152

151

114

106

137

191

140

155

174

122

75

196

144

169

221

170

127

179

173

177

226

192

138

190

114

for sand and silty sand to obtain the cone resistance qc1 N are different. If the stratum is sand, the values in the first table must be used, and the required qc1 N value for ensuring that no liquefaction will take place is 140. If the stratum is silty sand, then the second table must be used and the required qc1 N value for ensuring that no liquefaction will take place is 80. Since the strata consist of an alternating sand and silty sand layer, both cases have been considered for each measurement. There are only there individual qc1 N values that are lower than 140 when the whole strata is assumed to be pure sand and only one value is below the required value of 80 when the strata is assumed to be silty sand. However when the average values are analyzed, it can be seen that neither for a single column, nor for a certain depth there is a liquefaction risk, since the average cone resistance values are all well above the required qc1 N values. So based upon DCPT testing it can be concluded that the liquefaction risk has been successfully eliminated with the installation of the Stone columns. 5.2 Geogrid reinforcement To provide the lateral stability of the granular fill on the top, a single layer of high strength (PET) geogrid reinforcement was found to be necessary. This type of reinforcement was chosen because of its high Elastic Modulus, which allows it to take upon itself the maximum load with minimum strain. In this section granular fill had a thickness of 75 cm and was constructed in three layers of equal thickness. The required characteristics of the fill materials are as given for the 200 kPa loaded area. Again in the last layer of the fill a granular material with smaller grain size was used to provide a better rolling surface for the vehicles moving on the field. It is recommended in the literature, that the soil improvement below the loaded area is extended towards the outside by an amount of 2/3 of the to be improved soil thickness (Anon., 1998). So if we consider the upper sand strata to have a thickness of 8 m the necessary extension of the improved area shall be 5.3 m and it can be said, that considering that there is also a soft clay layer present underneath the sand, this extension of 5.3 m is a minimum value. As a conclusion it can be stated that the above given design provides a suitable platform for the heavy DEMAG CC 400 crawler cranes to operate on the stabilized fill. The design of the geogrid was chosen based on the polymer type (Elastic Modulus), tensile strength and on survivability criteria. 6

CONCLUSION

All soil improvement work was completed in June 2003 and the yard is under operation since the end of 2003 till today without any problem of bearing capacity or damage. Both areas are subjected frequently to heavy loading by crawler cranes as has been foreseen during the design. Parts of the area are also used to store heavy parts. The design with stone columns and geogrid reinforced base proved to be a very economical and very efficient solution to the bearing capacity problem. REFERENCES Anon. (1998) “Remedial measures against soil liquefaction” Edited by the Japanese Geotechnical Society, A.A. Balkema. Anon. (2000) “AZFEN yard site investigation report rev. B” Performed according to AMEC’s proposal reference CD/LA/11-00/1343, December, 2000.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Resilient characteristics of bottom ash H.H. Titi, A.R. Coenen & M.B. Elias Department of Civil Engineering & Mechanics, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA

ABSTRACT: This research aimed at evaluating the characteristics of coal combustion bottom ash for potential utilization in pavement construction materials. A comprehensive laboratory testing program was undertaken to evaluate the physical properties, compaction characteristics, and resilient modulus of bottom ash. The investigated bottom ash was obtained from power plants in Wisconsin and Michigan. Test results showed that there is a wide spectrum of bottom ash properties pertaining to specific gravity and unit weight; the investigated bottom ash samples were classified as granular material. Repeated load triaxial testing was performed to determine the resilient modulus of the bottom ash. Specimens were tested at the maximum dry unit weight and optimum moisture content. Test results demonstrated that the resilient modulus values of bottom ash vary depending on the physical properties and unit weight of the bottom ash. For four bottom ash types, the resilient modulus values were low compared with that of typical subgrade soils, while for one type the resilient modulus was comparable with/higher than that of a typical subgrade soil. 1

INTRODUCTION

Coal combustion power plants are a major provider of electricity worldwide. In the 1970’s, power/electric companies were already responsible for consuming nearly 80% of the total coal produced each year (within the U.S.). Coal ash is a by-product of the combustion process. This coal ash is generally divided into two types of material: fly ash (finer, predominately airborne) and bottom ash (heavier and coarser than fly ash, much of which settles to the bottom of the furnace). Together they amount to more than 90 million tons of coal ash per year in the United States alone. In years past, this material was considered a waste. However, studies have found the fly ash to be particularly useful due to the cementitious properties of the material. As additional studies were conducted, advanced uses for fly ash were developed. On a global scale, several countries now put 75% or greater of the coal ash they produce to productive use. The material that does not have a beneficial use is still being placed in landfills or ponds. Of the total coal ash produced, nearly 20% is bottom ash. However, less than 50% of the total bottom ash created as a by-product of coal combustion is put to use after the generation of electricity. This provides an opportunity for identifying uses for the remaining >50% of bottom ash in construction and the opportunity to reduce disposal cost and space. It is the goal of this study to determine characteristics of the coal combustion bottom ash to develop new/extended uses for the material. Many tests have been conducted to determine the chemical properties of bottom ash to ensure its safe application within approved uses. In Wisconsin and surroundings, We Energies (a Wisconsin power company) bottom ash has been beneficially used as backfill, an aggregate in concrete and in asphalt, in pavement base and subbase course layers and in manufactured soils. It has been found that bottom ash can be safely placed on site and additional research on its physical properties will investigate the structural integrity. A major input parameter in the new mechanistic-empirical pavement design is the resilient modulus of pavement layer materials and subgrade soil. Therefore, a comprehensive laboratory testing program was undertaken in this study to investigate the resilient modulus of coal combustion bottom ash. 117

The objective of this research is to determine the potential of utilizing coal combustion bottom ash in base and subbase course pavement layers and to improve resilient characteristics of subgrade soil. To achieve this goal, the resilient modulus and other engineering properties of coal combustion bottom ash were determined, analyzed, and critically evaluated. Five bottom ash samples from power plants in Wisconsin and Michigan were obtained and subjected to a comprehensive laboratory testing program. The testing program comprised of mechanical analysis, consistency limits, specific gravity, compaction characteristics, and repeated load triaxial test. The testing program provided complete characterization of the bottom ash as a subbase or base course layer material. 2

EXPERIMENTAL STUDY

2.1 Bottom ash source We Energies is responsible for production of more than ¾ million ton of coal ash each year, of which nearly 20% is bottom ash, consistent with the national production numbers (based on 1997 We Energies production). Previous studies have been conducted to determine the chemical composition of the coal ash and the safety associated with its use on other sites. As previously stated, by-products and their respective chemical compositions are determined by the method of firing as well as the actual coal product that is used for the combustion process. The four facilities at the specific locations from which five samples were extracted are described further. The bottom ash samples provided by We Energies are from four of their coal-firing power plants: 1. 2. 3. 4.

Pleasant Prairie Power Plant (PPPP) Valley Power Plant (VAPP) Oak Creek Power Plant (OCPP) Presque Isle Power Plant (PIPP)

Pleasant Prairie Power Plant (PPPP) located in Kenosha County, Wisconsin burns low sub-bituminous coal and is responsible for nearly 40% of We Energies total coal ash production (based on 1997 figures). Valley Power Plant of downtown Milwaukee, Wisconsin produces nearly 60,000 tons of ash from its burning of low sulfur bituminous coal. Oak Creek Power Plant (OCPP) of Wisconsin’s Milwaukee County burns bituminous as well as sub-bituminous coal and produces more than 200,000 tons of coal ash annually (nearly 30% of total production). Presque Isle Power Plant, located in Marquette, Michigan, is split into two groups: Units 1–6 burn a low sulfur bituminous coal and Units 7–9 burn a low sulfur sub-bituminous coal. The chemical components of the five bottom ash samples from the four power plants are presented in Table 1. Table 1. Bottom ash chemical composition based on type of coal burned (Ramme & Tharaniyil 2000).

Compound

Symbol

Bottom ash from bituminous coal, % (mass)

Silicon Dioxide Aluminum Oxide Iron Oxide Calcium Oxide Magnesium Oxide Sodium Oxide Potassium Oxide

SiO2 AL2O3 Fe2O3 CaO MgO Na2O K 2O

61.0 25.4 6.6 1.5 1.0 0.9 0.2

Bottom ash from sub-bituminous coal, % (mass) 46.75 18.76 5.91 17.80 3.96 1.28 0.31

* Mass percentage values shown may vary 2 to 5% from plant to plant.

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The current primary application of We Energies bottom ash is as a light-weight replacement for aggregates in base and subbase course layers of hot mixed asphalt pavement as well as in concrete/masonry products. This applies mainly to the larger particle sizes of the bottom ash that most closely imitate the particle sizes of aggregates generally used. This study focuses on the use of bottom ash while accounting for its entirety. Physical and mechanical properties of bottom ash samples were determined and compared with values for typical subgrade soils used as pavement materials. 2.2 Laboratory tests on bottom ash and subgrade Table 2 presents description of the bottom ash samples used. Subgrade soil samples were from the Marquette Interchange Project in Milwaukee, Wisconsin. The collected samples were subjected to standard laboratory testing procedures to determine physical properties and compaction characteristics. The testing consisted of the following: grain-size distribution (sieve and hydrometer analyses), specific gravity (Gs), and Standard Proctor compaction testing to determine the optimum moisture content (wopt.) and maximum dry unit weight (γdmax) of each material. A repeated load triaxial test was conducted on bottom ash specimens to determine their resilient modulus, following AASHTO T307: Standard Method of Test for Determining the Resilient Modulus of Soils and Aggregate Materials. The test was conducted on compacted soil specimens that were prepared in accordance with the procedure described by AASHTO T 307. The repeated load triaxial test consists of applying a cyclic load on a cylindrical specimen under constant confining pressure (σc) and measuring the axial recoverable strain (εr). The repeated load triaxial test setup is shown in Figure 1. The system consists of a loading Table 2.

General description of bottom ash samples.

Bottom ash source

Description

Pleasant Prairie Power Plant (PPPP) Valley Power Plant (VAPP) Oak Creek Power Plant (OCPP) Presque Isle Power Plant, 7–9 (PIPP)

Medium brown fairly uniform Black, very light weight, fine Light brown with larger aggregate-like clusters Medium to dark brown with full array of light to dark scattered particles Very light weight, light black, few light brown grains

Presque Isle Power Plant, 1–6 (PIPP)

Figure 1.

The repeated load triaxial test setup (Instron 8802 dynamic materials test system).

119

frame with a crosshead mounted hydraulic actuator. A load cell is attached to the actuator to measure the applied load. The soil sample is housed in a triaxial cell where confining pressure is applied. As the actuator applies the repeated load, sample deformation is measured by a set of Linear Variable Differential Transducers (LVDT’s). A data acquisition system records all data during testing. It should be noted that all bottom ash specimens were tested immediately following preparation in order to minimize the effect of any cementitious matter, if present. The reason for this is that the AASHTO T307 is specified for unbound materials and a longer setting time may cause the material to transition toward a bound material. 3

RESULTS AND DISCUSSION

3.1 Physical and compaction properties of bottom ash Table 3 summarizes the results of physical properties and compaction characteristics of the investigated bottom ash samples. These properties consist of particle size distribution, specific gravity, optimum moisture content and maximum dry unit weight. In addition, classification of the bottom ash using the Unified Soil Classification System (USCS) and the AASHTO soil classification system is also presented. The amount of fines (% passing #200 sieve) in the investigated bottom ash samples ranges from 13.2 to 19.1%, which indicates that all bottom ash samples are a coarse-grained material. This is evident from the classification of the samples where all specimens are considered silty sand (SM) by the USCS and granular material (A-1-b and A-2-4) using the AASHTO soil classification system. The particle size distribution curves of the investigated bottom ash samples are shown in Figure 2. Inspection of Figure 2 shows that PIPP 7-9 and OCPP samples have particle size distribution curves possessing a higher percentage of larger particle sizes compared with PPPP, VAPP and PIPP 1-6 samples. In addition, PIPP 7-9 and OCPP Table 3a.

Properties of the investigated bottom ash.

Optimum Passing Specific moisture Maximum Bottom sieve dry unit gravity content ash type #200 (%) Gs Wopt (%) weight (pcf)

Maximum AASHTO dry unit classification & weight group index (kN/m3)

PPPP

19.1

2.43

VAPP

14.0

2.23

OCPP

18.2

2.72

9.24* 15.48* 19.16* 35.73* 6.31

68.11* 68.84* 30.21* 30.28* 82.68

10.71* 10.82* 4.75* 4.76* 13

PIPP 7-9 13.2

2.73

6.29

73.10

11.49

PIPP 1-6 18.8

2.04

43.37

49.38

7.76

A-2-4 (0) granular material A-2-4 (0) granular material A-1-b (0) granular material A-1-b (0) granular material A-2-4 (0) granular material

Unified soil classification system (USCS) Silty sand (SM) Silty sand (SM) Silty sand (SM) Silty sand (SM) Silty sand (SM)

* Bottom ash has a double peak compaction curve. All bottom ash materials are non-plastic. Table 3b. Properties of the investigated bottom ash (continued). Bottom ash

Coefficient of uniformity (Cu)

Coefficient of curvature (Cc)

PPPP VAPP OCPP PIPP 7-9 PIPP 1-6

6.71 4.10 32.01 24.34 4.73

1.24 1.10 0.94 1.24 1.21

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Particle Size (in) 0.1

0.01

0.001

0.0001

1E-005

Percent Finer (%)

100 80 60 40 VAPP OCPP PIPP 7-9 PIPP 1-6 PPPP

20 0 10

1

0.1

0.01

0.001

Particle Size (mm)

Particle size distribution curves of bottom ash samples.

Dry Unit Weight, γd (lb/ft 3)

Figure 2.

OCPP PIPP 1-6 PIPP 7-9 PPPP VAPP

80

60

40

20 0

Figure 3.

10

20 30 Moisture Content (%)

40

50

Compaction curves for bottom ash samples.

30.4

4.78

VAPP Bottom Ash

30.3

4.76

30.2 4.74 30.1 4.72

30 10

Figure 4.

Dry Unit Weight, γd (kN/m3)

Dry Unit Weight, γd (lb/ft 3)

30.5

20

30 Moisture Content (%)

40

50

The compaction curve for VAPP bottom ash.

particle size distribution curves show that these two samples cover a wider range of particle sizes (Cu = 24 and 32, respectively) rather than PPPP, VAPP and PIPP 1-6 samples, which are nearly uniform in their particle size distribution. (Cu = 6.7, 4.1, and 4.7, respectively). Specific gravity of the investigated bottom ash samples varies between 2.04 and 2.73. Bottom ash samples from VAPP, PIPP and PPPP were very light compared with OCPP and PIPP 7-9. The results of the compaction tests on bottom ash samples are depicted in Figures 3 and 4. Test results showed that VAPP bottom ash possesses the lowest dry unit weight that varies near γd = 4.8 kN/m3. OCPP bottom ash showed the highest dry unit weight with approximately γd = 13.0 kN/m3. Examination of the compaction curves showed that the PPPP and VAPP bottom ash have double peak dry unit weight-moisture content relationships. For VAPP and PIPP 1-6 bottom ash samples, the dry unit weight values are very low and the range near the optimum moisture content is large. The maximum dry unit weight for 121

Deviator Stress σd (psi) 2

4

6

Deviator Stress σd (psi)

8 10

2

σc=27.6 kPa

10000

σc=13.8 kPa

8000 6000

40

4000 20 2000

60

σc=27.6 kPa

10000

σc=13.8 kPa

8000 6000

40

4000 20 2000

10 20

40

60

10

80 100

(a) PPPP bottom ash

4

6

2

10000 60

8000 6000

40

4000 σc= 41.4 kPa σc=27.6 kPa σc=13.8 kPa

2000

10 20

40

60

Resilient Modulus, Mr (MPa)

80

Resilient Modulus, Mr (psi)

100

80

10

60

80 100

Deviator Stress σd (psi)

8 10

100

20

40

(b) VAPP bottom ash

Deviator Stress σd (psi) 2

20

Deviator Stress σd (kPa)

Deviator Stress σd (kPa)

4

6

8 10

σc= 41.4 kPa

60

σc=27.6 kPa

10000

σc=13.8 kPa

8000 6000

40

4000 20 2000

Resilient Modulus, Mr (psi)

10

Resilient Modulus, Mr (MPa)

8 10

6

σc= 41.4 kPa

80

Resilient Modulus, Mr (psi)

60

Resilient Modulus, Mr (MPa)

σc= 41.4 kPa

80

10

10

80 100

10

Deviator Stress σd (kPa)

20

40

60

80 100

Deviator Stress σd (kPa)

(c) OCPP bottom ash

Figure 5.

4

100

Resilient Modulus, M r (psi)

Resilient Modulus, Mr (MPa)

100

(d) PIPP 1-6 bottom ash

Repeated load triaxial test results of the investigated bottom ash samples.

PIPP 1-6 is 7.8 kN/m3 and for VAPP is 4.8 kN/m3, which are very low when compared with the maximum dry unit weight of 13.0 kN/m3 for OCPP and 11.5 kN/m3 for PIPP 7-9. These higher values of dry unit weights for OCPP and PIPP 7-9 can be explained by the particle size distribution curves that cover wider ranges and by the specific gravity of the samples. 3.2 Repeated load triaxial test The results of the repeated load triaxial test on bottom ash are shown in Figure 5. The test results of PPPP bottom ash show low resilient modulus values that decrease with a decrease in confining pressure (σ3). For example, at a confining pressure σ3 = 41.4 kPa, the resilient modulus for the PPPP bottom ash varies between 19.14 and 20.16 MPa. With a confining pressure of σ3 = 27.6 kPa the resilient modulus for the PPPP bottom ash varies between 14.94 and 18.59 MPa, and for the lowest confining pressure of the test procedure σ3 = 13.8 kPa, the resilient modulus varies between 13.20 and 17.83 MPa. In each case, as the deviatoric stress increases while maintaining a constant confining pressure, the bottom ash shows a trend indicative of hardening. The results of repeated load triaxial testing on PPPP bottom ash are presented in Figure 5a. Repeated load triaxial testing of VAPP bottom ash revealed that VAPP material provides the lowest resilient modulus values of all bottom ash investigated in this study as shown in Figure 5b. The results of repeated load triaxial testing on OCPP bottom ash are presented in Figure 5c. The OCPP bottom ash shows higher resilient modulus values compared with PPPP, VAPP, and also PIPP 1-6 for a confining pressure σ3 = 13.8 kPa. For a confining pressure σ3 = 41.4 kPa, the resilient modulus varies between 61.44 MPa at a deviator stress of σd = 13.1 kPa and 50.72 MPa at σd = 63.2 kPa. The bottom ash shows softening as the deviator stress increases when the confining pressure σ3 = 41.4 kPa and shows hardening at lower confining pressures. These resilient modulus test results are generally considered to be moderate when compared with the other investigated bottom ash samples. Resilient modulus values of PIPP 1-6 bottom ash are depicted in Figure 5d. All bottom ash samples were prepared at the optimum moisture content and maximum dry unit weight of the material determined by compaction tests and listed in Table 3. For the bottom ash samples resulting in a double peak compaction curve, the lower moisture content of the two peaks was chosen for preparation of specimens for repeated load triaxial tests. 122

Deviator Stress σd (psi) 2

4

6

8 10

100 10000 60

8000 6000

40

4000 20

σc=41.4 kPa σc=27.6 kPa σc=13.8 kPa

Resilient Modulus, Mr (psi)

Resilient Modulus, Mr (MPa)

80

2000

10 10

20

40

60

80 100

Deviator Stress σd (kPa)

Figure 6.

Repeated load triaxial test results on subgrade soil.

3.3 Subgrade soil Resilient modulus and other properties were also determined for a subgrade soil to make comparisons with bottom ash test results. Soil consists of about 60% passing sieve #200 with non-plastic fines. The soil was classified as sandy silt (ML) according to USCS and silty soil (A-4) according to the AASHTO soil classification with a GI = 0. Standard Proctor test results show that the average maximum dry unit weight γdmax = 18.7 kN/m3 and the corresponding average optimum moisture content wopt. = 10.5%. The results of the repeated load triaxial test on this “typical” subgrade soil are shown in Figure 6. Test results show that the resilient modulus of subgrade soil increases with the increase in the confining pressure. Also, the resilient modulus decreases with the increase in the deviator stress. It should be noted that the resilient modulus of OCPP bottom ash (see Figure 5c) is comparable to the resilient modulus of this typical subgrade soil, which was obtained from the site of the Marquette interchange project in downtown Milwaukee, Wisconsin. The other investigated bottom ash samples exhibited lower resilient modulus values compared with the subgrade soil. This study provided preliminary results on the resilient modulus of bottom ash and demonstrated that the bottom ash characteristics are very important factors. Since there are encouraging results regarding the comparable resilient modulus values between bottom ash and subgrade soil, further research is needed to characterize the resilient modulus of bottomash soil mixtures and bottom ash-soil-fly ash mixture. 4

CONCLUSIONS

This paper presented an evaluation of the characteristics of the coal combustion bottom ash for potential utilization in pavement construction materials. A comprehensive laboratory testing program was undertaken to evaluate the physical properties, compaction characteristics, and resilient modulus of bottom ash, which was obtained from power plants in Wisconsin and Michigan. Based on test results, the following conclusions were reached: 1. There is a wide spectrum of bottom ash properties pertaining to specific gravity and unit weight; in addition, the investigated bottom ash samples were classified as granular material. 2. Repeated load triaxial test results on bottom ash (at maximum dry unit weight and optimum moisture content) demonstrated that the resilient modulus values of bottom ash vary depending on the physical properties and unit weight of the bottom ash. For four bottom ash types, the resilient modulus values were low compared with typical subgrade soils, while for one type the resilient modulus was comparable to/higher than that of typical subgrade soil. 123

This study provided preliminary results on the resilient modulus of bottom ash and demonstrated that the bottom ash characteristics are very important factors. Since there are encouraging results regarding the comparable resilient modulus values between bottom ash and subgrade soil, further research is needed to characterize the resilient modulus of bottomash soil mixtures and bottom ash-soil-fly ash mixture. ACKNOWLEDGEMENT The authors would like to acknowledge the help and support of Dr. Bruce Ramme and WeEnergies for this research. REFERENCES Abichou, T., Edil, T.B., Benson, C.H. and Bahia, H. Beneficial Use of Foundry By-Products in Highway Construction. GeoTrans—Geotechnical Engineering for Transportation Projects, GSP No. 126, 2004, pp. 715–722. Arm, M. Mechanical Properties of Residues as Unbound Road Materials—experimental test on MSWI bottom ash, crushed concrete and blast furnace slag, Swedish Geotechnical Institute Report No. 64, Stockholm, 2003. Averitt, P. Coal Resources of the United States, January 1, 1974. U.S. Geological Survey. U.S.G.S. Bulletin 1412. U.S. Department of Interior. 1974. Coal Ash Utilization: Fly Ash, Bottom Ash and Slag, Pollution Technology Review No. 48, New Jersey, 1978. “Combustion,” in: Chemical Engineering Handbook, Perry, J.H. et al., eds. New York, McGraw-Hill, 1950. Edil, T.B., Benson, C.H., Bin-Shafique, M.S., Tanyu, B.F., Kim, W.H. and Senol, A. Field Evaluation of Construction Alternatives for Roadways over Soft Subgrade. In Transportation Research Record: Journal of the Transportation Research Board, No. 1786, TRB, National Research Council, Washington, D.C., 2002, pp. 36–48. Huang, W.H. and Lovell, C.W. Bottom Ash as Embankment Material. Geotechnics of Waste Fills, ASTM STP 1070, 1990, pp. 71–85. Kayabah, K. and Bulus, G. The usability of bottom ash as an engineering material when amended with different matrices. Engineering Geology, No. 56, 2000, pp. 296–303. Kim, B., Prezzi, M. and Salgado, R. Geotechnical Properties of Fly and Bottom Ash Mixtures for Use in Highway Embankments. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 131, No. 7, 2005, pp. 914–924. Kumar, S. and Stewart, J. Evaluation of Illinois Pulverized Coal Combustion Dry Bottom Ash for Use in Geotechnical Engineering Applications. J. Energy Engineering, Vol. 129, No. 2, pp. 42–55. Ramme, B.W. and Tharaniyil, M.P. Coal Combustion Products Utilization Handbook, TekDoc-Technical Documentation Inc., Wisconsin, 2000. Seals, R.K., Moulton, L.K. and Ruth, B.E. Bottom Ash: An Engineering Material. Journal of Soil Mechanics and Foundations Division, Vol. 98, No. 4, 1972, pp. 311–325. Senol, A., Bin-Shafique, M.S., Edil, T.B. and Benson, C.H. Use of Class C Fly Ash For Stabilization of Soft Subgrade. Fifth International Congress on Advances in Civil Engineering, Instanbul Technical University, Istanbul, Turkey, 2002. Steam-Electric Plant Air and Water Quality Control Data, Federal Power Commission. Publication No. FPC-S-229. Washington, D.C. Feb. 1973. Surprenant, N., Hall, R., Slater, S., Suza, T., Sussman, M. and Young, C. Preliminary Environmental Assessment of Conventional Combustion Systems. Vol. I. GCA Corporation, Bedford, Massachusetts. Publication No. GCA-TR-75-26-G. Environmental Protection Agency. August 1975. p. 264. Tanyu, B.F., Kim, W.H., Edil, T.B. and Benson, C.H. Development of Methodology to Include Structural Contribution of Alternative Working Platforms in Pavement Structure. In Transportation Research Record: Journal of the Transportation Research Board, No. 1936, TRB, National Research Council, Washington, D.C., 2005, pp. 70–77. Titi, H.H., Elias, M.B. and Helwany, S. Determination of Typical Resilient Modulus Values for Selected Soils in Wisconsin, Report No. CEM-06-GT01. Wisconsin Department of Transportation. 2004.

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Precision triaxial equipment for the evaluation of the elastic behavior of soils N. Araújo & A. Gomes Correia Minho University, Guimarães, Portugal

ABSTRACT: Samples of a sandy soil reconstituted by Proctor compaction were investigated under different isotropic and anisotropic stress paths for different initial stress states in the p-q space using a triaxial apparatus developed for this purpose. The equipment uses a triaxial cell with sample instrumentation for accurate measurements of the stress and strain states. The tendencies of the limit of the elastic domain were analyzed. Several initial stress states and stress paths were investigate in order to quantify key tendencies. Results show that the limit of the elastic domain of the studied soil depends on the initial stress state and on the applied stress path.

1

INTRODUCTION

Even though geomaterials are widely used, little attention has been paid to their mechanical behaviour at low strain levels. The physical and mechanical properties of geomaterials must be efficiently controlled in cases such as the construction of dams, embankments, and foundations. According to Vinale et al. (1999), even if high strain levels are reached during construction, the precise measurement of low strains must be performed to correctly evaluate the stress state. Studies performed by Vinale et al. (1999) on silty sand from the El-Infiernillo Dam, with a water content of 11.4%, demonstrated that the use of a secant modulus associated with a deformation level of 1% caused an overestimation of field settlements, and the need to work with lower strain levels. According to Jardine et al. (1991), soil behaviour can be divided into 4 domains, with the first characterized by linear elastic behaviour until the surface Y1 is reached (see Figure 1a), i.e., until strain level εY1 is reached (corresponding to the constant value in the secant modulus degradation curve—see Figure 1b). The strain level necessary to reach surface Y1 is usually about 10–6 to 10–5. The importance attributed by the geotechnical community to the small strain domain (behaviour inside surface Y1) is because it allows a better prediction of foundation settlements under vertical loads, allows the modifications of traditional empirical testing to more scientific ones, both in the laboratory and in situ, increases the importance of geophysical testing, and allows the evolution of simplified models to more realistic ones by including new relevant factors (Gomes Correia, 2004a). To correctly evaluate the first domain (surface Y1), the errors induced by the laboratory techniques must be reduced. Gomes Correia (1985, 2004b) and Burland (1989) verified that for strain levels less than 0.1%, the traditional external instrumentation used in triaxial tests underestimates the real soil stiffness. For that reason, it is necessary to use local instrumentation in triaxial tests (see Figure 2). Errors induced by external instrumentation are due to bending of the sample, deformability of the testing system, adjustments in the triaxial chamber, and rotation/confining of the sample near the top and base (Jardine et al., 1984; Goto et al., 1991).

125

Figure 1.

a) Domain surface and b) secant modulus degradation curve (Jardine 1992).

Figure 2. Influence of instrumentation in measurements using external instrumentation (solid line) and local instrumentation (dashed line) (Gomes Correia, 1985).

2

INSTRUMENTATION TECHNIQUE

2.1 Transducer selection As already discussed, the use of external instrumentation is not compatible with the evaluation of the elastic domain. This task demands the use of local instrumentation able to record strain levels as small as 10–6. Several types of transducers can be used (Gomes Correia et al., 2006), including piezoelectric transducers (bender elements), Hall Effect transducers, linear variable displacement transducers (LVDTs), and local deformation transducers (LDTs). Local instrumentation was first developed in the early 1980s, and at that time was a challenge for geotechnical laboratories. In an initial study, Burland & Symes (1982) were able to record strains as low as 10–5 using four electrolytic transducers. Other authors have used other techniques with similar results. Gomes Correia (1985) used miniature LVDTs and proximity sensors, Clayton et al. (1989) used Hall Effect transducers, and Gomes Correia & Gillet (1993) used LVDTs in a large triaxial chamber. At the Geotechnical Engineering Institute of Industrials Sciences in Tokyo University, Satoshi Goto developed a simple transducer designed for use as a local deformation transducer able to record strains from 10–6 to 10–2 (Goto et al., 1991). This transducer consists of a thin, long, and flexible strip of phosphor bronze, with a Wheatstone bridge in the middle. The advantages of this transducer are its simplicity, low cost, low weight, insensitivity to temperature (if constructed using a full bridge), and the ability to use it in water (Gomes Correia et al., 2006; Goto et al., 1991). Hall effect transducers provide insufficient resolution and high sensitivity to electric noise and temperature, while LVDTs are difficult to attach to the sample due to their significant weight, and piezoelectric transducers have difficulties in measurement and interpretation, namely with time and distance between waves (Gomes Correia et al., 2006). For the proposed evaluation of the elastic domain, and considering the prior experiments, it was decided to apply local instrumentation in a triaxial chamber existing at Minho University. The use of LDTs, originally developed by Goto et al. (1991) and able 126

to detect strain increments of 10–6, was adopted. All the needed transducers were constructed in the Civil Engineering Laboratory at the Minho University. One disadvantage of this technique is the small deformation field, which according to Hoque et al. (1997) should not be greater than 2%. Hoque et al. (1997) performed several tests to confirm the long term stability, hysteresis, and durability under pressurized submersion. Only the glue used was not tested. The results presented by this author were satisfactory and allow the confident use of this technique without additional testing. 2.2 Radial instrumentation The radial instrumentation system was developed in three phases. In order to record radial deformation, it becomes necessary to create a system able to record this deformation in classical triaxial chambers, with little space between the sample and the chamber wall. Classical triaxial chambers use water as a medium to apply the confining pressure to the sample so that volume change could be measured through the flow in/out of the chamber. This system was eliminated since it is not possible to measure small strain with it. In addition, the use of compressed air makes testing much easier, and the purchase of automatic pneumatic systems are less expensive than those using water. Thus, it becomes necessary to develop a system able to record the radial deformation by taking advantage of the good resolution of LDTs. First, since Goto et al. (1991) used half bridge LDTs for radial instrumentation in prismatic samples, changes were introduced in order to obtain the best sensor resolution. This was considered as a starting point for what full bridge transducers should be. In order to do this, the strip width was enlarged to 4 mm to allow the application of 2 gauges to each strip side. This increase in strip width induces greater forces in the LDT’s pseudo-articulation. For that reason, and also due to the fact that the strip length was small (only 75 mm), the strip thickness was reduced to 0.2 mm. Using this combination, the recommendations of Goto et al. (1991) were accomplished. Secondly, two solutions were studied: the use of an articulate ring (similar to the one used in Hall Effect transducers) in contact with the sample at two opposite points. The second alternative was the use of a belt in which a LDT measured the variation in the sample perimeter. This last option was adopted since it requires less space between the sample and the chamber, it weighs less, the measuring perimeter is more reliable than measuring diameter, and the outputs are increased by a factor of π. The belt (see Figure 3) was constructed with inexpensive and easy to find materials. This developed system presents pseudo-articulations adjustable to the LDT’s initial position (see Figure 3c). However, these adjustments can only be performed during calibration of the system. In fact, the relation between the LDT measurement and the sample diameter is not linear. The relation (Equation 1) could not be calculated in a computer code, so an approximation to a 3º degree polynomial was used. This approximation presents the best adjustment of a group of polynomial (degree 1 to 3), exponential, power and logarithmic approximations.

Figure 3. a) Belt radial system components, b) belt radial system mounted in sample and c) LDT installed in belt radial system.

127

a)

Figure 4. scheme.

b)

a) Belt radial system scheme (Araújo 2007) and b) direct radial measurement system

C = D × − arcsin

B 2

(1)

D +A 2

During the test campaign, A was set equal to 9 mm, C equal to 259 mm, and D was obtained as a function of B (value presented by the radial LDT). The meanings of the variables are indicated in Figure 4. Some limitations in this developed radial system were found during testing. The non-linear relationship between diameter and LDT reading requires the use of an approximate relation that induces a small error and does not allow new corrections in the LDT pseudo-articulations. Moreover, adjustments between the latex membrane and the teflon strip induce unexpected behavior that interferes with the radial strain measurements. Due to this fact, this system had to be improved. Since good measurements were obtained with the axial system, the idea of measuring radial deformation using the same principle was adopted. The problem consists of the fact that measurements had to be made on a non-planar surface. With the schemes presented in Figures 4b and 8b, this problem was overcome and a linear relationship between the horizontal LDT measurement and the diameter was easily defined (Equation 2). It should be pointed out that the relation was obtained assuming that α remains constant. The use of the direct radial system can be questioned since the variation of sample section is obtained by means of the relative displacements of only two points. However, even if this problematic is not present in the belt system, since it captures the influence of the entire sample, it should be note that the extra confining and system adjustments are not acceptable in small strain domain testing, and for that the use of direct measures should be employed. The way to control measuring accuracy is to use two horizontal LDTs, being this a future improvement. ⎛ B ⎞ B D = 2⋅A⋅⎜ − 1⎟ + Dinitial ⋅ Binitial ⎝ Binitial ⎠

(2)

2.3 Axial instrumentation Axial deformation was measured with LDTs constructed in the Civil Engineering Department at Minho University according to recommendations made by Goto et al. (1991). The length of the LDTs was the only parameter chosen. In these transducers, as in the radial ones, waterproofing was not applied in a first phase in order to increase the flexibility and reduce weight. However, this protection was actually applied since it allows easy handling of the LDTs. 128

3

ACQUISITION AND CONTROL SYSTEM

3.1 Acquisition As a starting point in assembling the acquisition system, characteristics presented by Hoque et al. (1997) were considered. In this author’s system, LDTs were excited with 2 VDC, with the output amplified through Kyowa DPM-600 amplifiers with an amplification factor of 10. The analogue to digital conversion was performed using a 12 bit AD converter in an interval of ±5 V, corresponding to a resolution of 2.442 mV. The system developed at Minho University used a 14 bit AD converter from National Instruments and 8 signal amplifiers (model SG-30 16 CR-G) connected to a Wheatstone bridge. These components were chosen for their low price and good quality. The AD converter is also a DA converter since it has 2 analogue outputs and 12 digital outputs that allow the control of proportional servo-valves or precise step motors. All signals were amplified for an output voltage interval of ±10 VDC. Attached to that it is a 14 bit converter with a resolution equal to 1.221 mV. All LDTs were excited with 3 VDC, despite the fact that it causes a current of 25 mA, which is slightly greater than the maximum recommended by the amplifier’s manufacturer (20 mA). This voltage level was used so that the output of the LDTs reaches the amplifier’s maximum interval. As indicated by Goto et al. (1991), an analogue filter can be used to reduce the noise of the LDTs, even if a slight phase in the signal is produced. Since the testing was performed at a low rate (never greater than 10 kPa per minute), its influence was negligible. 3.2 Control system In an initial phase, tests were performed in a classical triaxial chamber, with manual control of the chamber pressure through a mechanical pneumatic valve. The axial load was applied through a pneumatic cylinder with a second mechanical pneumatic valve. This phase, with obvious limitations due to operator control, was used to evaluate the potential of a pneumatic system. The results were satisfactory and provide excellent guidelines for the development of the automatic control system. The automatic control system was initially developed by Araújo (2007) and was improved in this work. Araújo (2007) took advantage of a stress path chamber in the Civil Engineering Laboratory at Minho University, which already had a low friction pneumatic piston to apply the axial load. In order to control the air pressure, a proportional pneumatic-valve search was completed. Tests were performed with a valve from FESTO (model VPPE) with a working pressure range of 600 kPa. However, it was realized that with this open loop valve a resolution less than 15 kPa could never be achieved. Since the mechanical pneumatic-valves provide excellent resolution (0.1 kPa for a full pressure range of 500 kPa), the automation of these elements was performed by Araújo (2007) using accurate step-motors. For this, a commercial model RS-Amidata (reference number 440–458; see Figure 5a) was chosen. An electronic board (RS-Amidata, reference number 240–7920; see Figure 5b) provided control of the step-motor. In order to improve the step precision, a reduction system was also used (see Figure 5c).

Figure 5. a) Precise step-motor, b) electronic board to digitally control the step-motors and c) reduction system to reduce step angle.

129

Figure 6. Available stress paths using one mechanical pneumatic-valves and one proportional pneumatic-valve.

With this system, Araújo (2007) used distinct paths to check the system efficiency. Control software was developed by the author using the LabView language to efficiently control the stress paths (deviatoric and isotropic stresses). For high pressure values, a reduction in precision was detected but it did not compromise the efficiency of the system. However, a severe limitation was detected when the applied stress path involved the simultaneous variations in average and deviatoric stress. This limitation was due to adjustments in the reduction system and the slow velocity of the system. The system was able to maintain one of the variables at a constant level (deviatoric or average stress) while the second was used to produce the cyclic test. In order to overcome this limitation, a proportional servo-valve had to be used. In this work, a new search for a high precision proportional pneumatic-valve was performed. A commercial valve from Proportion-Air, Incorporated, was chosen as a solution. It consists of a closed-loop proportional pneumatic-valve with a typical resolution of ±0.02% for a full range greater than 600 kPa. This proportional pneumatic-valve was used to control the deviatoric stress, as the step-motor maintained the average stress. This combination was used since the automated mechanical pneumatic-valves solution causes less oscillation when applying cyclic loading and the proportional pneumatic-valve solution has excellent behavior when rapid reversals in air pressure are needed. The control signal of the proportional pneumatic-valve was computed from the value applied by the step-motor so that the maximum precision in control was achieved. This improvement required a new version of the controlling software. Several distinct stress paths were programmed in order to evaluate the system efficiency. As shown in Figure 6, all paths can now be applied. The introduction of the close loop pneumatic valve (with a precision of 0.02%) allows a global system precision of 0.8 kPa, independently of the applied stress path. It should be mentioned that all tests were performed at low velocities which may be seen as the only limitation. However, this limitation could be overcome with the replacement of the mechanical pneumatic-valves by a second proportional pneumatic-valve. Note that this change was not introduced since the slow velocity improves the precision in the applied stress path, and the mechanical pneumatic-valves (as already described) allow less oscillation during cyclic variations in air pressure. 4

EXPERIMENTAL PROGRAM

4.1 Study soil and sample construction This work was intended to study the behaviour of Perafita sand in the small strain domain. This silty sand has already been studied in a bilateral cooperative project between France and Portugal, in a first phase through “Instituto Superior Técnico” (Technical University 130

Figure 7.

Grain size distribution studies performed in Perafita sand.

Figure 8.

a) Instrumentation system and b) improved direct radial measuring system (Araújo, 2007).

of Lisbon) and in a second phase through Minho University, with “Ecole Centrale Paris” (ECPMSSMat) (Hadiwardoyo, 2002; Fleureau et al., 2002; Ferreira, 2003). Ferreira (2003) classified the soil as non-plastic with a uniformity coefficient of 17 and a curvature coefficient of 1.85. The solid particle density was equal to 2.69. The compaction parameters relative to the modified Proctor test are (Fleureau et al., 2002): optimum water content of 13.2%, dry volumetric mass of 1890 kg/m3, and void ratio of 0.42. In Figure 7, it can be see that a high percentage of small particles is present, when compared with the grain size distribution curve from previous studies. The grain size analysis presented by Araújo (2007) was performed after removal of particles retained in an ASTM #4 sieve in order to remove all gravel particles. In this work, all samples were constructed using the following state conditions: natural volumetric weight of 18.9 kN/m3, void ratio of 0.56, degree of saturation of 0.615, and water content of 13%. The solid particle density was assumed to be constant and equal to 2.69. This lower volumetric weight (when compared with those presented by Fleureau et al., 2002) was assumed to represent some in situ conditions, with volumetric weight and water content lower than those obtained with the modified Proctor test. Sample compaction was carried out in a 100 mm diameter by 200 mm height mould. In order to guarantee a close constant density in the compacted specimen, the compaction was performed into 5 layers of 4 cm each. Using a mechanical press, and by knowing the weight of the material in each layer, it was possible to compress the soil until the desired layer thickness was reached. 131

Figure 9.

Evaluation of the elastic domain.

Figure 10.

Increments that induced elastic domain limits.

4.2 Testing program Results were obtained during the evolution of the testing system in its 3 distinct phases. During the first phase, without radial instrumentation and manual control of the applied stress paths, tests were performed on 3 samples (Araújo, 2007). In this phase, since no automatic control was still available, small corrections were not made and only 2 distinct stress paths could be applied (isolated variations in the deviatoric stress or in the average stress). It was also not possible to execute a large number of cycles. As referred previously, this initial system was improved by Araújo (2007) with a belt radial system (see Figure 8a) and an automatic control system. With this improved system, human limitations in testing were removed, precision was improved, and the applied stresses were efficiently controlled. This system was originally developed to allow the application of all stress paths. However, when the stress path required synchronization in the variation of the average and deviatoric stresses, the control was not acceptable. Nevertheless, it became possible to improve the precision in the application of the second path and the execution of a larger number of cycles. Testing was performed during this phase on 5 samples. In the last improving phase of the system, the introduction of an improved radial measuring system (see Figure 8b) and the use of a high precision proportional pneumatic-valve allowed the correct evaluation of the volumetric strain and the application of any stress path. Testing was performed on 2 samples with a synchronized stress path (slope equal to 0.5 in q-p space) efficiently controlled on 4 distinct stress paths. Figure 9 clarifies the procedure used to obtain the elastic domain limit. For the case of an unloading/loading cycle with an initial stress level of (p0, q0) = (66.7 kPa, 50 kPa) and a slope path equal to 0.5, an amplitude of 7 kPa (in average pressure variation) induced an elastic but hysteretic behaviour. With a cycle of 5 kPa, the behaviour was then linear. 132

The control system was programmed to apply, for each distinct stress path (deviatoric, isotropic, or anisotropic stress path), a cyclic loading increment of 2 kPa until hysteretic behaviour was detected. Each increment was applied for 10 cycles. 4.3 Analysis of the results During phases 1 and 2, since the radial system was not completely accurate, the evaluation of the elastic domain was performed with axial extension εa. During phase 3, since good behaviour was recorded in the radial measuring system, the volumetric strain εv was used. Nevertheless, since all tests were performed in the elastic domain, a linear variation of εa, as well as in the radial extension εr, will induce a linear variation in εv. All available results obtained for the Perafita sand are presented in Figure 10. For each initial stress state, the applied path and the corresponding limit linear elastic domain increment is represented. In this figure, it is possible to see that the results obtained in phase 1 agree well with the results from phase 2. This validated the use of the manual testing procedure. This agreement was expected due to the lack of influence of the loading velocity in the elastic domain. Analyses of the results presented in Figure 10 were divided into three distinct groups in order to more easily detect major tendencies. As a first approach, several paths applied from the same initial stress state were analyzed. Then, the influence of the average stress and deviatoric stress on the path increment amplitude was evaluated. Finally, the simultaneous influence of average stress, deviatoric stress, and initial stress state was analyzed. The overall results show that the definition of the elastic domain is not possible without the simultaneous consideration of the initial stress state and the direction of the applied stress path. It was observed that the average stress presents a much higher influence than the deviatoric stress in the elastic limit of the material. 5

CONCLUSIONS

A precision triaxial equipment was developed and described for the evaluation of the elastic domain of soil behaviour. The results obtained with this equipment allowed the conclusion that the limit of the elastic domain of the studied soil depends on the initial stress state and also on the applied stress path. The initial average stress has a greater influence than the initial deviatoric stress. In addition, increments of the applied stress induce larger elastic domains in all the paths applied in this study. These results are of great practical interest, namely from the perspective of developing a constitutive law for the studied material. ACKNOWLEDGMENTS This work was financed by the Portuguese Foundation for Science and Technology (FCT) under the POCI/ECM/611/2004 project entitled “Soil-rail track interaction for high speed trains”. The writers wish to thank FCT for its financial support and Doctor Jaime Fonseca and Eng. Carlos Palha for their contributions. REFERENCES Araújo, N. 2007. Development of a precision triaxial equipment for the evaluation of the elastic limit of geomaterials. PAPCC, Minho University, Portugal (in Portuguese). Burland, J. & Symes, M. 1982. A simple axial displacement gauge for use in the triaxial apparatus. Géotechnique 32: 62–65. Burland, J. 1989. Small is beautiful: the stiffness of soils at small strains. Canadian Geotechnical Journal 26: 499–516.

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Clayton, C., Khatrush, S., Bica, A. & Siddique, A. 1989. The use of Hall Effect semiconductor in geotechnical instrumentation. Geotechnical Testing Journal 12: 69–76. Ferreira, S. 2003. The influence of non saturation and of grain size distribution on the characteristics of deformability of a granite aggregate. Master’s Thesis, Instituto Superior Técnico, Portugal (in Portuguese). Fleureau, J., Hadiwardoyo, S., Dufour-Laridan, E., Gomes Correia, A. & Langlois, V. 2002. “Influence of suction on the dynamic properties of a silty sand”. In 8 Congresso Nacional de Geotecnia, Lisbon, 15–18 April. Gomes Correia, A. 1985. “Contribution a l’étude mécanique des sols soumis à des chargements cycliques”. PhD Thesis, Ecole National des Ponts et Chaussées, Paris. Gomes Correia, A. & Gillet, S. 1993. A large triaxial test apparatus for study of granular materials under repeated loading used at LNEC. In European Symposium of Flexible Pavements EUROFLEX93, Lisbon, 20–22 September, A.A. Balkema, Rotterdam, Netherlands. Gomes Correia, A. 2004a. Deformability characteristics of soils interesting the serviceability of structures. Revista da Sociedade Portuguesa de Geotecnia 100: 130–122 (in Portuguese). Gomes Correia, A. 2004b. Evaluation of mechanical properties of unbound granular materials for pavements and rail tracks, keynote lecture. Pavement and Railway Design and Construction (Gomes Correia & Loizos, eds.), Millpress, 35–60. Gomes Correia, A., Reis Ferreira, S. & Araújo, N. 2006. Precision triaxial tests for the evaluation of the deformability characteristics. In 10th Congresso Nacional de Geotecnia, Lisbon, 22–25 May, Sociedade Portuguesa de Geotecnia, Portugal (in Portuguese). Goto, S., Tatsuoka, F., Shibuya, S., Kim, Y.-S. & Sato, T. 1991. A simple gauge for local small strain measurements in the laboratory. Soils and Foundations 31: 169–180. Hadiwardoyo, S. 2002. Characterization of granular materials from very small to large strain. PhD Thesis, Ecole Centrale Paris, Paris. Hoque, E., Sato, T. & Tatsuoka, F. 1997. Performance evaluation of ldt’s for use in triaxial tests. Geotechnical Testing Journal 20: 149–167. Jardine, R.J., Symes, M. & Burland, J. 1984. The measurements of soil stiffness in the triaxial apparatus. Géotechnique 34: 323–240. Jardine, R.J., John, H.D., Hight, D.W. & Potts, D.M. 1991. Some practical applications of a non-linear ground model. In Proceedings of 10th European Conference on Soil Mechanics and Foundation Engineering,, Florence, 27–30 May. Jardine, R.J. 1992. Some observations on the kinematic nature of soil stiffness. Soils and Foundations 32(2): 111–124. Vinale, F., Onofrio, A., Mancuso, C., Magistris, F.S. & Tatsuoka, F. 1999. The pre-failure behavior of soils as construction material. In II International Symposium on Pre-failure Deformation Characteristics of Geomaterials, Torino, 28–30 September.

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Granular materials

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A performance study of different curing materials applied to soil-Portland cement base course cure R.M. Fortes & J.V. Merighi Department of Civil Engineering, Mackenzie Presbyterian University, São Paulo, Brazil

ABSTRACT: In 2007 an agreement was signed between “Departamento de Estradas de Rodagem de São Paulo—DER-SP” (São Paulo DOT) and Mackenzie Presbyterian University (UPM) for construction of a test facility. São Paulo State Test Track is being constructed to improve research in all areas related to highway without any cost to DER-SP or UPM. In Sao Paulo, State has more than 10 thousand kilometers of soil-cement base course. Part of these roads was made in the 70’s and after 30 years, the base course is almost intact. If some rehabilitation of the road is needed, it occurs in the last layer. However, when this technology has been used, the DER-SP has observed that the cure of this material is essential for its performance, mainly to avoid the cracking appearance. This paper reports a performance study of the different curing materials and when and how to apply curing over soil-cement courses. 1

INTRODUCTION

Brazil is located in a tropical area. The upper layer of the soils is often a red to yellow coloration denominated as lateritic soils. These natural materials are rich in aluminum hydroxides and ferric hydrates that result in an elevated mechanic resistance. Associated with this property, some variations present good behavior when in presence of water (Fortes & Merighi 2003). In the State of São Paulo, the low traffic volume roads extend 12,000 km. About 6,000 km of that use lateritic fine sand soil as base material and in the other 50% is used the soil-cement course. Many of these roads, after 30 years still show excellent performance. The traffic in these roads reaches more than two thousand vehicles per day and 30% of that is bus and trucks. Considering this scenery and the total cost involved in the road construction, there are encouragements to use the soil-cement technology in its respective base. Nowadays, the São Paulo Governor is starting the construction of more than 5 thousand kilometers of rural roads to low traffic volume. Stabilization of soil is a process that transforms unstable soils into structurally sound construction foundations by modifying subgrade soils, subbase and base materials. The primary addictions used for the stabilization and to improve the behavior of the materials are: lime, fly ash, and Portland cement. However, cement has demonstrated to be effective in stabilizing a wide variety of soils, including granular materials, silts, and clays; byproducts such as slag and fly ash; and waste materials such as pulverized bituminous pavements and crushed concrete (Little et al. 1999). The standard practice of soil-cement course recommends that immediately after finishing, the construction shall take a protection to prevent evaporation and loss of water from the layer. This process is denominated curing and can be defined as a practice to reduce moisture loss during the early hardening period. The process allows soil-cement properties to develop and prevents damage as a result of drying during the early ages of the layer. Traditionally, the Brazilian specifications for road recommend promoting an adequate cement hydration of the Portland cement, an application of bituminous material; in particular medium curing cut-back asphalt or emulsified asphalt, in way to protect against the evaporation and loss of water from the layer, during at least for 7 days. 137

Aiming to study the real behavior of soil-cement mixtures in contact with cut-back asphalt and to verify the performance of another kind of products in terms of protection or loss water in soils-cement mix was developed a preliminary research in laboratory and after that was applied in the field test. 2

BRIEF LITERATURE REVIEW

Soil-cement is the soil stabilized by addition of cement and water, acquiring compressive strength presenting after seven days of at least 2.1 MPa (21 kgf/cm2) (DNER 1997a). Since 1915, more than 100,000 miles of equivalent 7.5 m wide pavement bases have been constructed using cement-stabilized soils in USA (Little et al. 1999). The first use of this technology was in Spain around 1964. In the decades of 70 and 80 this technology was almost not used. In 1990 this situation was reverted, considering the management of highways net, the technology of the soil-cement became for the regional authorities the preferential solution (Jofré & Diaz-Minguela 2005). Historically, the soil-cement technology was introduced in Brazil in 1936 and at São Paulo State was built more than 10 thousand kilometers using the soil-cement base. The first construction using this technology for base course was in 1941 in the Petrolina airport (ISAÍA 2007). Senço (1997) affirmed that the soil-cement experience in SP DOT happened in the 40’s when motivated by state development starting the construction of new roads in region without granular bases courses (stones). Until today, this technology has been used. The major performance problems found with stabilized materials are associated to shrinkage cracking. For Halsted (2006), wide shrinkage cracks can result in moisture infiltration into the sub grade causing pumping and loss of support for the stabilized layer above; faulting of the stabilized layer due the loss of sub grade support; moisture-induced deterioration of the stabilized layer at the joint, causing a widening of the crack and joint raveling or loss of aggregate interlock at the crack. The Portland Cement Association (PCA 1995 (a)) recommends in the Soil-Cement Construction Handbook that for adequate cement hydration, a moisture-retaining cover have been placed over the soil-cement soon after completion to retain this moisture. Recommend too that the material for curing be bituminous material or other material such as waterproof paper or plastic sheets, wet straw or sand, fog-type water spray, and wet burlap. It also explains that the types of bituminous materials most used are RC-250, MC-250, RT-5, and emulsified asphalt SS-1. In another document the PCA recommends that curing compounds: emulsified asphalt or liquid membrane-forming compounds for curing concrete (PCA 1995b). Nowadays we have a lot of new products used in curing concrete and part of them can be used alternatively as curing product in soil-cement layer. The DNER (1997b) recommends applying a wet grass, bituminous materials or other material in way to protect against the evaporation and loss of water from the layer, during 7 days. The São Paulo DOT recommends the same time for curing and the application of rapid cure emulsified asphalt. The document ET-40 from Brazilian Portland Cement Association (ABCP 2000) recommends the cure, to protect the layer against the fast loss of humidity, during at least 7 days. The document still recommends three options of materials for the cure: a) the emulsified asphalt, that does not have to be considered as tack coat; b) a layer of humid soil or sand, with at least 5 cm of thickness or still; c) the covering with a straw layer or grass of, at least 10 cm of thickness. 3

SCOPE OF RESEARCH

The standard practice of soil-cement base recommends that immediately after finishing the construction shall a protection be taken to prevent evaporation and loss of water from the layer. This process is denominated curing and it can be defined as a practice to reduce moisture loss during the early hardening period. The process allows soil-cement 138

properties to develop and prevents damage as a result of drying during the early ages of the layer. The cracking in a cement treated material is caused by volume change (shrinkage). This process can occur for a number of reasons, such as cement hydration, drying and temperature change. The greatest amount of shrinkage occurs early in the life of the pavement (within the first couple months) (PCA 2003a). The severity of shrinkage of stabilized materials is influenced in part by material properties and mix design proportions. Fine-grained materials tend to exhibit greater shrinkage than coarse-grained materials. Final crack widths are essentially dependent upon the ultimate shrinkage strain and crack spacing. This ultimate shrinkage is one of the most imperative characteristic properties of stabilized materials. According to Halsted (2006), efforts to minimize shrinkage cracking have focused on material selection, mix design, use of additives, curing, and construction techniques. This research covers a laboratory and field study of the efficiency of different curing products for soil-cement bases course curing. Fortes et al. (2008) related the construction of the field study in the SP-332 São Paulo-Campinas Road, approximately the 90 km outside of São Paulo. Figure 1 presents an aerial view of the test track. São Paulo State Test Track is being constructed to improve research in all areas related to highway, such as pavement, bridges, environment, using new technologies. It’s been created many kind of research sponsor, for example: section sponsors; material suppliers; equipment

Figure 1.

Aerial view of the test track.

Figure 2.

Construction of soil-cement layer (a). Curing production application (b).

139

suppliers; technical support; trucking operations; other universities, organizations or companies associated with the highway area, large and small, brought about this joint venture at a truly appropriate time, without any cost to DER-SP or UPM. The mission of this facility will be a reference in terms of highway sector; develop and implement new technologies in infrastructure transport area. Preliminary research was developed in the laboratory and then carried to the field and involved the following steps: a. Definition of the kinds of tropical soils that have potential to be used as soil-cement base; b. Selection of the kinds of curing materials that have potential to be used as element for curing the soil-cement mixture; c. The soil-cement dosage; d. Laboratory soil-cement tests to determine the potential products to use in cure; e. Selection of the eleven different curing materials to be used in the test track; f. Construction of thirteen sections of 40 m × 2.5 m using ten curing materials to available its performance in the test track. Figure 2 shows a view of the field test construction and a curing product application. 4

SUMMARY OF RESEARCH WORK

The research tasks were conducted to evaluate the performances of different types of products that have potential to be used as element for curing of soil-cement mixes. The soil selected was a soil classified as A-7–6 (AASHTO) or LG` (MCT classification) (DNIT DNER CLA 259 1996)—lateritic clayey (Fortes & Merighi 2003) and the Portland cement contents obtained in the dosage test was 9%. In laboratory were done the follow tests: DNER (1996)—Tropical soils classification whose principal main is to classify the soil in lateritic or not lateritic and sand, clay or silt behavior; NBR 7182 (ABNT 1986). This standard is approximately equivalent to ASTM D698-07 e 1 Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Standard Effort (12 400 ft-lbf/ft3 (600 kN-m/m3)) and ASTM D1557-07 Standard Test Methods for Laboratory Compaction Characteristics of Soil Using Modified Effort (56,000 ft-lbf/ft3 (2,700 kN-m/ m3)); NBR12025 (ABNT 1990). This standard is approximately equivalent to ASTM D1633-00 (2007) Standard Test Methods for Compressive Strength of Molded Soil-Cement Cylinders. The samples were compacted in normal proctor energy and in sequence, removed of cylinder to application of curing products follow the rate recommended in Table 1. It was prepared 3 samples for laboratory test for which type of the curing products. It was applied curing material in the top, base and lateral surfaces area, of the specimens and during 28 days they stayed under environmental conditions and there were determinate the variation of the weight. It was observed in the first ages (7 days) that the best performance to waterproof follows this order: K, F, D, C, B. The products A, E, G, H and I didn’t protect the surface against evaporation and loss of water. The 28-day compressive strength test for all types of the curing products was made by testing three specimens. It was observed that in case of some products application an increase in the results. The minimum value of the resistance without cure product application was 2.874 MPa. For the products H, E, K and G, the values were 5.786; 5.561; 4.738 and 4.211 MPa respectively. In the field, test was constructed in thirteen sections as shown in Figure 3 and presented in Table 2 where is explained the different types of curing products used. The average of soilcement base course thickness was 16.9 cm. During the experiment, these sections didn’t receive any action of the traffic. The moisture-density relationship was according to standard Proctor energy in all sections and the results attended the DER-SP (2006) requirements. In terms of the minimum density (degree of compaction), all values were greater than 96.0% and the range of the moisture condition in relation to the optimum water content was less than 2.0%. 140

Table 1.

Materials applied as curing product in the specimens.

Sample

Material

A

Rapid-setting (RS) cationic emulsified asphalt Curing agent concrete—Emulsified polyolefin. White pigmented compound—Complies with ASTM C 309-94 type 2 class A Curing agent concrete—Paraffin emulsion, white-pigmented curing compound Hydrocarbon paraffin emulsion, white-pigmented curing compound Synthetic resin, white-pigmented curing compound Hydrocarbon paraffin emulsion, white-pigmented curing compound Tensoactive. Inorganic salts and polymer ion exchangers. Polymers liquid, brown color High performance hyper plasticizer and hardening accelerator concrete admixture No curing product No curing product Special emulsified asphalt

B

C

D

E F

G

H

I J K

Figure 3.

Density (kg/m3)

Rate (kg/m2)

Application methods

–

0.8

950–1000

0.15–0.20

980 ± 20

0.15–0.20

Uniformly applied to the surface

940

0.17–0.20

Uniformly applied to the surface

1020

0.20

1000

0.17–0.20

Uniformly applied to the surface Uniformly applied to the surface

1100

1 kg/m3

Added in the mixes

1200

0.5%–1.0% of the soil weight

Added in the mixes

– – –

– – 0.001–0.0015 m3/m2

– – Uniformly applied to the surface

Uniformly applied to the surface Uniformly applied to the surface for spray application

Layout of the test track sections.

In the field, specimens were milled from the test track and they were molded with the sample collected during the execution. The following tests were conducted: a) Determination of Compressive Strength of test specimens (ABNT 1990) and tension strength of specimens submitted to diametrical compression (ABNT 1994) as recommended by Brazilian standards. The compressive strength was determined to 7 and 28 days ages and the diametrical compression was determined to 28 days age; PD (dynamic penetration test) of the MCT methodology (Fortes et al. 2006); LWD (Light weight deflectometer) was determined just after compaction and 28 days age; Benkelman beam deflection test (DNER 1994). 141

Table 2. Section no.

Product applied as curing product in the test track. Change

1 2

0–2 2–4

3

4–6

4

Density (Kg/m3)

Curing product applied

Rate

Application methods

Product A—No Product – Product B—Medium Cur- – ing cut-back asphalt (Brazilian Specification—CM 30*) Product C—Rapid-setting – (RS) cationic emulsified asphalt

– – Uniformly applied 0.001 to to the surface 0.0015 m3/m2

6–8

Product D—Special emulsified asphalt

–

0.001 to 0.0015 m3/ m2

5

8–10

6

10–12

980–1,000

0.375 kg/m2

7

12–14

Product E—Special emulsified asphalt Product F—Paraffin emulsion. white color Product G—Evaporation retardant and finishing aid for fresh concrete

980–1,020

0.438 kg/m2

8

14–16

9

10

11

12

13

Product H—Evaporation reducer-monomolecular polymers films 16–18 Product I—high performance hyper plasticizer and hardening accelerator concrete admixture 18–20 Product J—Tensoactive. Inorganic salts and polymer ion exchangers. 20–22 Product K—Curing agent concrete— Emulsified polyolefin. White pigmented 22–24 Product L—Curing concrete agent— Emulsified polyolefin. White pigmented. Complies with ASTM C 309-3 24–270.15 Product M—No Product

1.03 kg/m2

0.018 kg/m2 dilte 1:8 1,200

0.5%–1.0% of the soil weight

1,100

1 kg/m3 de soil

950 to 1,000

0.15–0.20 kg/m2

Can be applied with ordinary garden or backpack type sprayers Apply with a constant-pressure or industrial sprayer It is added to the gauging water at the plant or added on site into the mix It is added to the compaction water Uniformly applied to the surface for spray application

980 ± 20

–

–

–

The determination of the dynamic penetration test using PD was done after construction and 28-days age. These values can represent the bearing ratio capacity in situ. It was observed that the bearing ratio capacity after construction presented an average value of 32.92% and after 28 days, 42.10%. Figure 4 presents the comparative results of the Benkelman beam and LWD (Light weight deflectometer) for 28 days age. The order of the best product performance was: D, C, G, F, H. The other products didn’t present good performance. In terms of the presence of the cracks and their width in the field, after 28 days, the crack width without cure product application was less than 37 mm. This width is justified due to 142

160

140

Deflexion (0,01mm)

120

100

80

60

40

20

0 0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

Chainage LWD

Figure 4.

Benkelman Beam Left side

Benkelman Beam Right side

Comparative results of the Benkelman beam and light weight deflectometer after 28 days.

the use of the 9% Portland cement addition to a clayey soil. The application of the products B, C, D and E avoided the appearance of cracking. The maximum crack width presented in the sections cured with products H and I were 9 mm. In these sections with applied products F, J and K, the maximum crack width was 12 mm. 5

CONCLUSIONS

The importance of the cure agent was observed in this research. Its application creates conditions to allow to the development of the strength potential and durability and to prevent possible damages because of the drying and/or thermal gradient changes during the first ages of structure (LNEC 1974; FHWA 2005). It was possible to observe that the laboratory research presented best results compared to the field device due to the easy control of the operation. The application of these products was deemed effective following the recommendations of the suppliers. In the laboratory, all of them presented good performance to prevent the appearance of cracking, with exception of the emulsified asphalt, but in the field, the results demonstrated that is necessary to take care in the application of this products. It is important to emphasize that fresh hydraulic cementitious mixtures are caustic and may cause chemical burns to skin and tissue upon prolonged exposure. So, any curing product could avoid this reaction and it is the responsibility of the user to establish an appropriate safety and health practices and determine the applicability of regulatory limitations prior to use. Also, the application of the curing products requires a protection of the surface to any mechanics action, to avoid the cure product removal. Considering the results of the laboratory and field research, the special emulsified asphalt presented the best performance. ACKNOWLEDGEMENT The authors would like to thank the LENC—Laboratório de Engenharia e Consultoria Ltda for its assistance in tests, in special to Ms. Álvaro Sérgio Barbosa Jr.; Ms Marcus dos Reis and to Benicio Bibiano Bento. REFERENCES American Society for Testing and Materials. ASTM D698—07 E 1 Standard Test Methods For Laboratory Compaction Characteristics Of Soil Using Standard Effort (12 400 Ft-Lbf/Ft3 (600 Kn-M/M3)). American Society for Testing and Materials. ASTM D1557—07 Standard Test Methods For Laboratory Compaction Characteristics Of Soil Using Modified Effort (56.000 Ft-Lbf/Ft3 (2.700 Kn-M/M3)).

143

American Society for Testing and Materials. ASTM D1633—00 (2007) Standard Test Methods For Compressive Strength Of Molded Soil-Cement Cylinders. Associação Brasileira De Cimento Portland—Abcp—Et-40—Construção De Bases De Solo Cimento Pelo Processo De Mistura Na Pista. 5.Ed. São Paulo, Abcp, 2000. 55p. Associação Brasileira De Normas Técnicas—Abnt Nbr 7182—Solo—Ensaio De Compactação. Rio De Janeiro, 01/08/1986. 10p. Associação Brasileira De Normas Técnicas—Abnt Nbr12025 Solo-Cimento—Ensaio De Compressão Simples De Corpos-De-Prova Cilíndricos. Rio De Janeiro. 30/12/1990. 2p. Associação Brasileira De Normas Técnicas (Abnt). Nbr7222/1994. Argamassa E Concreto—Determinação Da Resistência À Tração Por Compressão Diametral De Corpos-De-Prova Cilíndricos. Rio De Janeiro, Rj, Brasil. 1994, 3p. Departamento De Estradas De Rodagem Do Estado De São Paulo Der/Sp—Departamento De Estradas De Rodagem Do Estado De São Paulo—Diretoria De Engenharia—Et-De-P00/004—Sub-Base Ou Base De Solo-Cimento—Rev. A—São Paulo—2006. Departamento Nacional De Estradas De Rodagem Dner Me 024/94—Pavimento—Determinação Das Deflexões Pela Viga Benkelman. Rio De Janeiro, Rj, Brasil. 1994, 6p. Departamento Nacional De Estradas De Rodagem Dner Cla 259–96—Classificação De Solos Tropicais Para Finalidades Rodoviárias Utilizando Corpos-De-Prova Compactados Em Equipamentos Miniaturas. Rio De Janeiro. 1996. Departamento Nacional De Estradas De Rodagem. Dner-700-Gttr. “Glossário De Termos Técnicos/ Rodoviários. Rio De Janeiro, 1997 (A). 296p. (Ipr. Publ.700). Disponível Em: http://Www1.Dnit. Gov.Br/Arquivos_Internet/Ipr/Ipr_New/Manuais/Dner-700-Gttr.Pdf Departamento Nacional De Estradas De Rodagem Dner Es 305/97—Pavimentação—Base De Solo Cimento. Rio De Janeiro. 1997 (B), 10p. Federal Highway Administration. FHWA. Guide For Curing of Portland Cement: Concrete Pavements, Volume I. Publication No. Fhwa-Rd-02-099. January 2005. 52p. Disponível Em: http://www.Fhwa. Dot.Gov/Pavement/Pccp/Pubs/02099/02099.Pdf Fortes, Rita Moura & Merighi, João Virgilio. The Use Of Mct Methodology For Rapid Classification Of Tropical Soils In Brazil Ijp—International Journal Of Pavements, Vol.2, No.3, September 2003, Pp.1–13. Fortes, Rita Moura; Zuppolini Neto, Alexandre; Menetti, Nélson César; Barbosa Jr., Álvaro S. Potencial Da Utilização Do Ensaio De Penetração Dinâmica Da Metodologia Mct Para Controle Da Construção De Valas. V Jornada Luso-Brasileira De Pavimentos: Políticas E Tecnologias. Andit, Universidade Presbiteriana Mackenzie, Feup—Faculdade De Engenharia Da Universidade Do Porto—Portugal, Caemd E Ciccopn. Recife, Pernambuco, Brasil, 5–7 De Julho De 2006. Fortes, Rita Moura; Merighi, João Virgilio; Bandeira, Alex Alves. 02–041—Estudo Em Laboratório Do Desempenho De Diferentes Materiais Utilizados Para A Cura De Base De Solo Cimento. 2008 Coninfra—Congresso De Infra-Estrutura De Transportes. Andit—Associação Nacional De InfraEstrutura De Transportes. São Paulo, São Paulo, Brasil, 25 A 28 De Junho De 2008. Halsted Gregory E. “Performance of Soil-Cement And Cement-Modified Soil For Pavements: Research Synopsis”. Portland Cement Association. 2006. Accessed In September. 15th. 2008. http://Www.Recycling roads.Org/Techdocs/Is691%20performance%20of%20soil-Cement%20&%20cms.Pdf Isaía, G.C. “Concreto: Ensino, Pesquisa E Realizações”. Ibracon Ed. São Paulo. 2005. 2v, 1579p. Jofré C.; Díaz-Minguela, J. Soilcement Subbases: Mix In Place Vs. Mix In Plant. Second International Symposium On Treatment And Recycling Of Materials—Tremti 2005, Paris, October 24–26, 2005. Communication C084. 7p. Little, Dallas N.; Males, Eric H.; Prusinski, Jan R.;Stewart, Barry. Cementitious Stabilization. A2 J01: Committee On Cementitious Stabilization—Transportation In The New Millennium. TRB, 2000. http://Onlinepubs.Trb.Org/Onlinepubs/Millennium/00016.Pdf Lnec—Laboratório Nacional De Engenharia Civil—Documentação Normativa—Especificação Lnec—Pavimentos Rodoviários—E 304-1974—Solo-Cimento—Portugal—1974. Portlant Cement Association. Soil-Cement Construction Handbook. Illinois. 1995 (A). Portlant Cement Association. Is008—Suggested Specifications For Soil-Cement Base Course Construction. 1995 (B). 4p. Accessed In September. 15th. 2008. http://www.Cement.Org/Bookstore/Profile. Asp?Store=&Ιd=196 Portland Cement Association. Reflective Cracking In Cement Stabilized Pavements. Item Code: Is537. 2003 (A). Accessed In September. 15th. 2008. http://www.Cement.Org/Bookstore/Profile. Asp?Itemid=Ιs537 Senço, W. De. Manual De Técnicas De Pavimentação—Volume I—São Paulo—Editora Pini—1997.

144

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Pavement base unbound granular materials gradation optimization J.P. Bilodeau, G. Doré & P. Pierre Department of Civil Engineering, Laval University, Quebec, Canada

ABSTRACT: Unbound base granular materials must provide adequate bearing capacity to ensure good pavement performance, but they should also have the ability to keep their structural integrity through seasons. The latter is greatly marked by the influence of water on the modulus and through freeze/thaw cycles, emphasizing the importance of drainage capacity. A laboratory study is realized in order to determine the gradation influence on the mechanical behavior and the environmental sensitivity of three typical unbound granular materials. The study allowed the identification of several directly or indirectly related gradation variables closely linked to the studied performance parameters. It was possible to link the environmental sensitivity to one variable related to fine particles content and volumetric influence. Using guidelines on load and environment contributions on the deterioration of typical pavement structures, it was possible to define zones within the grading envelope which ensure optimized behavior. 1

INTRODUCTION

In pavement construction, maintenance and rehabilitation, the use of unbound granular materials (UGM) in the base and the subbase is very common as they usually provide good drainage and adequate bearing capacity. When it comes to base UGM, their main function is essentially structural. However, as stated by Dawson (2001), in order to ensure good pavement performance, they play non negligible roles for drainage and protection against frost action. This emphasizes the importance of water in the pavement, as it can significantly affect base UGM integrity and deformation properties. According to Konrad and Lemieux (2005), water can migrate in every pavement structures. It is generally recognized that it enters the UGM layers by subhorizontal flow from the shoulders, by flowing through a cracked asphalt concrete and by capillary actions (Lebeau 2006, Swanson 1985, Brandl 2001, Ekblad 2007). In pavement engineering, the effect of water is taken into account as it significantly affects the resilient modulus and the permanent deformation behaviour. Moreover, when nearly saturated UGM are subjected to freeze/thaw cycles, their integrity may be affected by frost heave which may cause water content increase (Konrad 2008) depending on the material properties, the severity of which greatly increases with the saturation degree. During the spring period, the UGM materials’ performance is weakened by the net volume increase (Simonsen et al. 2001) and the high water contents (Konrad 2008) caused by the frost action. Therefore, UGM must show structural qualities and the ability to keep their structural integrity throughout a year. This fact is emphasized in scientific literature, since the general UGM characteristics required to ensure good mechanical behaviour are too often not in accordance with the ones required to ensure that water drains rapidly from the layer (Dawson 2001, Janoo 1998, Brown and Chan 1996, Côté and Konrad 2003). For a given aggregate source, it seems that this problem may be investigated from a grain-size distribution point of view. In most of the Transport Agencies, base UGM gradation requirements are specified with grading envelopes. Such envelopes restrain mechanical and drainage performance variations of aggregate, but significant differences may be measured from an extreme to another within the 145

gradation requirements (Côté and Konrad 2003, Boudali 1997, Tian et al. 1997, Richardson 1997, Jones and Jones 1989, Heydinger et al. 1996, Zaman et al. 1994, Flon et Poulin 1987). Therefore, it is more than relevant to investigate the global performance (mechanical properties, modulus water sensitivity, drainage, freeze/thaw sensitivity and erosion resistance) of base UGM for different aggregate sources, in order to suggest restrained zones within a grading envelope in which grading design is optimal for different type of pavement structures.

2

MATERIALS TESTED

In this study, the unbound granular materials tested are partially crushed gneiss, crushed limestone and crushed basalt, whose main source properties are presented in Table 1. The choice of these aggregate sources gives the opportunity to consider to a limited extent the effect of particle shape and surface roughness. In order to study the gradation influence on the behaviour of base granular materials from various aggregate sources, six gradation curves are defined according to the MTQ (Quebec Ministry of Transportation) grading envelope. The gradations tested are presented in Figure 1 and correspond to the fine limit (F), coarse limit (C), middle (M), uniform (U) and well graded (WG) materials of the grading envelope. The MTQ grading envelope is also presented in grey shade in Figure 1 whose limits are defined by F and C gradations. In addition, a discontinuous gradation (FM) which corresponds to modification of the F gradation curve is tested in order to consider the effect of discontinuities on the performance. The main gradation characteristics are presented also in Figure 1. They are presented for the entire gradation but also the gravel (31.5 mm > d > 5 mm) and sand fraction (5 mm > d > 0.08 mm) in order to get information on the influence of each aggregate fraction on the performance of the gradations tested. In order to characterize the effect of grain-size distribution on the behaviour of typical Quebec base UGM, the three aggregate sources were sieved into narrow granular fractions (Passing/Retained (mm/mm): 31.5/20, 20/14, 14/10, 10/5, 5/2.5, 2.5/1.25, 1.25/0.63, 0.63/0.315, 0.315/0.16, 0.16/0.08 and 0.08/0). The sieved UGM were then blended in the laboratory with the appropriate proportions to obtain samples having the gradations presented. Table 2 presents the main materials index properties determined in the characterization. The values ρdmax, ρs, wopt, Abs. and BV represents the modified proctor maximum dry density, the grain density, the optimum water content, the absorption value and the methylene blue value. The mixes volumetric characteristics at maximum dry density are the porosity nopt and the fine fraction porosity nfopt (Côté and Konrad 2003). The latter is expressed by: nf =

VVF n n n − %F = = = c VVC n + (1 − n )% F nc nc (1 − % F )

(1)

in which nf = fine fraction porosity, %F = fine particles content, n = porosity, nc = coarse fraction porosity, VVF = voids volume in the fine fraction and VVC = voids volume in the coarse fraction. In addition, the percentage of the loose unit weight of the coarse aggregate %LUWCA determined by volume, the percentage of the rodded unit weight of the fine aggre-

Table 1.

Aggregate source characteristics.

Wearing (%) Los Angeles (%) Fractured particles (%) Flat/Elongated (%) Petrographic number

G*

L*

B*

16 44 72 14/34 109

18 21 100 23/41 141

10 12 100 16/36 141

Fines specific surface SSF (m2/g) Fines liquid limit wLF (%) Fines mean diameter d50F (μm) Fines clay size content <2 μm (%) Fines uniformity coefficient CuF

* G = Gneiss, L = Limestone and B = Basalt.

146

G*

L*

B*

4 29,8 38 4.2 7.9

16 23,3 18 12.5 17.9

14 27,2 21 14 24.0

Figure 1.

Basalt

Limestone

Gneiss

Table 2.

F M C U WG FM F M C U WG FM F M C U WG FM

Tested gradations.

Main properties of tested gradations. wopt ρd max (kg/m3) (%)

Abs. ρs (kg/m3) (%)

nopt (%)

nf opt (%)

BV %LUWCA %RUWFA %VCA %VFA (cm3/g) (%) (%) (%) (%)

2167 2205 2179 2091 2251 2119 2268 2289 2241 2193 2330 2196 2359 2355 2304 2227 2442 2275

2647 2634 2648 2640 2659 2647 2601 2627 2627 2639 2627 2636 2783 2797 2835 2816 2825 2804

18.1 16.3 17.7 20.8 15.3 19.9 12.8 12.9 14.7 16.9 11.3 16.7 15.2 15.8 18.7 20.9 13.6 18.9

76.0 81.2 91.5 92.9 72.1 78.1 67.7 76.6 89.6 91.0 64.6 74.1 72.0 80.7 92.0 93.0 69.1 76.9

0.07 0.09 0.07 0.06 0.13 0.07 0.31 0.23 0.16 0.16 0.25 0.28 0.22 0.23 0.14 0.15 0.25 0.18

4.9 5.7 4.8 5.9 4.8 4.7 5.0 5.7 4.7 5.8 6.2 4.9 5.1 6.3 4.3 5.9 5.1 5.3

0.49 0.85 0.55 0.99 0.54 0.49 1.54 1.45 1.01 0.99 0.78 1.23 1.87 2.18 1.20 1.59 1.18 1.99

77.7 79.9 98.4 89.7 82.2 63.7 79.9 82.0 101.1 94.2 88.9 66.2 83.9 83.9 101.8 96.2 88.2 69.0

96.8 98.8 86.0 85.8 97.0 98.5 93.5 96.5 85.7 85.7 96.0 97.8 100.4 101.8 89.2 89.8 102.6 103.7

44.8 44.3 45.5 44.2 43.8 44.3 47.0 46.7 46.9 47.4 48.1 47.0 49.4 47.7 48.5 48.8 47.7 49.0

29.2 27.9 28.1 31.6 25.3 31.8 24.8 26.2 26.8 31.8 23.3 30.7 29.5 29.8 31.4 35.1 26.9 33.4

gate %RUWFA determined by volume, the voids within the coarse aggregates at loose unit weight %VCA and the voids within the fine aggregates at rodded unit weight %VFA are also presented. Those volumetric characteristics are determined with unit weight tests and provide useful indications about the blend and particle properties (shape, roughness, etc.). 3

EXPERIMENTAL PROGRAM

The compaction of the laboratory specimens is performed with a vibratory compactor to ensure minimization of grain crushing. In order to investigate the mechanical behaviour and the sensitivity to environmental stresses, the samples for each aggregate source were 147

submitted to a series of performance tests. These are the resilient modulus tests, frost heave tests, hydraulic conductivity tests and erosion resistance tests. During the resilient modulus tests, some information regarding the permanent strain sensitivity was also collected. The mechanical properties characterization is performed with resilient modulus testing. The followed laboratory procedure is the same one that was used by Doucet and Doré (2004) and is in accordance with the standard LC 22-400 (MTQ 2004), which is mostly based on AASHTO T307-99 (AASHTO 2003). The main differences between the two standards are that more conditioning cycles are applied (10000), the deformation is measured on the sample inside the triaxial cell and the samples are characterized at three water contents. The first water content is equal to Abs.+2%, the second is at near saturation (sample saturation being performed with a vacuum) and the third is a drained water content. The samples are 300 mm height and have an internal diameter of 150 mm. The data from the conditioning cycles are used to characterize the permanent strain behaviour by extracting the permanent deformation rate of the last 5000 cycles. The freezing tests are performed inside an extensible freezing cell as it is described in Bilodeau (2008). The frost susceptibility was determined through step-freezing segregation potential tests in open drainage system on saturated samples. The samples were submitted to a temperature of –4°C at the specimen top, 2°C at the specimen bottom and an overburden stress of 7 kPa. The sample dimensions are 175 mm × 101.4 mm (Height × Diameter) and they are scalped on the 5 mm sieve. The hydraulic conductivity tests are performed inside a rigid wall permeameter compaction mould. From the data presented in Côté et Konrad (2003), Boudali (1997) and Flon et Poulin (1987) on several Quebec base UGM, the expected hydraulic conductivity varies from 10–5 to 10–8 m/s and the used hydraulic gradient falls in the suggested gradient magnitude (ASTM 2002). Backpressure of the specimen up to 700 kPa is realized to ensure good sample saturation to minimize this variable effect. Finally, the erosion resistance is investigated with the laboratory equipment and procedure described in Bilodeau et al. (2007). Compacted samples are submitted to 7 litres surface water flowing in order to measure an erosion rate, which represents the dry mass of materials extracted from a specific surface in a specific time.

4

EXPERIMENTAL RESULTS

The results of the 72 tests performed on the selected UGM are summarized in Table 3. The values of segregation potential SP7 kPa, erosion rate ER, saturated hydraulic conductivity K, resilient modulus water sensitivity S400 (total stress θ = 400 kPa), resilient modulus MR400 (θ = 400 kPa, saturated water content) and permanent strain rate e–P are presented in this table. The resilient modulus and resilient modulus sensitivity are presented for θ of 400 kPa, since it represents approximately the median limit of the total stress characterization interval. The resilient modulus water sensitivity is described by calculating the slope of the relationship between MR and saturation degree. Since the resilient modulus is characterized at three water contents, the linear relationship hypothesis is the best approximation to compute the effect of water on resilient behavior. It should be pointed out that, in average, the reached compaction level is 97.6% with a standard deviation of 2.0% for all the tests and all the samples. Therefore, density should not influence significantly the results presented. In order to investigate the effect of grain-size distribution on the various performance parameters described, the strength of association between these parameters and several directly or indirectly gradation related variables was verified with correlation coefficients R in combination with dispersion diagrams. Prior to that analysis, the statistical normality of each group of data was verified with the Shapiro-Wilk test. This analysis clearly demonstrated that the environmental related performance parameters are all strongly related to the finer fraction of the materials, as it is generally found in the literature. However, it is observed that for each performance parameter, the fine fraction porosity is almost always the variable presenting the highest strength of association for the three aggregate source tested. Some examples of the relationships found between performance parameters and fine fraction 148

SP7 kPa (mm2 °C–1 d–1)

ER (g m–2 s–1)

K (m s–1)

S400 (MPa %–1)

MR400 (MPa)

e–P (% cycle–1)

Gneiss

F M C U WG FM Mean SD*

16.4 10.6 7.3 4 20.7 10.8 11.6 6.1

437.6 603.5 697.4 1037.8 381.4 573.5 621.9 233.7

4.38 × 10–6 1.14 × 10–5 1.20 × 10–5 1.41 × 10–5 4.15 × 10–6 5.44 × 10–6 8.58 × 10–6 4.41 × 10–6

–1.489 –1.052 –0.835 –0.631 –1.650 –1.340 –1.166 0.395

367.6 356 360.4 320.4 394.9 458.2 376.3 46.7

1.85 × 10–7 2.00 × 10–7 2.80 × 10–7 2.75 × 10–7 2.10 × 10–7 3.05 × 10–7 2.43 × 10–7 5.01 × 10–8

Limestone

Performance test results.

F M C U WG FM Mean SD

32.8 27.2 20.9 12.4 40.9 27.6 27.0 9.8

133.5 224.5 309.9 511.0 104.4 154.9 239.7 152.0

5.56 × 10–6 2.58 × 10–6 1.38 × 10–5 1.65 × 10–5 2.50 × 10–6 7.58 × 10–6 8.09 × 10–6 5.86 × 10–6

–0.929 –0.527 –0.483 –0.414 –0.828 –0.414 –0.599 0.200

647.7 725.1 824.6 643.8 719.0 561.4 686.9 90.1

2.65 × 10–7 1.85 × 10–7 2.00 × 10–7 2.00 × 10–7 3.37 × 10–7 4.50 × 10–7 2.73 × 10–7 1.04 × 10–7

Basalt

Table 3.

F M C U WG FM Mean SD

62.5 59.2 37.7 28.7 63.4 51.1 50.4 14.3

236.4 273.6 289.8 643.5 111.1 262.7 302.9 178.8

1.54 × 10–6 2.36 × 10–6 1.17 × 10–5 2.10 × 10–5 3.55 × 10–6 7.14 × 10–6 7.88 × 10–6 7.44 × 10–6

–0.403 –0.379 –0.205 –0.284 –0.723 –0.551 –0.424 0.188

441.2 473.7 507.0 438.1 526.9 376.8 460.6 54.1

2.00 × 10–7 2.35 × 10–7 3.71 × 10–7 2.50 × 10–7 1.55 × 10–7 4.50 × 10–7 2.77 × 10–7 1.11 × 10–7

*SD = Standard deviation.

Figure 2.

Examples of the relationships between performance parameters and explanatory variables.

porosity are presented in Figure 2. The average R value for these relationships is 0.91. For the environmental stresses sensitivity, the R values between the performance parameters and nf are generally higher than the ones with %F, d10 and Cu amongst others. One exception is found for the erosion resistance, were Cu presents higher R values. The mechanical performance, investigated through MR and e–P, is explained by various parameters related to various 149

soil fractions, depending on the aggregate source, as presented in Figure 2. The average R value between the presented explanatory variables and the mechanical performance is 0.96. As a general trend, the resilient behaviour of the crushed rocks is highly dependent of the gravel fraction grain-size distribution and on the gradation uniformity for the gneiss, while the permanent strain behaviour for all sources relates on grain-size properties of the smaller fractions. Generally, the strength of association between the explanatory variables and the resilient modulus is higher than with the permanent strain rate. The main reason is probably that, unlike the MR400 values at water saturation, the permanent strain rate are obtained at unequal saturation degree for all the samples. In order to quantify the performance variations, the FM gradation curve had to be removed from the relationships between mechanical performance and the explanatory variables because the behaviour was divergent from the other grain-size distributions. Also, the gneiss presents a lot less explanatory variables related to the mechanical performance.

5

DISCUSSION

In order to describe the sensitivity to environmental stresses, it is found that the fine fraction porosity is the best variable. It is related to the fine particles percentage and the samples void content. Conceptually, it describes how the fine particles fill the voids created by the coarse aggregate (d > 80 μm) granular assembly and is expressed as a ratio of the voids volume within the fine fraction (d > 80 μm) to the voids volume within the coarse fraction (d > 80 μm) (Equation 1). Therefore, it has the advantage of describing the fine particles effect on performance also on a volume and voids point of view. This is the main reason why higher R values are always found for this parameter, especially when compared to the ones obtained for the fine particles mass percentage. However, the fine fraction porosity is highly dependent on the fine particles percentage more than any other gradation related parameters. For the SP7kPa and K, it is observed that the gneiss material presents the highest values in average, followed by the limestone and the basalt. The results variability is lower for the hydraulic conductivity tests. According to the previous work of Côté and Konrad (2003) and Konrad (2005), this trend can be considered mainly as a function of the fine particles’ properties, for which some examples are presented in Table 1. However, it can be observed that the fine particles’ uniformity coefficient CuF and the fine particles’ clay-size content <2 μm are the most suitable fines characteristics to describe the variability in the average values. When it comes to erosion resistance, the previous work from Bilodeau et al. (2007) demonstrated the important role of uniformity coefficient and fine fraction porosity to describe gradation influence, but also, the methylene blue value VB to describe the aggregate source effect. The S400 values representing resilient modulus water sensitivity also clearly show the effect of the aggregate source, but also reveal the importance of other aggregate properties. At first look, it is noticeable that the crushed aggregates present approximately the same values while the partially crushed aggregate presents significantly higher S400 values. This shows the high importance of inter particle friction obtained by grain crushing. The mechanical performance analysis of the crushed aggregate reveals that the resilient modulus is mostly a function of the coarse aggregate size and grain-size distribution. For the basalt, it is related to the size of the coarser particles (10 mm to 20 mm), while it is related to the particle sizes of 2.5 mm to 14 mm for the limestone. For the gneiss, it was found that the resilient modulus is more related to the uniformity related parameters, Cu showing the strongest relation with MR. It was found that the permanent strain behavior is complementary to the resilient behavior of these materials. In fact, it is more related to the finer fraction of the materials (coarse sand and fine sand) for the basalt and the gneiss, the finer these fraction are, the better (lower) the permanent strain behavior is. For the limestone, the results show that more uniformly graded materials are suitable. For the gneiss materials, it can be observed in Table 2 that the permanent strain rate increases with an increase of %LUWCA and decreases with an increase of %RUWFA. This means that when the coarse aggregate fills a large volumetric proportion of the sample and a somewhat significant number of contacts 150

are found between the particles of the coarse aggregate fraction, the permanent strain behavior is weaker. This is probably because of the nature of the aggregate, which is partially crushed and still presents some smooth and rounded surfaces. The highest resilient modulus, for the limestone, can be explained by the crushed nature of this aggregate source, and also by the fact this type of materials has low porosity values (Boudali 1997). This packing potential can also be appreciated by the %VCA and %VFA values. The basalt is also a crushed material but presents MR values lower than the limestone, probably because the packing potential of the aggregates is lower as shown by the %VCA, %VFA and n values. As previously mentioned, the results demonstrated that the suitable characteristics to ensure a good mechanical behavior are not always in agreement with the ones to ensure good drainage, low frost susceptibility and a low resilient modulus water sensitivity. Taking the basalt example, the results indicate that a coarser coarse aggregate fraction and a finer sand fraction (d20) would improve the resilient modulus and the permanent strain behavior. However, to obtain a low frost susceptibility, good drainage and low resilient modulus water sensitivity, higher fine fraction porosity at maximum dry density are suitable, which can mainly be obtained by reducing the fine particle percentage. Overall, the gneiss material is also subjected to this problem, while it is less the case for the limestone, since a good permanent strain behavior is linked to more uniformly graded materials for this aggregate source. In order to take into account this problem, detailed information must be known on how typical pavement deteriorates. A recent study from Doré et al. (2006) showed that, for a fine grained subgrade soil and wet freeze conditions (typical in the province of Quebec, Canada), the ratio of the load associated pavement deterioration to the total pavement deterioration was about 0.5 for local roads and 0.75 for major highways. Consequently, the environmental related contributions to pavement deterioration were about 50 and 25% respectively. Taking these ratios into account, it seems suitable to divide the performance variations associated with various gradation related variables into four specific performance levels, numbered L1 to L4. Within the studied grading envelope, level 1 (L1) includes the upper 25% materials in the total performance variations, level 2 (L2) includes materials in the 25 to 50% of the total performance variations, etc. For the example of a major highway, using these levels, a zone included in the grading envelope corresponding to L1 for the mechanical behavior and L3 for the behavior under environmental factors should be selected. Using the various relationships found between performance parameters and nf , the maximum and minimum performance, and therefore the performance variation, can be determined if the variation in nf within the envelope is known. Significant relationships between n and Cu were identified and were used to identify the minimum and maximum nf values and, therefore, the maximum and minimum performance parameter values. It was then postulated that the strong dependency of nf to %F should be used to associate a critical %Fc value to critical nf (nf c) value for each level. To do so, a matrix of 14750 gradations was created using 10 theoretical gradations computed with the Fuller & Thompson equation, 10 real gradations

Figure 3.

Relationship between nfopt and %F for the three aggregate sources.

151

of sold base granular materials and the tested gradations (excluding FM) (25 theoretical and real gradation shapes that fall within the considered grading envelope). The matrix was created by dividing the interval between each pair of gradation in 50 to create 49 new gradations for each pair. Using the matrix, typical relationships between nf and %F (Figure 3) were determined. As it can be observed, the variability of nfopt values is greater for the limestone than be basalt, mostly because of the greater tendency of the limestone particles to pack in a denser manner thus causing the addition of fine particles to influence the packing of the particles having d > 80 μm to a greater extent. The critical %Fc values for each level and performance parameter considered are presented in Table 4. As it can be observed, the %Fc for the parameters showing a linear relationship between performance and nf (SP7 kPa and S400) are not equal to the %F maximum variation (2 to 7%) divided in four parts (3.25, 4.5 and 5.75%). This shows the importance of considering not only the %F effect by mass, but also on a volumetric point of view. For the other performance parameters, the distribution of the %Fc is also dependent on the relationship type (exponential, power, etc.). It should be noted that the combination of SP7 kPa and S400 values gives a useful indication for freeze/thaw sensitivity because it considers the sensitivity to volume increase and modulus water sensitivity, which are the two main mechanisms to consider for thaw weakening. The same exercise can be performed for the mechanical behavior (resilient modulus and permanent strain rate). However, in that case, the maximum and minimum of the gradation related variables identified can be easily obtained in comparison to nf . It should be noted that several relationships were found relevant between the resilient modulus and various gradation related parameters, especially for the crushed materials gravel fractions. For the gneiss, only the relationship between MR400 and Cu was identified. The results of that analysis, combining the mechanical performance on the resilient and permanent strain behaviors point of view, are presented in Figure 4. For the previous cited examples, which are a local road and a major highway, the combination of Figure 4 and Table 4 can be used to determine zones within the grading envelope

Table 4.

Values of %Fc and nfc for various performance parameters.

Gneiss : nf c/%Fc SP7 kPa S400

K

Limestone : nf c/%Fc ER

L1 0.876/3.3 0.897/2.4 0.784/5.9 L2 0.822/4.8 0.856/3.4 0.840/4.3 L3 0.715/6.4 0.801/4.9 0.888/2.9

Figure 4.

SP7 kPa S400

K

Basalt : nf c/%Fc ER

SP7 kPa S400

K

ER

0.845/3.3 0.883/2.4 0.735/5.8 0.869/3.1 0.906/2.3 0.771/5.4 0.772/4.9 0.836/3.5 0.810/4.1 0.807/4.6 0.870/3.1 0.836/3.9 0.699/6.6 0.765/5.1 0.869/2.7 0.745/6.0 0.815/4.4 0.888/2.7

Mechanical performance zone for each performance parameter.

152

in which gradations should be restrained to ensure an adequate performance for these two examples. As previously mentioned, for a major highway, level 1 should be selected from a mechanical point of view while level 3 should be selected in terms of fine particles percentage. For local roads, it seems that level 2 should be selected from mechanical and environmental points of view. However, the %Fc values vary from one performance parameter to another and, therefore, it is necessary to determine the priority performance parameters for the design. Also, it should be pointed out that, as it is widely described in the scientific literature, the anticipated performance significantly varies from one aggregate source to another so the methodology presented must be combined with a good engineering judgment to allow level modification with aggregate source. 6

CONCLUSION

A laboratory study was conducted on the performance of UGM for six gradations and three aggregate sources. The performance was considered from multiple points of view, which are mechanical performance and environmental stresses sensitivity. The results allowed identifying one fines related volumetric parameter, nf , that describes satisfactorily the latter. In the former case, the contribution of various fractions of the grain-size distributions tested was pointed out. Various relationships between explanatory variables and performance parameters were used in order to identify the maximum performance variation within the grading envelope. Using data on the typical deterioration processes of typical pavement structures in Canada, adapted gradation zones were identified to ensure adequate performance of three commonly used unbound granular materials regarding the mechanical behavior and the environmental stresses sensitivity. REFERENCES American Association for State Highway and Transportation Officials. 2000. Determining the Resilient Modulus of Soils and Aggregate Materials. In Standard Specifications for Transportation Materials and Methods of Sampling and Testing, 20th Edition. AASHTO, Washington, DC. American Society for Testing and Materials. 2002. Standard Test Method for Measurement of Hydraulic Conductivity of Porous Materials Using a Rigid Wall, Compaction-mold Permeameter. Standard D5856-95, ASTM, Philadelphia, PA. Bilodeau, J.-P., Doré, G. and Pierre, P. 2007. Erosion Susceptibility of Granular Pavement Materials. International Journal of Pavement Engineering, 8(1): 55–66. Bilodeau, J.-P., Doré, G. and Pierre, P. 2008. Gradation Influence on Frost Susceptibility of Base Granular Materials. International Journal of Pavement Engineering, 9(6): 397–411. Boudali, M. 1997. Module réversible des graves non traitées des fondations routières du Québec. Ministère des Transports du Québec, Québec, Québec. Brandl, H. 2001. Freezing-Thawing behavior of soils and other granular materials—influence of compaction. In Geotechnics for Roads, Rail Tracks and Earth. A.A. Balkema, Rotterdam, The Netherlands, pp. 141–164. Brown, S. and Chan, F.W.K. 1996. Reduced rutting in unbound granular pavement layers through improved grading design. In Proceedings of the Institution of Civil Engineers: Transport, 117(1), 40–49. Côté, J. and Konrad, J.-M. 2003. Assessment of the hydraulic characteristics of unsaturated basecourse materials: a practical method for pavement engineers. Canadian Geotechnical Journal, 40(1): 121–136. Dawson, A. 2001. Granular Pavement Layer Materials … Where are we?. ARRB Workshop, Melbourne, Australia, 20 p. Doré, G., Drouin, P., Pierre, P., Desrochers, P. and Ullidtz, P. 2006. Estimation of the Relationships of Flexible Pavement Deterioration to Traffic and Weather in Canada. In Proceedings of the 10th International Conference on Asphalt Pavements CD-Rom, Québec, Québec. Doucet, F. and et Doré, G. 2004. Module réversible et coefficient de poisson réversible des matériaux granulaires C-LTPP. In Proceedings of the 57th Canadian Geotechnical and 5th Joint IAH-CNC and CGS Groundwater Specialty Conferences CD-Rom, Québec, Québec.

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Ekblad, J. 2007. Influence of Water on Coarse Granular Road Material Properties. PhD Dissertation, Royal Institute of Technology, Stockholm, Sweden. Flon, P. et Poulin, J.-F. 1987. Influence du pourcentage de particules fines sur la portance d’une chaussée à partir d’essais en laboratoire. Études et recherche en transports, Matériaux et Essais, Ministère des Transports du Québec, ISBN-2-550-17670-7. Heydinger, A., Xie, Q., Randolph, B. and Gupta, J. 1996. Analysis of resilient modulus of dense- and open-graded aggregates. Transportation Research Record, 1547: 1–6. Janoo, V.C. 1998. Quantification of shape, angularity, and surface texture of base course materials. Special report 98-1, U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH. Jones, H.A. and Jones, R.H. 1989. Horizontal permeability of compacted aggregates. In Proceedings of the 3rd Symposium on Unbound Aggregates in Roads (UNBAR4), University of Nottingham. Edited by R.-H. Jones and A.R. Dawson. Butterwoths, London, pp. 70–77. Konrad, J.-M. 2005. Estimation of the segregation potential of fine-grained soils using the frost heave response of two reference soils. Canadian Geotechnical Journal, 42: 38–50. Konrad, J.-M. and et Lemieux, N. 2005. Influence of fines on frost heave characteristics of a wellgraded base-course material. Canadian Geotechnical Journal, 42: 515–527. Konrad, J.-M. 2008. Freezing-Induced water migration in compacted base-course materials. Canadian Geotechnical Journal, 45: 895–909. Lebeau, M. 2006. Développement d’une méthodologie de sélection des matériaux de fondation routière pour contrer les effets du dégel. PhD Dissertation, Université Laval, Québec, Canada. Ministère des Transports du Québec. 2004. Détermination du module réversible et du coefficient de poisson réversible des matériaux granulaires à l’aide d’une cellule triaxiale à chargement déviatorique répété (LC-22-400). Procédure de laboratoire, Ministère des Transports du Québec, Québec. Richardson, D. 1997. Drainability characteristics of granular pavement base materials. Journal of transportation engineering, 123(5): 385–392. Simonsen, E., Janoo, V.C. and Isacsson, U. 2002. Resilient properties of unbound road materials during seasonal frost conditions. Journal of Cold Regions Engineering, ASCE 16(1): 28–50. Swanson, H. 1985. Literature review on frost heaving. Report No. CDOH-DTP-R-85-1, Colorado department of highways, Denver, Colorado. Tian, P., Zaman, M.M. and Laguros, J.G. 1998. Gradation and moisture effects on resilient moduli of aggregates. Transportation Research Record, 1619: 75–84. Zaman, M., Chen, D.-H. and Laguros, J.G. 1994. Resilient Moduli of Granular Materials. Journal of Transportation Engineering, 120(6): 967–988.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Influence of the macroscopic cohesion on the 3D FE modeling of a flexible pavement rut depth F. Allou & C. Petit Laboratory of Mechanics and Modeling of Materials and Structures in Civil Engineering, University of Limoges, Egletons, France

C. Chazallon Laboratory of Engineering Design—INSA, Strasbourg Cedex, France

P. Hornych Materials and Pavements Structures Division, Laboratoire Central des Ponts et Chaussées, Bouguenais Cedex, France

ABSTRACT: Rutting, due to permanent deformations of unbound materials, is one of the principal damage modes of low traffic pavements. Flexible pavement design methods remain empirical in so far as they do not take into account the inelastic behavior of these materials. A simplified method, based on the concept of the shakedown theory developed by Zarka for metallic structures under cyclic loadings, to estimate the permanent deformations of unbound granular materials (UGM) subjected to traffic loading has been developed. Based on repeated load triaxial tests, a general procedure has been developed for the determination of the material parameters of the constitutive model. Finally, the results of a finite elements modelling of the long-term behaviour of a flexible pavement with the simplified method are presented and compared to the results of a full scale pavement experiment performed at LCPC. 1

INTRODUCTION

Low traffic pavement design methods, used in pavements mechanics, are based on linear elastic calculations. The design criterion for rutting consists in limiting the vertical elastic strains at the top of the subgrade. No criterion is applied for the unbound granular layers. This paper presents a simplified model for the prediction of rutting of unbound pavement layers. This model, based on elastoplasticity, uses the shakedown theory to determine directly the final state of the structure, which can lead to a stabilization of the permanent strains (elastic shakedown or plastic shakedown) or to failure (ratchetting). The shakedown concept applied to pavements has been introduced first by Sharp et al. (1984). Contributions of Yu & Hossain (1998) and Maier et al. (2003) are based on the fact that if ratchetting occurs, the structure will fail. The critical load level below which the structure shakes down and above which it fails is called the shakedown load and it is this parameter that is the key design load. The work of Habiballah and Chazallon (2005) is based on the theory developed by Zarka (1979) for metallic structures submitted to cyclic loadings. Zarka defines the plastic strains at elastic shakedown with Melan’s static theorem extended to kinematic hardening materials. The evaluation of the plastic strains when plastic shakedown occurs, is based on this simplified method. Habiballah and Chazallon have extended the previous results to unbound granular materials with a non-associated elastoplastic model. To improve the finite elements modelling of flexible pavements, the model takes into account the initial state of the material, such as:

155

– the initial stress state. – the initial water content. – the initial anisotropy: the elastoplastic calculation uses an anisotropic hyperelastic law. In order to describe the time dependent evolution of the rut depth, a parameter linking time and cycle number has been added. The first part of the paper presents the simplified model, based on the shakedown theory. A comparison of calculations with experimental results of repeated load triaxial tests on an unbound granular material is discussed. The last part presents the results of the finite element modelling of the long-term behaviour of a flexible pavement with the simplified model, which consider the macroscopic cohesion, introduced in the elastic calculation, to take into account effect of unsaturated conditions. A comparison of calculations with the results of the LCPC full-scale pavement experiment is presented. The results which have been obtained underline the influence of the macroscopic cohesion on the resilient behavior which leads to overestimate the rut depth calculation when it is taken into account. 2

THE CONSTITUTIVE MODEL

Let us consider an elastoplastic structure. Its boundary Γ is subjected to imposed surface forces Fi d ( x,t ) in the Γ Fi partition and to prescribed surface displacements U dj ( x,t ) in the ΓU j partition. The body forces X dj ( x,t ) and the initial strain ε ijI( x,t = 0 ) are defined in the volume V. This structure is supposed to satisfy the theory of small displacements and deformations. This last hypothesis is enough for rutting of unbound granular layers. The general problem can be solved with the finite elements method as follows:

ε ij ( x,t ) = Mijklσ kl ( x,t ) + ε ijp( x,t ) + ε ijI( x, 0 )

(1)

where the actual strain tensor εij(x, t) is kinematically admissible with U dj ( x,t ) on ΓU and the actual stress tensor σelij is statically admissible with Fi d ( x,t ) on Γ Fi and with X dj ( x,t ) in V; ε ijp ( x,t ) is the plastic strain tensor, ε ijI( x, 0 ) is the initial strain tensor, Mijkl is the compliance elasticity matrix. The basic general problem can be decomposed into an elastic and inelastic part. 2.1 Elastic problem The response associated with the elastic part is expressed as follow:

ε ijel( x,t ) = Mijklσ klel( x,t ) + ε ijI( x, 0 )

(2)

where the elastic strain tensor ε ijel( x,t ) is kinematically admissible with U dj ( x,t ) on ΓU j and the elastic stress tensor σ ijel( x,t ) is statically admissible with on Γ Fi and with X dj ( x,t ) in V. This elastic part of the behaviour is considered non-linear and is described by the anisotropic Boyce model (Hornych et al. 1998). Its expression is:

ε v′ =

2 1 p′n ⎛ q′ ⎞ 1 p′n ⎡ ( n − 1) K a ⎛ q′ ⎞ ⎤ d ′ ⎢ ⎥ + and ( , ) ε 1 F x t = ⎜ ⎟ ⎜ ⎟ i q K a pan −1 ⎢ 3Ga pan −1 ⎝ p′ ⎠ 6Ga ⎝ p′ ⎠ ⎥ ⎣ ⎦

(3)

where ε v′ = ε1/γ + 2 ⋅ ε 3 is the resilient volumetric strain; ε q′ = (2 / 3) (ε1 / γ − ε 3 ) is the resilient shear strain; p' = (γ ⋅ σ1 + 2 ⋅ σ3) is the mean stress; q' = γ ⋅ σ1 − σ3 is the deviatoric stress; Ka, Ga, n and γ are the model parameters. In this model, the vertical and horizontal elastic parameters are linked by the relationship: Eh ν hv = γ 2, =γ Ev ν hh 156

(4)

In triaxial tests, values of γ are generally lower than 1, which means that the material is stiffer in the vertical direction (Ev > Eh). 2.2 Inelastic problem The inelastic problem is obtained by difference between the total and the elastic problem. It can be written according to the following equation:

ε ijine ( x,t ) = ε ij ( x,t ) − ε ijel ( x,t ) = M ijkl Rij ( x,t ) + ε ijp ( x,t )

(5)

where ε ijine ( x,t ) is kinematically admissible with 0 on ΓU j . In this formulation, the elasticity matrix Mijkl is anisotropic. The residual stress field Rij(x,t) is defined as the difference between the actual and the elastic stress fields as follow: Rij ( x,t ) = σ ij ( x,t ) − σ ijel ( x,t )

(6)

It is statically admissible with 0 on Γ Fi and with 0 in V. With the knowledge of the plastic strain tensor ε ijp ( x,t ) and the compliance elasticity matrix Mijkl, the inelastic problem is solved with a null stress boundary condition and the inelastic strain fields ε ijine ( x,t ) are obtained. Then the residual stress tensor is calculated with the following expression: −1 Rij ( x,t ) = Mijkl (ε ijine ( x,t ) − ε ijp ( x,t ))

(7)

The main idea of the Zarka method is to introduce an internal structural parameter field to give an estimate of the stabilized state and the inelastic component, for metallic structures subjected to cyclic loading. This approach has been applied by Habiballah to predict the inelastic behavior of unbound granular materials under large numbers of load cycles. The same framework has been used and the simplified method is summarized in the next paragraph. The Drucker Prager yield surface and the Von-Mises yield surface are used with linear kinematic hardening. The flow rule is associated. Its expression takes the following form: r ≤ rmin ⇒ f = g =

1 (Sij ( x,t ) − yij ( x,t )) : (Sij ( x,t ) − yij ( x,t )) − α I1 (σ ij ( x,t )) − k 2

(8)

1 r > rmin ⇒ f = g = ( Sij ( x,t ) − yij ( x,t )):( Sij ( x,t ) − yij ( x,t )) 2 where rmin defines the size of the elastic domain. yij = 23H ε ijp is the kinematic hardening tensor, H is the hardening modulus, Sij is the deviatoric part of the actual stress tensor σij, I1(σij) is the first stress invariant, α and k are material parameters. The actual deviatoric stress can be written as: Sij ( x,t ) = Sijel ( x,t ) + devRij ( x,t )

(9)

We define the structural transformed parameters field: Yij ( x,t ) = yij ( x,t ) − devRij ( x,t )

(10)

Then, the yield surface in the deviatoric plane can be expressed as follows: f (Sijel −Yij ) ≤ 0 157

(11)

el

The yield surface boundary becomes a circle centered in Sij , in the structural transformed parameters plane. The inelastic problem can be written with the structural transformed parameters field:  ′ R ( x,t ) + 3 Y ( x,t ) ε ijine ( x,t ) = M ijkl kl ij 2H

(12)

 ′ is the modified anisotropic elasticity matrix, defined by the following equality: where M ijkl 3 ′ = M M dev ijkl ijkl + 2H

(13)

Thus, we obtain the residual stress tensor of the elastoplastic structure with:  ′−1 ⎛ ε ine ( x,t ) − 3 Y ( x,t ) ⎞ Rij ( x,t ) = M ijkl ⎜ kl kl ⎟ 2H ⎝ ⎠

(14)

Finally, the plastic strain ε ij is given by: p

ε ijp ( x,t ) =

3 (Yij ( x,t ) + devRij ( x,t )) 2H

(15)

2.3 Response of a structure subjected to a cyclic loading During a cyclic loading, the elastic response of the structure can be written: Sijel ( x,t ) = (1 − Λ(t ) ) Sijel min ( x ) + Λ(t )Sijel max ( x )

(16)

el el where Sij min ( x ) and Sij max ( x ) are the minimum and maximum values respectively of the deviatoric part of the elastic stress tensor, Λ(t) is a periodic function of time. The elastic domain C (Sijel ), in the transformed structural parameters plane, is a circle centred in Sijel . The plastic mechanism is active only if the transformed structural parameters field is on the boundary of the convex C (Sijel ) . The nature of the limit state of the structure will depend on the elastic response. According to the loading amplitude ΔSijel , the convex set C (Sijel ) = C0 + Sijel moves linearly between C (Sijel min ) and C (Sijel max ). Two cases exist:

– elastic shakedown will occur when those two convex sets have a common part Cl′ . – otherwise, plastic shakedown occurs. 2.3.1 Elastic shakedown At each point of a structure in an elastic shakedown situation, the initial structural transformed parameters (Y0)ij can be transported with the movement of the plastic convex. Three cases can be obtained: – (Y0)ij is inside Cl and remains immobile (Fig. 1a). – (Y0)ij is such that, after the first cycle, it reaches the boundary of Cl and remains immobile (Fig. 1b). – (Y0)ij is transported with the movements of the convex to finish on the boundary Cl or Cl′ (Fig. 1c). In this case, the stabilized state is reached after several cycles. Thus, the final position (Y1)ij determines the final cycle which solves the inelastic problem and the general problem. 158

Cl'

Sijelmin

Cl

Cl

Cl Sijelmin

Sijel max

Sijelmin

Sijelmax

(Y0)ij

(Y1)ij

(Y1)ij

(Y0)ij

(Y0)ij = (Y0)ij (a)

(b)

Figure 1.

Sijelmax

(c)

Cases for the determination of (Y1)ij.

2.3.2 Plastic shakedown The solution is given from geometrical considerations (Zarka 1979, Habiballah & Chazallon 2005). In the structural transformed parameters plane, Yijmax and Yij min belong to extreme positions of the two convex centered in Sijel max and Sijel min, respectively. The final cycle is defined by the mean value (ε ijp )moy and the range Δε ijp. Thus, the values of the ΔYij and (Yij)moy fields are respectively: ⎛ ΔYij ( x ) = ΔSijel ( x ) ⎜1 − ⎜ ⎝

(Yij )moy ( x ) =

ΔSijel ( x ) ⎜⎛ 1+ ⎜ 2 ⎝

⎞ ⎟ el ⎟ 1 Δ el Δ ( S ( x ) S ( x )) ij ij 2 ⎠ r1( x ) + r 2 ( x )

⎞ ⎟ + S el ( x ) ijmin el el 1 ( ΔSij ( x )ΔSij ( x )) ⎟⎠ 2 r1( x ) − r 2 ( x )

(17)

(18)

where r1 and r2 are the radii of the two convex centered in Sijel min and Sijel max. Modifications have been added in order to describe the rut depth evolution with time. For that, a new function F(N) is defined. This function, determined from results of repeated load triaxial tests, is applied to the stabilized plastic deformation, as follows: ⎡ ⎛ N ⎞− B ⎤ ε ijp ( x, N ) = F ( N ) ⋅ ε ijp ( x ) and F ( N ) = ⎢1 − ⎜ ⎟ ⎥ ⎢⎣ ⎝ 100 ⎠ ⎥⎦

(19)

where N is the number of cycles; B controls the shape of the curve of evolution of the plastic strains. For finite elements modelling of pavements, the function F(N) is applied to the load level instead of the stabilized plastic strain (Hornych et al. 2007). 3

EVALUATION OF MODEL PARAMETERS

For the calibration of the model, a programme of repeated load triaxial tests was performed, on a 0/20 mm unbound granular base course material (crushed gneiss) and on a 0/4 mm subgrade soil (Missillac sand), tested on the LCPC accelerated pavement testing facility by Hornych (2003, 2005). The tests were performed on 160 mm diameter specimens. The unbound granular material was tested at a constant dry density of 2,1 g/cm3 (97% of the optimum of the modified Proctor test), and at two different water contents: w = 4% and 5% (corresponding to water contents obtained in situ) (Hornych et al. 2007). In this paper, we present only the result obtained at water content: w = 4%. The Missillac sand was tested at a dry density of 2.04 g/cm3 (97% of the optimum of the modified Proctor test), and at a water content w = 11% (Allou et al. 2007). The cyclic tests have been performed at a frequency of 159

1 Hz, and in all tests, drained conditions were used (drainage outlets of the triaxial cell open to the atmosphere). The simplified model requires the elasticity parameters, Drucker-Prager parameters (the elasticity cone aperture ψ and the apex of the Drucker-Prager cone on the isotropic stress axis p*), the hardening modulus H and the function F(N). To determine the parameters of the model, three categories of tests were performed, for each water content: – three monotonic triaxial shear tests, with confining pressures σ3 = 10, 20 and 40 kPa. – one repeated load triaxial test to determine the non linear elastic behaviour. – three permanent deformation tests, with both cyclic axial stress and confining pressure, performed using the procedure proposed by Gidel (2001). It consists in applying, on the same specimen, several loading stages with the same stress ratio q/p, but with increasing stress amplitudes 3.1 Elasticity parameters The model parameters (Ka, Ga, n and γ) are obtained using repeated load triaxial tests results. The resilient behaviour test includes a cyclic conditioning (20000 load cycles with cyclic stresses p = 300 kPa and q = 600 kPa), to stabilize the permanent strains of the material and to attain the resilient behaviour. Then short loadings (100 cycles), following different stress paths, are performed to study the resilient behaviour. 3.2 Drucker Prager parameters The parameter p* = k/3α is the elasticity cone vertex position on the isotropic axis. It is identified by the failure line obtained from three monotonic triaxial shear tests. The parameter ψ = artg(3α 3 ) represents the elasticity cone aperture in the (p,q) stress space. It is determined to obtain a reduced initial elastic domain just before the plastic flow, where the elastic strain must be equal to 10−5 for low stress ratios q/p. 3.3 Plasticity parameters The plastic calculation requires two parameters: the hardening modulus H and the function F(N). These two parameters require an adjustment on repeated load triaxial tests results, with different stress ratios. Therefore, three permanent deformation tests, with both cyclic axial stress and confining pressure, were performed with the procedure proposed by Gidel et al. (2001). It consists in applying, on the same specimen, several loading stages with the same stress ratio q/p, but with increasing stress amplitudes: – stress ratios of 1, 2 and 2.5 were applied for the Maraîchères material. Each loading stage included 50000 cycles. – stress ratios of 1, 1.5, 2 and 3 were applied for the Missillac sand. Each loading stage included 10000 cycles.

Figure 2.

Evolution law of the hardening modulus for each q/p ratio (Maraîchères material, w = 4%).

160

The standard for the repeated load triaxial test suggests the following equation to relate permanent axial deformation with the number of cycles (Hornych et al. 1993): (20) ε p = F (N ) ⋅ A 1

where ε1p is the vertical plastic deformation; A is the limit value of ε1p when N tends towards the infinite and F(N) is the shape function defined in Equation 19. This model has been calibrated with the previous triaxial test results for each loading stage and water content. The simplified elastoplastic model is based on the shakedown theory and gives the stabilized plastic strains. With the experimental stabilized plastic strains, elasticity and Drucker Prager parameters, we determine the hardening modulus H and the parameter B, with the simplified method for each loading stage. We assume a linear evolution of the hardening modulus with the stress path length for each stress ratio (q/p), in the Log ⎡ pmin ⎤ , Log ⎡ H ⋅ Lmin ⎤ plane (Fig. 2), where ⎣ Δp ⎦ ⎣ pa L ⎦

)

(

Lmin =

2 2 pmin + qmin

and L = Δp2 + Δq 2

Thus, the hardening modulus is expressed hereafter: a

H = 10b ⋅

⎛p ⎞ L ⋅ ⎜ min ⎟ ⋅ pa Lmin ⎝ Δp ⎠

(21)

where a and b are material parameters, determined with linear regressions where the coefficients are function of the q/p ratio (Allou et al. 2007); Pa is the atmospheric pressure. To estimate the rut depth evolution with time (number of cycles), we use the same regression approach to determine the evolution law of B. We assume a linear evolution of the B parameter with the stress path length, the applied stress and the initial stress state of the material for each stress ratio q/p, in the ⎡ pmin ⎤ ⎡ Lmin ⎤ plane (Allou et al. 2007, Hornych et al. 2007). Thus , B⋅ L ⎣ Δp ⎦ ⎣ ⎦ we can write:

)

(

B=

⎛ L p ⎞ ⋅ ⎜ d + c ⋅ min ⎟ Δp ⎠ Lmin ⎝

(22)

where c and d are material parameters. These two parameters are defined with linear regression functions of the q/p ratio (Allou et al. 2007). 4

VALIDATION

In this section, a numerical simulation is presented to demonstrate the capabilities of the proposed model. The simplified method has been implemented in the non-linear finite elements code Cast3 m (Cast3 m 2005). 180 160 140

-4 p ε 1 (10 )

120 100 80 60

q/p =1

40

q/p =2 q/p =2.5

20

Model 0 0

50000

100000

150000

200000

250000

Number of cycles N

Figure 3. Comparison between the model and the experimental results (Maraîchères material, w = 4%).

161

With the evolution law of F(N), the plastic strain is determined as a function of the number of cycles, for several stages, with various q/p ratios. Figure 3 shows a comparison between the measured and calculated deformations. It can be seen that the proposed approach gives fairly good results. 5

NUMERICAL MODELLING OF LOW TRAFIC PAVEMENT STRUCTURE

This last part presents the application of the simplified method to the prediction of results of the LCPC full-scale pavement experiment. The finite elements modelling of a flexible pavement is performed with the finite elements code Cast3 m in three steps: – the first step is the pre-processing where the finite elements mesh is generated, load and boundary conditions are assigned and material properties are defined. – the second step is the elastic analysis where the minimum and the maximum stress fields are computed. This second step is very sensitive to the elastic parameters which have been used, and the convergence is sometimes difficult with the modified Newton method. Nevertheless it has been obtained for all the calculations. – the third step is the calculation of the plastic displacement and strain fields from the non linear elastic stress field. This last step doesn’t require classical elastoplastic finite element package but an algorithm allows to take into account the stress redistribution due to plasticity. 5.1 The finite elements analysis To illustrate the results obtained with the model, the rutting of a low traffic pavement structure tested on the LCPC accelerated pavement testing facility has been simulated (Hornych 2005). This pavement structure consists of: – a 6.6 cm thick bituminous wearing course. – a granular base and subbase, with a total thickness of 50 cm. – a clayey sand subgrade (thickness 2.23 metres), resting on a rigid concrete slab. A quarter of the 3D FE mesh is generated to simulate the response of the pavement structure, as shown in Figure 4. The FE model in this study requires 2200 cubical elements with 20 nodes. The gravity and lateral stresses are first applied to the pavement structure to establish the initial in situ stress states. Such initial stresses are determined with the materials unit weights and the lateral stress coefficient K0 which is assumed to be equal to 0.5. Then the pavement is subjected to a cyclic traffic loading which is the French Standard axle load (dual wheel half axle loaded at 65 kN), with 1 millions load applications. The loading area is rectangular, with a length of 0.30 m and a width of 0.18 m.

Figure 4.

Pavement structures considered and 3D finite element meshes.

162

5.2 Material properties The following material characteristics have been used for the calculation: – The bituminous concrete was assumed linear elastic, and its elastic modulus was determined from laboratory complex modulus tests, for a mean value of the temperature and a constant value of the loading frequency, corresponding to the in situ test conditions (T = 23°C, f = 12.5 Hz). The value of elastic modulus is equal to 6110 MPa. Its Poisson ratio was taken equal to 0.35. – The granular layer was described using the anisotropic Boyce model, using parameter values determined from laboratory cyclic triaxial tests (Hornych 2005). Parameters corresponding to the water content of 4% have been used (Table 1). – The subgrade soil was described using the anisotropic Boyce model, and parameters values determined from laboratory cyclic triaxial tests (Hornych 2003). Parameters corresponding to the water content of 11% have been used (Table 1). 5.3 Rut depth prediction With the simplified method, the inelastic displacement fields, the inelastic strain fields and the plastic strain fields are calculated at all Gauss points of the finite element mesh. The inelastic Table 1.

Parameters of the anisotropic Boyce model and Drucker Prager model. Non-linear elastic parameters

Maraîchères, w = 4% Missillac, w = 11%

Drucker Prager Parameters

n

Ka (MPa)

Ga (MPa)

γ

P* (KPa)

ψ (°)

0.34 0.514

21.9 24.2

41.6 29.9

0.55 0.638

40 12.8

15 15

20 18

Rut depth (mm)

16 14 12 10 Experience moy Experience min Experience max w = 4% w = 4% at limit state w = 5% w = 5% at limit state

8 6 4 2 0 0

500 000

1 000 000

1 500 000

2 000 000

2 500 000

Number of cycles N

Figure 5.

Comparison of measured rut depths and predictions.

14 12 p = 5kPa

Rut depth (mm)

10

p = 25kPa p = 5kPa-limit state

8

p = 25kPa-limit state 6 4 2 0 0

T

Figure 6.

500000

1000000

1500000

2000000

2500000

Number of cycles N

Comparison of predicted rut depth with and without cohesion (w = 4%).

163

vertical displacements at the surface of the pavement (rut depths) are obtained directly by the finite elements calculation. Four calculations have been performed, for N = 104, N = 105, N = 106, and N → ∞ (limit state). The results obtained are presented on Figure 5 (evolution of the rut depth with number of load cycles and at the limit state), and compared with the experimental measurements. This calculation leads to rut depths which are quite close in comparison with the experimental results. The final rut depths are not far from the minimum of the experimental measurements (the final values are 12.7 mm with the model at water content of 4% and 14.7 mm at water content of 5% compared with the minimum experimental value of 13.2 mm). However, the model leads to a much faster stabilization of permanent deformations than the experiment. These differences could be explained by the lateral wandering of the load, the variations of temperature and moisture content in the unbound layers, the stress rotations due to moving loads which are not taken into account in the calculations. Two Calculations have been performed on the same structure and at water content of 4%, considering two values of macroscopic cohesion. They are introduced in the elastic calculation, to take into account effect of unsaturated conditions: 40 kPa (real conditions of UGM) and a low value of cohesion (5 kPa). The results obtained are presented on Figure 6. We can see that the macroscopic cohesion can change the predicted rut depth by 50%, compared to the calculation without cohesion. The rut depth obtained after about 100 000 loads is 12.7 mm with cohesion and 6 mm without cohesion. 6

CONCLUSION

This paper describes a simplified model, based on the shakedown theory. This approach tries to keep the advantages of elastoplastic modelling: 3D structural calculation and realistic rheological model. This model requires 4 elasticity parameters and 4 plasticity parameters (H, B, ψ and p*). Elasticity parameters are determined from cyclic triaxial tests, using a procedure for the study of the resilient behaviour. Plasticity parameters require the determination of the macroscopic cohesion, the hardening modulus and the temporal function F. The evolution law of the hardening modulus and the temporal function F are determined with the calculation of the stabilized plastic strain, which requires multi stage cyclic triaxial tests on the UGM, under various stress paths and at different stress levels. Comparisons of the model calculations with results of cyclic triaxial tests have been presented, and fairly good results have been obtained. Finally, the finite elements modelling of a flexible pavement gives realistic rut depth levels. The model captures the general trend of the mechanical behaviour of the structure subjected to traffic loading and the influence of the number of loads on the rut depth. The first results are encouraging, taking into account the difficulty to model accurately the behaviour of a real pavement, subject to variable climatic conditions (temperature, moisture), which have a strong influence on the permanent deformation behaviour. The calculations performed have shown that the macroscopic cohesion, introduced in the elastic calculation, to take into account effect of unsaturated conditions can change the predicted rut depth by 50%, compared to the calculation without cohesion. REFERENCES Allou, F., Chazallon, C., Hornych, P. 2007. A numerical model for flexible pavements rut depth evolution with time. International Journal for Numerical and Analytical Methods for Geomaterials, DOI 10. 1002-NAG: 521. CAST3M 2005. CAST3M is a research FEM environment; its development is sponsored by the French Atomic Energy Commission, at, http://www-cast3 m.cea.fr/cast3 m. Gidel, G., Hornych, P., Chauvin, J.J., Breysse, D., Denis, A. 2001. Nouvelle approche pour l’étude des déformations permanentes des graves non traitées à l’appareil triaxial à chargement répétés. Bulletin de liaison des Laboratoire des Ponts et Chaussées: 5–22.

164

Habiballah, T.M., Chazallon, C. 2005. Cyclic plasticity based model for the unbound granular materials permanent strains modelling of flexible pavements. International Journal for Numerical and Analytical Methods in Geomechanics 29: 577–596. Hornych, P. 2003. Rapport interne confidentiel. L.C.P.C. de Nantes. Hornych, P. 2005. Rapport interne confidentiel. L.C.P.C. de Nantes. Hornych, P., Chazallon, C., Allou, F., El Abd, A. 2007. Prediction of permanent deformations of unbound granular materials in relation with the moisture content. To appear in the International Journal of Road Materials and Pavement Design. Hornych, P., Corte, J.F., Paute, J.L. 1993. Etude des déformations permanentes sous chargements répétés de trois graves non traitées. Bulletin de Liaison des Laboratoires des Ponts et Chaussées, No. 184: 45–55. Hornych, P., Kazai, A., Piau, J.M., 1998, Study of the resilient behaviour materials, Proc. 5th Int. Conf. on the Bearing Capacity of Road and Airfield, Balkema editor, Vol. 3, pp. 1277–1287. Maier, G., Pastor, J., Ponter, A.R.S., Weichert, D. 2003. Direct methods of limit and shakedown analysis. Numerical and Computational Methods 12 (3); R. de Borst and H.A. Mang editors, Elsevier—Pergamon, Amsterdam. Sharp, R., Booker, J. 1984. Shakedown of pavements under moving surface load. Journal of Transportation Engineering, pp. 1–14. Yu, H.S., Hossain, M.Z. 1998. Lower bound shakedown analysis of layered pavements discontinuous stress fields. Computer Methods in Applied Mechanics and Engineering 167: 209–222. Zarka, J., Casier, J. 1979. Elastic plastic response of structure to cyclic loading: practical rules. Mechanics Today 6; Ed Nemat-Nasser, Pergamon Press: 93–198.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Effect of grading and moisture on the deformation properties of unbound granular aggregates L.U. Mathisen Kolo Veidekke AS, Norway

ABSTRACT: Many test methods have been developed over the years to test the water sensitivity of unbound materials. One of the recent methods is the Tube Suction test, which is used in this study to find the influence of grading on the water sensitivity of a material. This test utilizes the dielectric properties to measure the ability of the material to suck water. Cyclic load triaxial testing is used to study the effect of grading and moisture on the deformation properties of the material tested. By adding different amounts of water to samples with the same grading, the sensitivity to changes in degree of saturation is seen. The study shows that the deformation properties are affected by the level of saturation, especially for gradings with higher amounts of fines. 1

INTRODUCTION

Water is needed in unbound materials during compaction to achieve high levels of compaction. In this case the water acts as a lubricant between the grains, allowing them to slide into the most effective packing when using proper compaction equipment. During springtime the materials in the road are often subjected to extreme environmental conditions, and water may be trapped in the base course and sub base layer. The melting starts mainly at the surface but also from the subgrade, leaving a frozen layer that acts as an almost impermeable layer somewhere in the structure. Water from the melting and even water from the sides and through the asphalt may thus be trapped in the unbound material, dependent on the permeability of the material and the drainage conditions of the road structure. The effective stresses in the structure are reduced and an excess pore water pressure may occur. In many countries the sensitivity to water is indirectly accounted for in the design guidelines by requirements regarding gradation and limitations on the amount of material smaller than 0.063 mm or 0.020 mm. These requirements are based on the assumption that the gradation is the main parameter deciding the pore size distribution in the material, and thereby also the permeability and the ability to keep water inside the material. The objective of this study is to test one material composed into four different grain size distributions to study the effect of grading on the water sensitivity of a material both by the Tube Suction test and by cyclic load triaxial testing of the material at different degrees of saturation. 2

WATER SENSITIVITY IN UNBOUND GRANULAR MATERIALS

It is found that the sensitivity to water is dependent on more than gradation and fines content. Parameters as mineralogy, specific surface area of fines, grain shape may in some cases cancel out the effect of gradation or amount of fines (Uthus et al 2006). Christine Hauck (Hauck 1989) studied the water sensitivity of gravel in her candidatum scientarius thesis at the University in Oslo by studying parameters like grading, fines content, mineralogy, plasticity and grain shape and by using CBR as a measure of the strength of the material. 167

The conclusions from this work was that the water sensitivity of a material should better be classified by the amount of material passing the 0.075 mm sieve, and the study showed that the amount of material <0.020 could vary in the range 50–90% of the total material smaller than 0.075 mm without affecting the stability dependent on the material type. It was also concluded that aggregate from schist and limestone and fines with high plasticity index should be avoided. This is because of possibly reduced internal friction and thereby an increasing possibility of pore pressure development. This study was the basis of the requirements in the Norwegian specifications today, which requires 8% or less material passing the 0.063 mm sieve of material smaller than 20 mm (Vegdirektoratet 2005). The ability of a material to suck water may be a measure of the water sensitivity. The Tube Suction test was developed by the Finnish National Road Administration and the Texas Transportation Institute (Saarenketo et al. 1997) to determine the moisture susceptibility of an unbound material. This is a relatively new test that classifies the materials by the measured dielectric value after 10 days of water suction. The dielectric value of a sample with three phases of materials; aggregates, water and air, depends on the volumetric distribution of these three different phases and the dielectric constant of each of them. Saarenketo and Scullion (Saarenketo et al. 1997) listed typical dielectric value for several materials, where air has a dielectric value of 1, dry aggregates has a dielectric value of 4 to 6, and free water has a dielectric value of 81. The dielectric value of tightly bound water is about 3 or 4 (Guthrie et al. 2001). As the free water has a very high dielectric value compared to the other constituents of an aggregate sample, the total dielectric value measured on the top of a cylindrical sample is very sensitive to free water, which is measured in the mix after 10 days of suction. 3

MATERIAL PROPERTIES

One material was used in this study, and only the grain size distribution was varied. The material was gneiss from a quarry in Askøy outside Bergen in Norway. This is a fine-grained rock where the main minerals determined by thin section analysis are quartz (47%) and feldspar (44%) with some amount of the minerals amphibole (5%) and titanite (2%). In the fines

100

Percentage passing sieve

90 80 70 60

n = 0.25 50 40

PPP

30

n = 0.35

20

n = 0.5

Sieve size (mm) Figure 1.

Grain size distributions of the materials used in the study.

168

8.0 11.2 16.0 22.4 31.5

4.0

2.0

1.0

0.500

0.250

0.125

0

0.063

10

>0.020 mm the main minerals found by X-ray diffraction (XRD) are plagioclase (31%), alkali feldspar (31%) and quartz (27%) with some amount of mica (8%) chlorite (2%) and amphibole (2%). In Figure 1, the three main grain size distributions are presented together with a fourth grading only used in the Tube Suction test, as a more extreme grading. The curves marked with n = 0.35 and n = 0.5 are both material with gradation 0/22 mm and two different grading coefficients normally used as unbound road materials. The grading coefficient n = 0.25 represents a material with far too high fines content according to the Norwegian specifications. The grain size distribution denoted PPP is the upper limit curve of a grading used in a Public Private Partnership project (PPP) in the southern part in Norway, 0/32 mm. In the Norwegian guidelines the requirements for non-water susceptible soils are defined by the amount of material smaller than 0.063 mm for unbound base materials. For crushed rock the maximum amount of fines ≤0.063 mm is 8% within the material smaller than 20 mm. This means that the two lower curves are within the limits, while the two upper curves are above the limit given in the Norwegian requirements. 4

TEST METHODS

4.1 Tube Suction Test The procedure has been under constant development, and there is still no standard method. In this study the procedure described by Guthrie et al. (2001) was used, with some modifications. A cylinder with an inner diameter of 149 mm and a height of 304.8 mm was used; in Guthrie et al. the diameter of the cylinder was 152.4 mm. About 6 mm from the bottom of the cylinder holes with diameter 3 mm were drilled around the circumference for water intake. The spacing between the holes was 12.7 mm and 4 additional holes were drilled in the bottom of the cylinder. Guthrie et al. (2001) described holes with 1.6 mm diameter, but these would probably easily clog. The samples were compacted at optimum moisture content in the cylinder in four layers to a final height of 200 mm by using a Modified Proctor hammer with 50 strokes per layer with a weight of 4.5 kg dropped from a height of 457 mm. The compacted samples were dried in an oven for four days in 40°C (45°C until constant mass). Then they were placed in water bath with distilled water reaching 12.7 mm over the bottom of the sample for 10 days. The measurements in the Tube Suction test are based on measuring the dielectric properties of the material. This value is defined as the ratio of the materials dielectric permittivity to the dielectric permittivity of free space. This gives a measure of the amount of free water in the sample. Measurements of the dielectric value and electrical conductivity were done during 10 days on the top surface of the samples. The equipment used is a PercometerTM with a surface measurement probe. This equipment measures 25 mm into the material according to the instrument specifications. 18 measurements were done for each sample each time, where the three lowest and the three highest readings were discarded to reduce the variability caused by surface imperfections. Three different gradings were used throughout this study, but none of them were extreme gradings, therefore another grading was added as a control to represent a more extreme

Table 1. Classification of materials by dielectric value. Dielectric value

Classification

<10 10–16 >16

Good Marginal Poor

169

700

Deviatoric stress - q [kPa]

600 500 400 300 200 100 0 0

Figure 3.

100 200 300 M ean stress - p [kPa]

400

Loading procedure.

grading, expected to be water susceptible. This was a grading with n = 0.25, giving about 23% material smaller than 0.063 mm. Only one sample was made for each grading. The maximum aggregate size should not exceed 25 mm, because of the size of the cylinder. One of the gradings in this study is 0/32 mm, the PPP curve. Saarenketo & Scullion (1997) suggested removing the larger aggregate grains, but in this case this was not done. To make a smoother surface of the compacted samples some finer material (1/2 mm) of the same material was added on the top of each sample Guthrie et al. (2002) suggested a classification for water sensitivity of materials by their mean dielectric value after 10 days of water absorption. This is presented in Table 1. 4.2 Cyclic load triaxial testing The deformation properties of the materials were found by cyclic load triaxial testing of cylindrical samples. In this study the samples were compacted in five layers at optimum moisture content using a Kango vibrating hammer. The European standard EN-13286-7 (CEN 2000) for triaxial testing of unbound mixtures offers a procedure called multistage loading for investigation of permanent deformations. In this procedure loading is run in five sequences of constant confining stresses (20, 45, 70, 100 and 150 kPa) with increasing deviatoric stress within each confining stress level. The principles of the loading procedure are shown by the stress paths in Figure 3 for “high stress levels”. Loading is applied at a frequency of 10 hertz with 10 000 cycles per deviatoric stress level and interrupted when the permanent axial strain reaches 0.5%. By interrupting the axial loading at this permanent strain level, the sample is still relatively far from its ultimate stress level/failure limit. Thus the next load sequence may be applied to the material while still being within a design stress level. The triaxial chamber is filled with water as a confining medium during the triaxial testing. In this case, strain was measured with three radial and three axial LVDTs (Linear Variable Displacement Transducers). The LVDTs for the radial measurements were mounted on the sample using clamps, while the axial LVDTs were mounted on the bottom plate to measure the axial deformation between the top and bottom plate. In attempt to saturate the material, water was added from the bottom of the sample and excess water was drained through the top. Water was added to the sample at a pressure of 20–25 kPa, under a confining stress of 20 kPa. Air was used as a confining medium in the triaxial chamber during the saturation process. The saturation process was stopped when the amount of water draining out from the top of the specimen was equal to the water added from the bottom. The sample was then left to equalize for about 12 hours under drained conditions. The degree of saturation was determined from the amount of water in the sample 170

10

9,91 n=0.5 PPP n=0.35 n=0.25

9 8

Dielectric value

7 6 5,57 5,37

5

4,23

4 3 2 1 0 0

20

40

60

80

100

120

140

160

180

200

220

240

Time [hr]

Figure 4.

Dielectric value as a function of time for the samples.

400 n=0.5 PPP n=0.35 n=0.25

350

351 321

300

Water uptake [g]

276 253

250

200

150

100

50

0 0

20

40

60

80

100

120

140

160

180

200

220

240

Time [hr]

Figure 5.

Water uptake as a function of time.

and the amount of drained water after testing. With this setup it was not possible to saturate any of the samples up to 100%. Only one sample was tested for each combination of gradation and degree of saturation. 5

RESULTS

5.1 Tube Suction test The results from the measurements of dielectric values on the surface of the sample over a period of 10 days are presented in Figure 7. Here the results seem to be lowest for the grading with the lowest fines content, n = 0.5, and highest for the grading with highest fines content, 171

Table 2.

Properties of the samples tested.

Gradation

n = 0.5

PPP

n = 0.35

n = 0.25

Dielectric mean value Standard deviation Absorbed water (g) Dry density (g/cm3) Degree of saturation (%)

4.23 0.82 253 2.19 40.1

5.37 0.16 276 2.25 39.9

5.57 0.42 321 2.28 58.6

9.91 0.64 351 2.27 59.9

800 Sr = 49 % Sr = 67 % Sr = 81 % Trendline Sr = 49 % Trendline Sr = 67 % Trendline Sr = 81 %

Resilient modulus [MPa] .

700 600 500 400 300 200 100 0 0

50

100

150

200

250

300

350

400

450

Mean stress [kPa]

Figure 6.

Resilient Modulus as a function of mean stress for grading n = 0.5.

n = 0.25. The PPP grading and the grading with n = 0.35 both show very stable and low dielectric value for the last measurements. The grading with n = 0.35 also have quite stable values, but for the last measurement it seems to decrease slightly. This is probably random, as the dielectric value seems to fluctuate slightly. The curve with grading coefficient of n = 0.25 show higher values than the other gradings. The last three readings show an increasing trend, and the last reading is 9.91. This sample should probably have been measured for a few more days to see at what point the dielectric value stabilizes. The last reading for this grading is very near the threshold value of 10 defined for moisture susceptible materials. Figure 5 presents the water uptake as a function of time for the samples tested. This shows a distinct difference between the four gradings, showing that the ability of a material to suck water is dependent on the grading and the content of fines. In Table 2 several properties for the samples tested are presented. As can be observed the degree of saturation increases with decreasing grading coefficient. The PPP grading seems to give a slightly lower degree of saturation compared to the grading with n = 0.5. When it comes to the dry density of the samples this seems to increase with increasing fines content except for the grading with n = 0.25, which shows a small decrease in dry density compared to the grading with n = 0.35. However, the increase in water uptake is less than indicated from the last three readings of the dielectric value in Figure 4. It is hard to give a good explanation of this. 5.2 Cyclic load triaxial testing The average resilient modulus for the 10 000 load cycles in one load step is presented in Figures 6–8. A load step is defined as the combination of a confining stress and a cyclic deviatoric stress. When interpreting these results it is important to remember that only one sample was tested for each combination of degree of saturation and grading. Figure 6 shows the resilient modulus as a function of the mean stress (σm = (σd + 3σ3)/3) for the material with the well-graded curve, n = 0.5. In this case the highest obtained degree 172

700 Sr = 34 % Sr = 66 % Sr = 85 % Trendline Sr = 34 % Trendline Sr = 66 % Trendline Sr = 85 %

Resilient modulus [MPa] .

600

500

400

300

200

100

0 0

50

100

150

200

250

300

350

400

450

Mean stress [kPa]

Figure 7.

Resilient Modulus as a function of mean stress for grading n = 0.35.

700

Sr = 39 % Sr = 58 % Sr = 68 % Trendline Sr = 39 % Trendline Sr = 58 % Trendline Sr = 68 %

Resilient modulus [MPa] .

600

500

400

300

200

100

0

0

50

100

150

200

250

300

350

400

450

Mean stress [kPa]

Figure 8.

Resilient Modulus as a function of mean stress for grading PPP.

Figure 9.

Elastic and plastic limits for grading n = 0.5.

of saturation was 85%. The sample with the lowest degree of saturation (49%) shows the highest resilient modulus. All specimens have about the same resilient modulus for low stress levels. For the higher stress levels however, the specimen with Sr = 81% have a lower resilient modulus than the other two; Sr = 67% and Sr = 49% respectively. In Figure 7 the resilient modulus for the samples with curve n = 0.35 is presented. Also here the degree of saturation is maximum 85%. Here the sample with the lowest degree of saturation (34%) has a significantly higher resilient modulus for all stress levels tested. The two other samples presented have close to equal resilient response, being lower than for Sr = 34%. This shows that the material with n = 0.35 is more affected by smaller changes in water content, thus being more water susceptible than the more open graded material with n = 0.5 173

shown in Figure 9. It is also worth to remark that for n = 0.5 the significant reduction of the resilient modulus occurred at Sr = 81% while the drop in the modulus for n = 0.35 occurred at a lower degree of saturation; Sr = 66%. In Figure 8 the data from the samples with the PPP-curve is presented. Here we observe the same tendency as for the n = 0.35 grading, but not as pronounced. The sample with the lowest degree of saturation has the highest resilient modulus for all stress levels, while the samples with 58 and 68% saturation respectively, have almost identical behaviour. For this grain size distribution we did not achieve as high degree of saturation as for the other two, only 68% at the highest, giving some limitations in the interpretations. The main principles of the method for interpretation of the permanent deformation behaviour are described in Hoff et al. (2003), who classified the permanent deformation behaviour of unbound materials into three different classes ranging from purely elastic response to failure by the observed strain rate of the last 5000 to 10000 cycles. The elastic limit is defined as the stage where the strain rate of the last 5000 cycles in a load step is so low that permanent deformations do not occur, while the plastic limit is defined as the stage where the strain rate of the last 5000 cycles indicates increasing permanent deformations. When interpreting the data, all load steps are classified into 3 stages; elastic, elasto-plastic and purely plastic behaviour. When plotted in a σ3-σd-plot this gives relatively clear elastic and plastic limits. For interpretation regarding permanent deformation behaviour the angles ρ and ϕ, corresponding to the elastic and plastic limit, is used.

Figure 10.

Elastic and plastic limits for grading n = 0.35.

Figure 11.

Elastic and plastic limits for grading PPP.

174

800 n=0.5, Sr = 67 % PPP, Sr = 68 % n=0.35, Sr = 66 % Trendline n = 0.5 Trendline PPP Trendline n = 0.35

Resilient modulus [MPa] .

700 600 500 400 300 200 100 0 0

50

100

150

200

250

300

350

400

450

Mean stress [kPa]

Figure 12. Resilient modulus as a function of mean stress for all three gradings with near the same degree of saturation.

Figure 13. Elastic and plastic (“Failure”) limits for all three gradings with near the same degree of saturation.

In Figure 9 the elastic and the plastic limit for the grading of n = 0.5, is presented in combination with the dry density for each sample. The resistance to permanent deformations seems to be reduced as the degree of saturation increases. In addition the dry density also seem to have an effect on the permanent deformation behaviour as the two samples with the lowest degree of saturation seem to follow the dry density. The highest degree of saturation achieved here was 81%, which is still quite far from full saturation. However, there is a trend towards pronounced reduction in the resistance to permanent deformations for the highest degree of saturation. In Figure 10 the permanent deformation behaviour for the grading with n = 0.35 is shown. For this grading the reduction in resistance to permanent deformations with increasing degree of saturation is more pronounced than for n = 0.5. The degree of saturation seems in this case to override the effect of dry density, which in fact is increasing. The highest degree of saturation also here is 85%, and the strength would probably continue to decrease for higher degrees of saturation. We observe a significant drop in sin ρ even at Sr = 66%. Compared to the samples with n = 0.5 the samples with n = 0.35 have a lower resistance to permanent deformations for low degrees of saturation and drops dramatically for increasing saturation. Figure 11 shows the elastic and plastic limit for the PPP grading. The trend is not as clear as for the other two grain size distributions, as it seems like the sample with a low degree of saturation has a lower resistance to permanent deformation even if the dry density for this sample is slightly higher than the sample with 58% saturation. The resistance to permanent deformations decreases from 58% saturation to 68%, which follows the decrease in dry 175

density. For this grading only 68% saturation is achieved, this is low compared to the other two grain size distributions. In Figure 13 the elastic and plastic limits for the three gradings with near the same degree of saturation are presented. The trend shows that the resistance to permanent deformations is significantly reduced with higher fines content (n = 0.35 and PPP). The densities for the samples are about identical, so this should not influence the results significantly. A second observation is that the material seems to have a larger area of elasto-plastic behaviour before “failure” for the gradings with more fines, as the difference between the elastic and plastic threshold limits is larger.

6

DISCUSSION

When studying the dielectric measurements from the Tube Suction test, the results seem reasonable from the information we have about grading, fines content and mineralogy of the material used. The most extreme grading with respect to fines content is the most water sensitive grading found by the Tube Suction test. However, only one sample from each grading was tested, and according to Guthrie et al. (5) the method has some variability. From the single samples we observe that the three main gradings, n = 0.5 and n = 0.35 and the PPP grading, are classified as non-moisture and non-frost susceptible by the suggested classification table presented in Guthrie et al. (7). The more extreme curve with grading coefficient of n = 0.25 may be characterized as moisture susceptible by this table, as the dielectric value is about 10 and seems to be increasing even to a higher value at the end of the test period. In this test series we did not succeed in achieving 100% saturation of the samples for triaxial testing. We did not use de-aired water, but this would probably have a marginal effect. It seems like the PPP curve was the hardest to saturate, as the highest degree of saturation achieved was 68%. The cyclic load triaxial testing shows a marked difference in the sensitivity to changes in the degree of saturation on the resilient modulus, showing the material with n = 0.35 to be the weakest. For the other two gradings the resilient modulus seems to be highest for a possible optimum degree of saturation. All three gradings show the lowest resilient modulus for the highest degree of saturation, even though the samples were not fully saturated. This shows that when the degree of saturation exceeds a certain level, the resilient modulus decreases. As this effect is more pronounced for the two gradings with the highest fines content, it seems like the fines content affect the sensitivity to changes in water content with respect to the obtained resilient modulus. When it comes to the permanent deformation behaviour, the samples with n = 0.5 are mainly affected by the dry density for the two lowest water contents. For the highest degree of saturation the resistance to permanent deformations decreases even if the dry density is slightly increasing. For the material with n = 0.35 the degree of saturation seems to be the key factor controlling the permanent deformation behaviour. In this case, the resistance to permanent deformations decreases dramatically with increasing degree of saturation from 34% to 85%. This is true even when the dry density increases. The samples with the PPP grading are obviously influenced by both the degree of saturation and the density. For the lowest degree of saturation (39%) the resistance to permanent deformations is lower, even if the dry density is higher for this sample compared to the other samples. The sample with the highest degree of saturation is influenced by both the dry density and the degree of saturation as the elastic and plastic limit decreases with decreasing dry density and increasing saturation. By comparing samples with equal degree of saturation of about 68%, the effect of the different gradings and changes in dry density may be more evident. Regarding the resilient deformation behaviour, the material with n = 0.5 show a significantly higher resilient modulus that the other two gradings. The material corresponding to the PPP grading and the material with n = 0.35 show similar behaviour for all stress levels even if the PPP sample have a higher dry density. This means that the resilient modulus decreases with increasing fines content for this degree of saturation. 176

The permanent deformation behaviour shows the same trend, as the material with grading coefficient n = 0.5 has the highest elastic and plastic limit. The material with the PPP grading have almost identical plastic limit as the material composed with n = 0.35 and a higher elastic limit for a higher dry density. This means that for this degree of saturation the resistance to permanent deformation decreases with increasing fines content. 7

CONCLUSIONS

Tube Suction test seems to be a fairly good method to detect sensitivity to water for the four different grain size distributions in this study, as the dielectric constant increases with increasing fines content and water content. However, none of the materials were classified as water sensitive. The degree of saturation affects the resilient modulus of the different grain size distributions significantly, as the resilient modulus decreases when the degree of saturation reaches a certain level. Increasing fines content makes the resilient modulus decrease also at a lower degree of saturation. The resistance to permanent deformations also decrease with increasing degree of saturation, except for the PPP grading which is influenced by the dry density. Resilient modulus and the resistance to permanent deformation decreases for increasing fines content for the samples tested. Low fines content seems to give more stable performance of unbound materials even under fluctuating water contents. The findings in this study should be further verified by testing more materials and also more extreme gradings. In this study the number of samples is on a minimum level, so more testing should be done to have more confidence regarding the results. ACKNOWLEDGEMENTS The author wishes to appreciate the support of Professor Ivar Horvli at NTNU and Inge Hoff at SINTEF during the work with this paper. Stein Hoseth at NTNU is greatly acknowledged for assistance in the laboratory REFERENCES CEN—European Commite for Standardization. (2000) Unbound and hydraulically bound mixtures— part 7: Cyclic load triaxial tests for unbound mixtures EN 13286-7. Brussels. Guthrie, W.S., Ellis, P.M. and Scullion, T. (2001) Repeatability and Reliability of the Tube Suction Test. Paper no 01-2486 Transportation Research Record 1772, Transportation Research Board, Washington DC, USA. Guthrie, W.S., Hermansson, Å. and Scullion, T. (2002) Determining Aggregate Frost Susceptibility with the Tube Suction Test. Proceedings for the 11th International Conference on Cold Regions Engineering, Anchorage, Alaska, pp. 663–674. Hoff, I., Bakløkk, L. and Aurstad, J. (2003) Influence of Laboratory Compaction Method on Unbound Granular Materials. Proceedings for the 6th International Symposium on Pavements Unbound (UNBAR 6) (CD-ROM), University of Nottingham, Great Brittain. Hauck, C. (1989) Water sensitivity of gravel materials (In Norwegian). Cand. Scient thesis, University of Oslo, Norway. Uthus, L., Hermansson, Å., Horvli, I. and Hoff, I. (2006) A study on the influence of water and fines on the deformation properties and frost heave of unbound aggregates. Proceedings for the 13th International Conference on Cold Regions Engineering (CD ROM), Orono, Maine, USA. Saarenketo, T. and Scullion, T. (1997) Using Suction and Dielectric Measurements as Performance Indicators for Aggregate Base Materials. Transportation Research Record 1577, Transportation Research Board, Washington DC, USA. Vegdirektoratet (2005). Håndbok 018 Vegbygging (In Norwegian), Oslo, Norway.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

IDOT test loop: Evaluating the field performance of various dense graded aggregates G. Heckel Illinois Department of Transportation District 6, Springfield, Illinois, USA

ABSTRACT: The Illinois Department of Transportation frequently utilizes dense graded aggregates to provide a stable platform for pavement construction. The performance of three dense graded aggregates having different physical characteristics, construction methods, and thickness was evaluated under controlled loading conditions in a full scale test loop. Prior to paving, test locations were subjected to up to 270 passes by a loaded tandem axle truck. Aggregate rutting at each test location was measured at regular intervals during loading. The results identified three primary factors affecting performance: 1) aggregate angularity, fines content, and fines plasticity; 2) aggregate layer moisture content and compaction; and 3) loading. The test loop results also indicated aggregate properties, rather than underlying soil stability and aggregate thickness, control performance when the soil subgrade has a CBR of approximately 5 or greater. The results show pavement construction platform thickness can be optimized for performance and economy by considering aggregate properties and construction methodology. The results also indicate some aggregates have properties making them inappropriate for use as a pavement construction platform. 1

INTRODUCTION

New pavements constructed by the Illinois Department of Transportation (IDOT) require an improved subgrade to ensure adequate support for constructing successive pavement layers. IDOT specifications require an improved subgrade to limit rutting to 13 mm during paving. Dense graded aggregates are frequently used to provide this support. Current Illinois pavement design policy requires this layer to be a minimum 300 mm thick regardless of the material used (IDOT, 2002). IDOT’s pavement design methodology does not include an aggregate improved subgrade in the structural design of pavements. IDOT specifications and various special provisions allow a wide variety of aggregates for improved subgrade applications. This reflects the reality that the material used on a particular project depends on what is economically available in the area. For example, aggregates can range from uncrushed gravels to crushed limestone with up to 12% fines. Depending on the construction specification, some aggregates have limits on fines plasticity, and others have no limit. Compaction can also range from meeting the subjective visual requirements of an inspector to having a specific density requirement. Anecdotal evidence based on years of experience with the different types of aggregate available throughout the state suggests IDOT could achieve greater economy in the use of aggregates. Cost savings could be achieved directly by reducing the required thickness when a better performing aggregate is used. Savings could also be achieved indirectly by reducing the use of aggregates that perform poorly in improved subgrade applications. IDOT uses approximately 1.7 million metric tons of aggregate in improved subgrade applications annually. With an average cost per metric ton in 2006 of $14, IDOT spends approximately twenty-nine million dollars per year for aggregate improved subgrades. If a 30% reduction in thickness can be achieved, IDOT could realize an annual savings of approximately nine million dollars. 179

There are a significant number of studies available investigating various aggregate properties and their effect on strength parameters in a laboratory setting. Resources such as The Aggregate Handbook (Barksdale, 1991) and NCHRP Report 453 Performance-Related Tests of Aggregates for Use in Unbound Pavement Layers (Saeed et al., 2001) provide a good overview of laboratory testing and behavior. Compared to the laboratory resources, there are a more limited number of field studies focused on directly evaluating different aggregates under controlled conditions. The Minnesota Department of Transportation constructed an experimental Low-Volume Road test loop where different aggregates were subject to controlled loading (Lukanen, 1997). The Lowell Test Road evaluated aggregate surface rutting of different aggregate types and thickness (Truebe and Evans, 1995). This project examines the relationship between aggregate properties, construction methods, loading, thickness and rutting under controlled construction and loading conditions. A test loop was incorporated into a new expressway construction project in fall 2003. The test loop incorporated crushed limestone, uncrushed gravel, and reclaimed asphalt pavement. Reclaimed asphalt does not typically meet the definition of a dense graded aggregate, but was included in this study because of the large quantity available in some parts of Illinois. The materials were placed at different thickness using varying compaction requirements and were subjected to controlled loading by tandem axle trucks. The performance of each material was compared to a crushed limestone control section incorporated within each test section. The control section represented the required 300 mm thickness and compaction method used on a majority of projects in IDOT’s District 6 at the time. 2

TEST LOOP INFORMATION

2.1 Aggregate properties Aggregate used in the test loop consisted of uncrushed gravel, crushed limestone (CLS), reclaimed asphalt pavement milled from surface (RAP-SM), and a coarser reclaimed asphalt pavement milled from a combination of base and surface (RAP-BM). All CLS materials were from the same source. Table 1 shows the average gradations of aggregates used in the test loop. With the exception of RAP materials, Atterberg limits were determined on the fraction smaller than 0.425 mm according to AASHTO T 89 and T 90. The CLS fines were non-plastic, while the gravel fines had a plasticity index of 19. While no specific test was performed to quantify angularity, the CLS may be generally characterized as angular with a rough surface texture. The gravel was rounded with a smooth surface texture, and the RAP included a mixture of angular and rounded particles with a smooth surface texture. The maximum laboratory density of each aggregate was determined according to AASHTO T 99, and the CBR was determined according to an IDOT test method for Illinois Bearing Ratio, which uses a hydraulic ram to compact the specimen and is considered equivalent to CBR (IDOT, 1999). Table 2 shows maximum density and CBR data for each aggregate. The CBR data shown in Table 2 for CLS and gravel demonstrates how moisture content can have a significant effect on aggregate layer stability. For example, the CLS data shows a significant decrease in CBR as the moisture content increases. Given the fines content described in Table 1, the same inter-particle lubrication that increases density can also reduce

Table 1.

Average gradations in percent passing of dense graded aggregates used in the test loop.

Aggregate 25.4 mm

19.1 mm

12.7 mm

9.5 mm

4.75 mm 1.18 mm

0.425 mm

0.075 mm

CLS Gravel RAP-SM RAP-BM

87.4 90.4 94.4 84.0

72.0 75.0 85.2 68.6

64.0 65.8 74.4 54.1

42.6 52.5 42.2 30.4

17.0 17.0 3.4 4.2

11.7 6.9 0.7 1.7

97.4 97.6 96.6 90.5

180

23.8 27.9 11.3 10.4

Table 2.

Average maximum density and average CBR data for aggregates used in the test loop. Optimum moisture content, OMC %

Aggregate

Maximum dry density kg/m3

CLS

2150

9.6

93.2 96.2

44 80

97 34

Gravel

2210

9.4

91.5 99.5

32 96

68 45

RAP-SM RAP-BM

1810 1860

10.5 10.1

93.3 98.5

40 32

17 23

Table 3.

CBR specimen % compaction %

CBR specimen % of OMC %

CBR at 5 mm penetration

Subgrade soil characteristics corresponding to each aggregate type.

Aggregate

AASHTO class

Average CBR*

Passing 0.075 mm %

Silt content %

Liquid limit

Plasticity index

Moisture content %

CLS Gravel RAP

A-6(10) A-6(12) A-6(13)

4.9 5 5.5

95 68 90

75 36 67

29 38 32

12 20 15

15 13 19

* CBR was determined in-situ using a dynamic cone penetrometer.

stability as moisture content approaches optimum. The low CBR values shown for RAP materials predict poor field performance, which is verified in Section 3.2. 2.2 Subgrade properties Samples of subgrade soils were obtained for classification, and dynamic cone penetration tests were performed prior to placing aggregate. Subgrade soils were classified based on AASHTO M 145, AASHTO T 88, T 89, and T 90. Table 3 shows selected subgrade soil characteristics within the top 600 mm below the aggregate layer. 2.3 Test loop construction A 335 meter test loop was incorporated into the US 67 Expressway construction project south of Jacksonville, Illinois. Adjacent sections of northbound and southbound subgrade in cut were selected for the test loop. Each section was divided longitudinally into 4 meter wide test and construction lanes. The construction lane enabled material to be delivered and stockpiled without loading the test lane with heavy trucks. The loop area was excavated to a depth 600 mm below plan top of subgrade elevation. The bottom of the excavation was not compacted prior to placing aggregate. Aggregates were placed in maximum 150 mm layers on the test lanes using an excavator, and grading to the desired aggregate thickness was performed using a small motor grader. Each layer was compacted using a smooth-drum vibratory roller. Compaction effort varied depending on the requirements of a particular test segment. Aggregates were compacted between 2 and 6 days prior to loading. A 38 mm rainfall also occurred after constructing the CLS test section. The gravel and RAP sections, with their CLS control sections, had not been placed prior to the rainfall. The short time interval and rainfall resulted in a severe case where aggregate “set-up” may not occur and the aggregate may have excessive moisture infiltration. As a result, test loop conditions represent a “real-world” scenario that often causes problems. 181

Table 4.

Summary of test location characteristics.

Aggregate

Range of thickness, T mm

Compaction specification

Gravel CLS RAP-SM RAP-BM CLS-Control

250–300 150–300 200–300 200–300 300

Visual 95%* and visual Visual Visual Visual

* CLS requiring 95% compaction has water added prior to delivery.

For all test locations, aggregate layer density was determined in the field using 100 mm to 150 mm direct transmission nuclear methods according to AASHTO T 310. Field moisture contents were determined using oven-dry methods according to AASHTO T 265. Because of the difficulty involved with grading aggregate to a variable depth, actual test locations were determined based on comparing a detailed survey before and after placing aggregate. Due to construction variability, some locations with a particular desired aggregate thickness could not be identified. Test locations were grouped according to the specific aggregate types being compared and similarity of soil conditions. 2.4 Test loading and rut measurement Four tandem axle trucks made maximum of 270 passes over test locations. The average gross truck weight was 216 kN. Using a 25%–75% front-rear load split, the load on the dual wheel tandem axle was 162 kN, and the load on the front single axle was 54.2 kN. The average tire pressure on the tandem axle was 650 kPa, and the average tire pressure on the front axle was 730 kPa. Unfortunately, the size of the tires was not recorded. Ten to twenty passes were made on each test location between each rut measurement. Rut measurements were made using a straight edge in four locations within each test location. Two measurements were taken on each side in an effort to minimize the potential for erroneous data. When rutting became excessive, trucks were diverted onto the construction lane. Trucks made loops between northbound and southbound lanes. Trucks ran continuously for approximately 7 hours, with the exception of short hourly breaks and lunch. The maximum 270 passes was sufficient to model most construction situations. For example, approximately 60 equivalent load passes would be required to supply material to pave a 150 mm thick HMA lift over 300 meters of 7 meter wide roadway. 3

DATA ANALYSIS

As described at the end of Section 2.3, some desired test locations were not identified prior to loading, resulting in an inability to make some desired comparisons. Care has also been taken to remove as many outside variables as possible when grouping results for comparison. 3.1 Gravel Gravel was compared to a control CLS at thicknesses of 250 mm and 300 mm. Aggregates were compacted to the point where an inspector would be satisfied based on visual observations. After 10 load passes, trucks had to be diverted to the construction lane because of excessive rutting. Table 5 shows gravel and CLS rutting data along with the aggregate’s percent compaction and percent of optimum moisture content (OMC). Visual observations during loading indicated most of the rutting occurred within the aggregate layer itself. The rutting would be more appropriately characterized as shoving. The poor 182

Table 5. Gravel and CLS control rut depth after 10 load passes with compaction data. Rut depth, mm Aggregate

T = 250 mm

T = 300 mm

% Compaction

% of OMC

Gravel CLS

180 135

143 46

91.8 93.4

33 67

T = Aggregate layer thickness.

Table 6.

RAP-SM, RAP-BM, and CLS control rut depth after 10 load passes with compaction data. Rut depth, mm

Aggregate

T = 200 mm

T = 250 mm

T = 300 mm

% Compaction

% of OMC

RAP-SM RAP-BM CLS Control

102 77 –

62 66 –

70 49 42

93.6 98.6 92.1

44.8 31.0 24.0

T = Aggregate layer thickness.

performance of this section may be a direct result of inadequate compaction and possibly moisture content. If an area is compacted only to the visual satisfaction of an inspector, the quality of compaction can vary depending on the inspector’s bias, experience, and also material type. Both the gravel and CLS sections were compacted using the same compactive effort. The rounded particle shape of the uncrushed gravel is likely to have contributed to the higher rut depth when compared to the CLS. Also, the laboratory CBR data shown in Table 2 does not accurately represent the field performance of the gravel at close to the same compaction and moisture content. One would not expect this significant rutting with a CBR close to 70. This shows CBR to be an unreliable test on gravel, most likely because of the confining effects of the mold. The laboratory CBR data for CLS at the field moisture content shows a CBR of close to 30, which provides some explanation of the high CLS rutting. The high moisture content shown in Table 5 is a result of the aggregate stockpiles being exposed to the 38 mm rainfall described in Section 2.3. 3.2 RAP Both RAP-SM and RAP-BM at thicknesses of 200 mm, 250 mm, 300 mm were compared to a control 300 mm CLS. Aggregates were compacted to the point where an inspector would be satisfied based on visual observations. After 10 load passes, trucks had to be diverted to the construction lane because of excessive rutting. Table 6 shows RAP-SM, RAP-BM, and CLS rutting data along with the aggregate’s percent compaction and percent of OMC. The rutting data shown in Table 6 confirms the poor performance predicted by the CBR data shown in Table 2. Even with the high percent compaction, the 300 mm thick RAPBM layer does not perform as well as the poorly compacted CLS control layer. Similar to the gravel described in Section 3.1, visual observations after loading showed most of the deformation consisted of shoving aggregate. The poor performance of RAP materials may be a result of a lack of fines, which allows larger particles to more readily shift position under load. The slightly better performance of the RAP-BM material could be a result of its coarser gradation, which may provide more interlock between particles. 183

3.3 CLS In addition to evaluating the performance of different thicknesses of CLS, different levels of compaction were also incorporated into the CLS section. CLS compacted to a minimum of 95% of the maximum AASHTO T 99 laboratory density have been designated “A”. CLS compacted according to the visual observations of an inspector have been designated “B”. A 300 mm CLS-B test location served as the control. After approximately 20 load passes, the left wheel-path within the CLS-B material showed two times the rutting depth as the right wheel path. The likely reason for these “edge-effects” was inadequate compaction along the left edge of the test lane. To compensate for this, the CLS-B rutting data shown in Figure 1 represents the average of 2 rut depths on the opposite wheel path. Because of the short distance between the CLS-A and CLS-B test sections, there was no room to divert trucks to the construction lane, so the CLS-B sections were regraded after approximately 120 passes. Figure 1 shows average rut depth versus the number of load passes for various thicknesses of CLS-A and CLS-B. The data shown in Figure 1 indicates CLS-A significantly outperforms the CLS-B at every thickness. The in-situ density information obtained prior to loading indicated both the CLSA and CLS-B had achieved an apparent percent compaction greater than 100%. During compaction, the roller operator was instructed to perform additional passes on the CLSA, so a higher compactive effort was verified on the CLS-A section. Because of the nearly equal apparent percent compaction, the CLS-B should have performed as well as the CLS-A.

80

Average Rut Depth, mm

70 60 300mm B 50

250mm B 150mm B

40

250mm A 200mm A

30

150mm A 20 10 0 0

30

60

90

120

150

180

210

240

270

300

Load Passes Figure 1.

Average rut depth versus load passes for various thicknesses of CLS-A and CLS-B.

Table 7.

CLS-A and CLS-B test section density and moisture content information.

Aggregate

Percent compaction prior to loading

Percent of OMC as placed

Percent of OMC prior to loading

CLS-A CLS-B

102 100

65 25

54 56

184

Table 7 shows the percent compaction prior to loading, as-placed moisture content, and moisture content prior to loading. The information in Table 7 shows a large increase in CLS-B moisture content between placement and loading as a result of the 38 mm rainfall. CLS-B was delivered to the project dry, while CLS-A was delivered wet to facilitate compaction to the required density. The increase in CLS-B moisture content resulting from rainfall may have affected the ability of the density test prior to loading to accurately reflect density at the time of placement. The decrease in CLS-A moisture content shows the rainwater did not infiltrate the aggregate. The difference in water infiltration, the observed greater compactive effort, and the typical percent compaction of other CLS control sections indicates the CLS-A probably had a higher density than the CLS-B even though the density test data shows otherwise. 4

CONCLUSIONS

The purpose of the test loop was to determine how aggregate properties, construction methods, and aggregate layer thicknesses affect field performance. The test loop data points to three primary factors affecting the performance of an aggregate improved subgrade: – Better performing materials had angular particles and low plasticity fines. In this case, the CLS had a relatively high fines content, but other factors, like angularity and low plasticity, probably offset the quantity of fines. The uncrushed gravel poor performance was probably significantly affected by the rounded particle shape providing little or no interlock and the high plasticity fines. The poor performance of RAP materials was likely due to a combination of their lack of fines and smooth particle surface texture. – The data shows compaction and moisture content had a significant effect of performance. The denser a material is at the time of placement, the better it performs, and the better it can tolerate rainfall without a loss in performance. This is clearly shown in the CLS test section when CLS-A and CLS-B are compared. – The data shows, as expected, rutting increased with the number of loading passes. However, the rate of increasing rut depth was dependant on aggregate properties, compaction, and moisture content. With subgrade CBR of approximately 5 in each of the test sections, aggregate properties appear to have a larger impact on performance than the subgrade conditions. The reclaimed asphalt pavement and uncrushed gravel used on the test loop demonstrated unacceptable performance for improved subgrade applications at any thickness. CLS performance was significantly improved when a compaction specification is used during placement. This study demonstrated that aggregate subgrade thickness can be optimized for performance and economy by considering aggregate properties and construction methods. This study examined a limited number of aggregates and did not include a comprehensive evaluation of how specific aggregate properties interact together to influence performance. A more detailed study is currently being conducted by the University of Illinois at Urbana-Champaign at the Illinois Center for Transportation. DISCLAIMER This paper represents the view of the author who is responsible for the accuracy of the data presented. The contents do not necessarily reflect the official views or policies of IDOT. REFERENCES Barksdale, R.D., 1991. The Aggregate Handbook. Washington D.C., National Stone Association. Heckel, G., 2009. Aggregate Subgrade Thickness Determination. Physical Research Report 154. Springfield: IDOT. IDOT, 1999. Geotechnical Manual. IDOT Bureau of Bridges and Structures. Springfield: IDOT

185

IDOT, 2002. Bureau of Design and Environment Manual. IDOT Bureau of Design and Environment. Springfield: IDOT. IDOT, 2005. Subgrade Stability Manual. IDOT Bureau of Bridges and Structures. Springfield: IDOT. Lukanen, E.O., 1997. An Evaluation of Aggregate and Chip Seal Surfaced Roads At Mn/ROAD. Report 1998–24. St. Paul: MnDOT Saeed, A., Hall, J.W. Jr. and Barker, W., 2001. Performance-Related Tests of Aggregates for Use in Unbound Pavement Layers. NCHRP Report 453. Washington D.C.: National Academy Press. Truebe, M.A. and Evans, G.L., 1995. Lowell Test Road: Helping Improve Road Surfacing Design. Proceedings of the Sixth International Conference on Low-Volume Roads vol. 2:98–107. Washington D.C.: National Academy Press.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Analytical evaluation of unbound granular layers in regard to permanent deformation L.A.T. Brito & A.R. Dawson Nottingham Transportation Engineering Centre, University of Nottingham, Nottingham, UK

P.J. Kolisoja Tampere University of Technology, Tampere, Finland

ABSTRACT: Computations of stress-strain state in granular layers are often simplified with the assessment of vertical stress at the top of the subgrade for the purpose of Low Volume Road (LVR) pavement design. This paper discusses an analytical method for evaluating the stress-strain condition in thinly surfaced or unsurfaced pavement typically used in LVR structures, aiming at a better understanding of the effect of modern loading condition in these roads—e.g. Tire Pressure Control Systems (TCPS) and super single tyres. The results of the modelled scenarios show a fairly well defined locus of maximum stress for a variety of structures, indicating greater damaging effect of super single over twin tyres and, likewise, greater damage inflicted by high tyre pressures. The analysis of some Heavy Vehicle Simulator (HVS) test results available from literature using this technique suggests a promising opportunity for the development of a simplified design method of LVR against rutting. 1

INTRODUCTION

In unsealed and thinly sealed roads, the behaviour of the pavement is mostly dictated by the granular layers. In such structures, the aggregate is responsible for spreading the load received by the tyres to the road foundation. Depending on the modular ratio and thicknesses among the pavement component layers, the unbound granular layer(s) (UGL) and the subgrade will be responsible to bear varying proportions of the stresses imposed. According to the level of stress each layer will suffer, consecutive vehicle passes will cause certain damage, triggering permanent deformation to accumulate throughout the pavement’s life. Growing use of new tools to aid transportation roads that are largely constituted of unbound granular material (UGM)—such as tyre pressure control systems (TPCS)—has motivated research about the difference tyre pressure would cause in regard to permanent deformation in UGL. The principle involved in TPCS is that by inflating (deflating) tyres, a smaller (bigger) “footprint” will cause a different tyre-pavement contact to occur as well as a different applied pressure on the pavement. This will directly affect the stress distribution in the pavement and, therefore, influence the permanent deformation induced. TPCS is of growing use in some countries in the forest business (Douglas et al. 2003, Munro & MacCulloch, 2007). At lower pressures the same vehicle may cross a softer pavement without causing rutting or wheel spin. The technique also seems to result in much less tyre wear (Munro & MacCulloch, 2007) and, perhaps, fuel use. The drawback is that the vehicle cannot travel at speed on conventional pavements without safety concerns, thus requiring the pressure to be increased to conventional levels in such situations. This system is credited in reducing the rutting damage in unsealed roads and also in improving ride quality for drivers. In addition to TPCS, the increasing use of super single tyres over dual tyres in all range of goods transportation is also a reality. The reduced tyre size directly affects the pave-

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ment’s rutting rates, as the smaller contact areas have a more concentrated load with consequent increased damage rates. This paper explains the derivation of a simplified method to assess the likelihood of pavement rutting when subjected to different loading conditions. An analytical method is explained that assesses both the impact of trucks equipped with TPCS running on dual tires and super singles in regard to permanent deformation. To achieve this, 180 conditions were simulated using the Kenlayer software and results from while an HVS experiment in Finland provided data for validation. 2

PERMANENT DEFORMATION IN UGM

As rutting is the main distress mode in unsealed and thinly sealed pavements (Dawson et al. 2005), it is desirable that it be analytically approached rather than empirically as many design methods do (Austroads 1992, TRL 1993, AASHTO 1993); it is only by understanding each material’s behaviour that engineers will be able to anticipate the liability of a given structure, subjected to certain traffic and environmental conditions, to rut. If only empirical assessment tools are employed, then different conditions than those which provided performance benchmarks, could be never reliably accounted for. Some design methods advocate that rutting only occurs within the subgrade provided that the unbound granular materials comply with materials specification. Hence, by limiting the vertical elastic strain at the top of the subgrade, it would be possible to assure a new pavement structure against rutting. This assumes minimally two things: a. Recipe-based specification of UGM which typically include criteria for aggregate strength, durability, cleanliness, grading and angularity would provide some guarantee of a direct measurement of resistance to rutting. b. The elastic properties of the subgrade material would have a direct relationship with its plastic properties. Both of these conditions have very weak validity for granular and soil materials, if any. Such over-simplified methods for pavement design make it impossible to take full advantages of alternative materials and often provide a low reliability procedure. Newer studies of plasticity in unbound granular materials for pavements such as Boyce (1980), Lekarp (1997), Werkmeister (2003), among others, have greatly advanced on the topic. Most of these models available for permanent deformation modelling are usually based on laboratory triaxial tests, what can be many times expensive tests for LVR projects. Rutting can occur for a number of reasons, and basically follow four different types of contributory mechanisms, according to Dawson & Kolisoja (2004), namely: • Mode 0—Compaction of granular layers alone. No rutting in the subgrade. It is usually associated with inadequate compaction of the UGL during construction. It doesn’t represent a major threat to the pavement as it is usually self-stabilizing with traffic providing the missing compaction effort early in the layer’s life. • Mode 1—Shear deformation within the granular layer of the pavement, near the surface. A dilative heave adjacent to the wheel track is usually characteristic of this mode. It is largely a consequence of inadequate granular material shear strength and ideally there would be no deformation of the subgrade. It may lead to incremental collapse. • Mode 2—Shear deformation within the subgrade with the granular layer following the subgrade. This usually occurs in situations where aggregate quality is good. The pavement may rut as a whole and incremental collapse may result. • Mode 3—Particle damage (e.g. attrition or abrasion, perhaps by studded tyres) can be a contributor to the same surface manifestation as in Mode 0 rutting though, of course, the mechanism is very different. • Combined mode—In practice rutting will be a mix of all previous modes. Each mode will have a certain contribution, although one mechanism may govern the overall rutting development. 188

As Mode 0 failure is self-stopping once adequate compaction has taken place and Mode 3 can be addressed by particle strength requirements, independent of the stress analysis, both this mechanisms have been discounted for this analysis. Hence, mechanisms of rutting such as Modes 1 & 2 are considered. Permanent deformation could be accounted through a rational modelling of the plastic deformation generated by each vehicle pass throughout the pavement’s life or, in a more qualitative fashion that would tell the likelihood of a specific structure to rut. This last rationale has been the option used in this study, as a means of promoting a readily accessible tool for engineers looking after LVRs. The proposed methodology still treats the pavement analytically, but permitting a more fundamental description of UGL behaviour than in simple linear elastic analysis but that simplifies elasto-plastic analysis for routine use, thereby reducing demands of material characterization and for computational skills. 3

ANALYSIS

For the analysis of the proposed study three different materials were selected and modelled, using the Kenlayer software (Huang, 2003), totalling 180 different combinations of load arrangement, tyre pressure, unbound granular material, stiffness ratio between base (in this case the trafficked layer) and subgrade (semi-infinite layer) and the ratio between base thickness and loaded radius, which is a function of the tyre pressure. The three materials tested (Northern Ireland Good, or NIG, Northern Ireland Poor, or NIP, and CAPTIF material, or CAF) are detailed in Section 3. Figure 1 illustrates the experimental matrix. The Ebas/Esub ratio represents the proportion between the resilient modulus of the base and subgrade while the “AggThick/LoadRadius” represents the ratio between the thickness of aggregate layer and loading radius. All the values were normalized so that the response of other structures could be easily interpolated from the results. As is typical for LVRs, the UGL was taken to be the trafficked layer. The thickness of he UGL was 9.5–66.5 cm and subgrade resilient modulus ranged from 45–350 MPa. The rather extreme values for Esub and Ebas/Esub were chosen in order to allow interpolation of the

Figure 1.

Experiment matrix—total of 180 analyses.

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Table 1.

Properties of materials analysed. MohrCoulomb Bulk Unit Failure Weight parameters

Name

Drucker-Prager Shakedown Shakedown (p–q stress range range K-Θ space) boundary A-B boundary B-C Constants

ρb (kN/m3) c (kPa) ϕ (°) d (kPa) β (°)

NI Good (NIG) 19 NI Poor (NIP) 21 CAPTIF2 (CAF) 22.8

74 27 0

46 46 61

135 49 0

62 62 68

d (kPa) β (°)

k1 d (kPa) β (°) (MPa) k2

10 65 0

59 114 0

58 39 45

65 56 62

71510 0.29 103460 0.23 3200 0.77

Range A. B & C are fields of stress in which permanent deformation under repeated loading is stabilising, incrementally increasing or de-stabilising, respectively. The range boundaries are defined in terms of pseudo-Drucker-Prager surface values in p–q space; “d” being the q-intercept of the surface and b the angle of the surface, both in p–q space.

results over a wide variety of situations. Although somewhat unrealistic at the highest values, to the values used allow the rationale of high stiffness materials to become evident. 3.1 Materials Three materials were selected from the University of Nottingham database (Arnold, 2004). All the necessary parameters for the analysis had already been previously assessed and are summarized in Table 1. The materials selected covered a range of likely behaviours expected for UGM. NI Poor (NIP) is a material used for a trial in Northern Ireland (Arnold, 2004), is known to be of a poor quality. It has relatively low cohesion (c) and a poor angle of friction (ϕ). It has moderate stiffness characteristics but a low non-linearity such that stiffness does not increase much in highly stressed areas. NI Good (NIG) is a granular material of a similar stiffness used in the same Northern Ireland trials. Although it has a similar stiffness its strength is higher than that of the NIP material and its “Range A” shakedown stress envelope is substantially larger. CAPTIF material 2 (CAF) is a much cleaner aggregate with no cohesion, but a very high frictional behaviour and a stiffness that rapidly increases with additional imposed stress (highest k2). Its shakedown ranges are similar to those of NIP, but has a much greater ultimate strength. 3.2 Loading arrangements The loading arrangements were those representatives of typical trucks on LVRs in the United Kingdom. Equivalent radii were obtained by distributing 45 kN wheel loads over circular areas at the tyre pressure, circular loads being the Kenlayer input mode (Fig. 2). The distances used between tyres were based on measurements made in pavement trials in Scotland (Brito et al. 2008). Dual tyres are based on a typical tyre designation 295/80R22.5 and the “super singles” 385/65R22.5. Figure 2 illustrates the radii and load position for all loading arrangements studied. Although lorries fitted with TPCS may run with tyre pressures as low as 240 kPa and as high as 900 kPa, pressures of 400 kPa and 800 kPa were deemed to be closer to the operational values. 3.3 Methodology of computations One advantage of the Kenlayer program (Huang, 2003) is its capability of treating UGMs as non-linear elastic using a k-θ model. This allows the computation of the elastic modulus of the layer according to the stress state it is subject to (due to external loading and geostatic forces). 190

Figure 2.

Equivalent, circular loaded wheel areas.

Figure 3.

Typical plot of computed stresses in pavement.

191

Figure 4.

Example of two p,q plots. Syield surface-failure in this plot is the same as Sf in the text.

Despite this benefit, the computational framework does not prevent the computation of tensile stresses which may lead to erroneous values at certain stress points. In addition, although non-linearity is accounted for, each layer has the same stiffness properties throughout which, for the thicker layers, may result in some distortions. The distortions caused by the computations of the tensile stress are minimized by the correction Kenlayer performs with the so-called “Method 3”, in which the negative or small horizontal stresses are modified according to the Mohr-Coulomb theory of failure, so that the strength of the material is not exceeded. This “method” is selected when the value of ϕ is

greater than zero and smaller than 90°. It also accounts for the geostatic stresses. The output results were computed in terms of the stress invariants p—the mean normal effective stress and q—the deviatoric stress. The analyses were carried out by the following steps: i. Stress and strain were computed at 360 points per structure. ii. The ratio of deviatoric stress over mean normal stress (q/p) was calculated for each point analysed. iii. If q/p > 3 or q/p < 0, the values were disregarded. For the first condition (q/p > 3) this implies that a tensile stress was being reported, an impossibility for a UGM/UGL. The second condition (q/p < 0) also indicates a negative stress being computed. iv. p and q results were plotted and a polynomial of 6th order was fit to each stress plot. v. The Drucker-Prager yield surface was then added to the plot and the proximity of the stress state to it was assessed by means of a variable, here called “S” and described further in the next section. Figure 3 shows a typical stress plot resulting from the analysis performed. Figure 4 shows a plot in which the polynomial fits are displayed for two different cases: Dual tyres at 400 kPa and Super Singles at 800 kPa (CAF; Agg. Thick/Load Rad = 1.3; Ebas/Esub = 2). 192

4 RESULTS Presenting all the results for the 180 analysis in this study would be cumbersome. As the main goal of the exercise is to promote a more qualitative study of the likelihood of the UGM developing permanent deformation, it is expected that the proximity of a certain stress state in a UGM to its yield failure envelope will provide a basis for the assessment of the rutting likelihood of rutting of the structure due to plastic deformation in the UGM. From previous studies (Dawson and Kolisoja, 2004) it is known that, if the stress states in the pavement are kept a long way from failure then no rutting in the granular layers will occur, but that if the stresses approach the static failure envelope, then the speed of development of rutting in the granular layer increases. Hence, in order to simplify all computations performed, the stress variable S is introduced to provide a single parameter that will allow a comparison between the most damaging stress in the pavement and the corresponding limit stress state (Fig. 4). The line drawn from “p, q = (250,0) to (0,250)” was chosen as the basis for defining S as it intersects most of the loci of maximum stress points when those loci are at their closest to the failure envelope. The length (in kPa) of the line from p, q = (250,0) to the stress loci is then termed “S” and the length from p, q = (250,0) to the failure envelope is “Sf ”. Different lines could have been selected, but this line seemed a reasonably reliable one for the purpose of assessing proximity to failure. In addition, after a careful study of the results, the computed stresses were found to be largely independent of granular material type, indicating that these stiffness non-linearities lead to very similar

Figure 5.

S values (kPa) for the dual tyres at both pressures.

Figure 6.

S values (kPa) for the Super Singles at both pressures.

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computed stiffnesses for the same loading and layer sequence. This fact means that the values of S are also very similar for pavement with granular layers made from any of the materials. Therefore, the effective number of values of S reduces to 60. Arguably, the p, q line selected for this study as a reference parameter to assess proximity to the yield surface could be changed. Although the three materials investigated covered to some extent the differences in mechanical behaviour exhibited by aggregates traditionally used in LVRs, different p, q lines may be required to assess the S variable for other materials. Even though a certain amount of empiricism is introduced in the assumption of a “p, q = (250,0) to (0,250)”, the computations performed show this line to be a good reference point. Figure 5 presents a surface plot containing the results for all 90 exercises modelled using dual tyres. Figure 6 illustrates the results for super single tyres. It is evident from Figure 4 that the value of S is sensitive to wheel loading arrangements. The S values for the failure envelopes, “Sf ” in Figure 4, are evidently different for each material. For the three materials tested, the values are: • NIG = 297.1 kPa • NIP = 254.9 kPa • CAF = 251.8 kPa A “S” condition that approaches the Sf means that the pavement is likely to rapidly develop permanent deformation. In effect, there should be a limit to which these values could be considered acceptable and not. Potentially, two boundaries could tell if this “proximity” to failure is either far distance from developing permanent deformation (Range A behavior, explained beneath Table 1), very likely to collapse after few loadings (Range C) or if it could develop a rutting acceptable for a certain number of vehicles passes (Range B). This follows the same criteria suggested by the Shakedown theory although considerably simplified.

5

VERIFICATION

Direct verification of the suggested design approach turned out to be challenging as the amount of suitable, well-documented experimental data available in the literature proved extremely limited. The main reason for this is obvious. Instrumented test sections are very seldom built using structures that are so weak that they are to be damaged under a small number of load repetitions. However, one source of data that was close to the intended application area of the design approach were some of the results from a test series performed using the Heavy Vehicle Simulator (HVS) at the Technical Research Center of Finland (VTT) (Korkiala-Tanttu et al. 2003). Even in these tests, however, the structure had some important differences from the typical very low volume/forest road type of structures mainly considered here (Fig. 7): • the structure was covered with a 50 mm layer of asphalt concrete. • the total thickness of the aggregate layers on top of a sandy subgrade was 500 mm. In the HVS tests different sections of the test structure were exposed to 70 000 load repetitions with a set of dual tires with total loads of 70 kN and 50 kN, and tire inflation pressures of 850 kPa and 700 kPa, respectively. The corresponding values of permanent axial strain in both upper and lower part of the unbound base course are presented in Table 2 together with the Mohr-Coulomb failure parameters determined by means of multi-stage monotonous triaxial tests and the respective value of Sf. For the rutting analysis of the unbound crushed rock base course the following assumptions and simplifications were made: • the thin AC surfacing was considered as a part of the unbound base course layer. • the unbound sub-base course was combined with the sandy subgrade. • the stiffness ratio Ebas/Esub was considered as 2.0. Keeping in mind the highly stressdependent stiffness in both the base and sub-base course/subgrade materials and the 194

Figure 7.

HVS test arrangement at VTT (Korkiala-Tanttu et al. 2003).

Table 2. Mohr-Coulomb failure parameters and the respective value of Sf for the base course material, values of Sf, S and permanent deformation after 70 000 load repetitions with different tire arrangements. Mohr-Coulomb failure parameters c (kPa)

ϕ (°)

Parameter Sf kPa

43.0

43.1

267

Dual wheel load kN

Tyre pressure kPa

Parameter S kPa

S/Sf %

Permanent strain Upper/lower part %

70 50

850 700

234 225

87.6 84.3

4.2/3.7 1.1/0.9

rapidly decreasing hydrostatic stress level alongside with increasing distance from the road surface, this may be considered as a reasonable assumption. Then, by interpolating to the inflation pressure of 700 kPa for the 50 kN dual wheel, and slightly extrapolating to the inflation pressure of 850 kPa for the 70 kN dual wheel, and using the respective values of Aggregate Thick/Load ratio of 2.17 and 2.35, S values of 225 kPa and 234 kPa were obtained (Table 2). As Table 2 indicates the accumulation rate of permanent deformations in the unbound base course rapidly increases alongside with the S/Sf ratio. Even though the available data is too limited for firm conclusions to drawn, it seems that a critical limit value of the S/Sf ratio for very rapid Mode 1 rutting (Range C) of the unbound base course to take place might be of the order of 90% as has been suggested earlier (Dawson et al. 2007). 6

CONCLUSIONS

The analytical evaluation carried out seemed to produce reliable results and seems to be easy to use. Benefits and limitations could be summarized as follows: • It is simpler than complex permanent deformation modelling that requires several input variables. • It is neither time consuming nor requires major computational resources. • It applies a logical rationale of permanent deformation development. That is, it suggests, that the proximity to a certain failure envelope is related to rutting likelihood. • As the calculations demonstrated little sensitivity to the materials’ resilient properties (within the range evaluated), the proximity to failure could be simply computed by determining the Sf parameter for a given material and comparing it to the S value of the structure. 195

• It analytically verifies the UGL against rutting rather than by performing a simplified empirical assessment. • Simplifications are inherent in the computations due to the software used, in particular. • Tensile stresses are manually filtered (by doing so, the software doesn’t recalculate the stress state of the pavement into a match where no tensile stresses exist; hence, there may be some minor inaccuracies in the results), • Rutting is only considered in the granular material (Mode 1). It is assumed that none comes from the subgrade (Mode 2). This assumption is in line with a study of LVR made by Tyrrell (2004) but could be unfounded on pavements with very thin structural layers. The presented verification example gives at least qualitative support to the suggested design approach. It must, however, be recognised that so far the verification is based on a very limited amount data, because well-documented experimental results from rutting tests performed with low volume road type of structures are extremely scarce. REFERENCES Arnold, G. 2004. “Rutting of Granular Pavements”. PhD Thesis, University of Nottingham, UK. AUSTROADS. 1992. Pavement Design—A Guide to the Structural Design of Road Pavement. Austroads, Sydney, Australia. AASHTO. 1993. AASHTO Guide for Design of Pavement Structures. Washington D.C. Boyce, J.R. 1980. A non-linear model for the elastic behaviour of granular materials under repeated loading. Proc. Int. Symp. Soils under Cyclic & Transient Loading, Swansea, pp 285–294. Brito, L.A.T., Dawson, A.R. & Tyrrell, R.W. 2008. Roads Under Timber Transport—Ringour Trials. NTEC Report 08022. May 2008. England/UK. Brown, S.F. & Dawson, A.R. 1992. Two-stage approach to asphalt pavement design. Proc. 7th Int. Conf. on Asphalt Pavements. Nottingham, June 1992, Vol 1 pp. 16–34. Douglas, R.A., Woodward, W.D.H. & Rogers R.J. 2003. Contact Pressures and Energies Beneath Soft Tires—Modelling Effects of Central Tire Inflation—Equipped Heavy-Truck Traffic on Road Surfaces. Transportation Research Record 1819, TRB Washington DC, 2003. Dawson, A. & Kolisoja, P. 2004. Permanent Deformation. Report on Task 2.1. Roadex II Project. Dawson, A., Kolisoja, P. & Vuorimies, N. 2005. Permanent Deformation Behaviour of Low Volume Roads in the Northern Periphery Areas, Proc. 7th Int. Conf. Bearing Capacity of Roads, Railways and Airfields, Trondheim. Dawson, A.R., Kolisoja, P., Vuorimies, N. & Saarenketo, T. 2007. Design of low-volume pavements against rutting—a simplified approach, Proc. 9th Low Vol. Roads Conference, Austin, TX, 2007. Huang, Y.H. 2004. Pavement Analysis and Design. 2nd ed.. New Jersey: Prentice Hall. 775 p. Korkiala-Tanttu, L., Laakosonen, R. & Törnqvist, J., 2003. “Kevään ja ylikuorman vaikutus ohutpäällysteisen tien vaurioitumiseen, HVS-Nordic-tutkimus” (The effect of the spring and the overload to the rutting of a low-volume road, HVS-Nordic-research), Finnish Road Administration, Finnra Reports 11/2003, Helsinki (In Finnish). Munro, R. & MacCulloch, F. 2007. Tyre Pressure Control on Timber Haulage Vehicles. Roadex III Report on Task B-2. Transport Research Laboratory. 1993. A guide to the structural design of bitumen-surfaced roads in tropical and sub-tropical countries, RN31, Draft 4th Edition. Lekarp, F. 1997. Permanent deformation behaviour of unbound granular materials. Licentiate Thesis. Sweden. Tyrrell, W. 2004. Pavement trials at Risk Quarry, Kirroughtree. Proc. 6th International Symposium on Unbound Materials—Unbar 6, Nottingham, 6–8 July 2004. England: Balkema. Werkmeister, S. 2003. Permanent deformation behaviour of unbound granular materials in pavement constructions. PhD Thesis, Technical University of Dresden, Germany.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Processed Portuguese steel slag—A new geomaterial A. Gomes Correia & S.M. Reis Ferreira Department of Civil Engineering, Minho University, Guimarães, Portugal

A.J. Roque National Laboratory of Civil Engineering, Lisbon, Portugal

A. Cavalheiro Portuguese Steel Company, Seixal, Portugal

ABSTRACT: The management strategy for waste, in which the prevention of its production is not yet feasible, should lead to the prioritization of the exploitation of its performance potential, especially through re-use solutions. On this basis, a Research and Development Project is under way in Portugal, which is intended to re-use the processed steel slags produced in the two Portuguese Companies. In this paper are presented the results obtained by laboratory performance-related tests for geometrical, physical and mechanical properties for the two Portuguese processed steel slags, named Inert Steel Aggregates for Construction (ISAC). A special emphasis is made in terms of elastic modulus, comparing the two ISACs, with two standard base course materials (granite and limestone aggregates). The laboratory results show that the ISACs could be used in transportation infrastructures. It was also experimentally observed that the two ISACs have better mechanical properties than the standard unbound granular base course materials. 1

INTRODUCTION

The two Portuguese Steel Companies (one is located at Seixal—SN of Seixal, and the other at Maia—SN of Maia; see Figure 1) estimate the annual production of processed steel slag in their electric furnaces at about 270 000 tons per annum and are expecting to produce, within medium term, 400 000 tons. The management of this large volume of material in accordance with the applicable legal framework represents a significant source of concern for the companies and for the country.

Figure 1.

Location of the two Portuguese steel companies (Roque et al 2007).

197

According to the routine tests and criteria for natural materials, these materials have generally been considered, in the past, as unsuitable for use in geotechnical works, as many other non-traditional materials. Therefore, the waste management strategy should favor the exploitation of its potential, namely through re-use solutions. In this context it is desirable to apply to these materials the principles of sustainable development: (i) reducing the quantities of waste that is disposed of in landfill; (ii) creating a new and important national market; and (iii) preserving natural raw materials. It is, therefore, necessary to demonstrate that the use of non-traditional materials, instead of natural ones, will assure, at least, the same construction quality and long term performance. On this basis, a Research and Development Project (R&D) is undertaken in Portugal, which is intended to study the re-use processed steel slag, actually named Inert Steel Aggregate for Construction (ISAC) produced in the Portuguese Steel Companies. The project, named “Application of waste in transportation infrastructures and geotechnical constructions—Re-use of steel slags”, is financially supported by the Portuguese Foundation for Science and Technology (FCT) and Portuguese Steel Companies (SN), and also embraced by the Portuguese Roads Administration (EP) and the Institute for Waste Affairs (APA). It includes the National Laboratory of Civil Engineering (LNEC— coordinator), the University of Minho (UM) and the Centre for Re-use of Waste (CVR). Its main purpose is to contribute to the creation of a mechanistic and environmental approach intended to promote the re-use of waste, in general, and processed steel slag, in particular. To evaluate the re-use of processed steel slags in transportation infrastructures and geotechnical constructions, a vast laboratory experimental program was implemented to study the mineralogical, chemical, geometrical, physical and mechanical properties. The aim of this preliminary study is to compare the values of these properties obtained for the ISACs with values specified in the Portuguese standards for natural aggregates that could be applied in transportation infrastructures. In this paper are presented the geometrical, physical and mechanical properties. Furthermore, a specific comparison is made in terms of elastic modulus, comparing the two ISACs with two standard base course materials (granite aggregate 0/31.5 mm and limestone aggregate 0/19 mm). The studied ISACs (see Figure 2) are processed black steel slags, which are separated from liquid steel at the end of the oxidation phase. The steel production process in the National Steel Companies with electric arc furnaces comprises two phases: the fusion phase and the refining phase. The main raw material used in the fusion phase is the ferrous scrap-iron. The components which are to produce black steel slag, mainly lime, are also added in this phase. The refining phase comprises three stages: the first corresponds to the oxidation period, during which the black steel slag is produced; the second corresponds to the reduction period, which produces the white steel slag; and the last one corresponds to the final adjustment period of the composition. The black steel slags are then submitted to one adequate processing to be re-used as an inert steel aggregate in the public works. The processing of the black steel slags into ISACs is done in three phases: i) flow and cooling of steel slag; ii) separation and exploitation of the metallic component; and iii) exploitation of the non-metallic component. Details of the processing ISACs were reported by Roque et al 2007. As regards the environmental aspects, the tested ISACs obtained from steel slag are, from a leacheability point of view, an inert waste (Roque et al 2007).

Figure 2.

Photo of Portuguese processed steel slags (ISACs).

198

2

INDEX PROPERTIES

For assessing the index properties of ISACs, a decision was made to use Portuguese standards/ specifications as a replacement for the equivalent European Standards, because, in this transition stage, many of the known reference studies have also been performed using the Portuguese standards/specifications. The particle size distributions were done in accordance with the Portuguese Specification E 196 and the Atterberg limits with the Portuguese Standard NP 143. Considering the particle size classification used by soil mechanics to describe natural soils, the ISACs from the SN of Maia, of which the percentage of fines (Ø ≤ 0.075 mm) is about 1.5%, consists of about 8.5% of material belonging to the sand fraction (0.06 mm < Ø ≤ 2 mm), 78.5% to the gravel fraction (2 mm < Ø ≤ 60 mm) and 1.5% to the fine blocks fraction (60 mm < Ø ≤ 200 mm), as shown in Figure 3. The Seixal ISAC consists of about 19.5% of material belonging to the sand fractions and 74% to the gravel fraction, the fine percentage being about 6.5%. In terms of maximum diameter, Dmax, and particle size indices (effective diameter D10 and uniformity and curvature coefficients, Cu and Cc, respectively), the values obtained for the Maia ISAC and for Seixal ISAC were, respectively: Dmax (mm) = 76.1 and 38.1; D10 (mm) = 1.96 and 0.22; Cu = 9.64 and 33.20; and Cc = 1.95 and 4.30 (Figure 3). The two aggregates are well graded materials. Based in the Atterberg limits results, both materials are non-plastic. The index properties (grading, plasticity and Los Angels (LA) coefficient) of Maia and Seixal ISACs are compared with the minimum requirements for those properties predicted in the Specification of the Portuguese Roads Administration for natural crushed materials to be applied in base, sub-base and in capping layers. Figure 3 compares the particle size distribution curves of ISACs with the particle size distribution ranges defined in the Specification 100 Seixal ISAC Maia ISAC

Cumulative % passing

80

Range of Road Portuguese Administration

60

40

20

0 0,01

0,1

1 Grain size (mm)

10

100

Figure 3. Particle size distributions of Maia and Seixal ISACs and their comparison with particle size distribution ranges specified by Portuguese Road Administration. Table 1. ISACs index properties and the Specification of the Portuguese Roads Administration for natural crushed materials to be applied in base, sub-base, and in capping layers. ISAC

Admissible values

Properties

Parameter

Seixal

Maia

Capping

Subbase

Base

Physical

wL (%) wP (%) VBS (%) SE (%)

NP NP 0 80

NP NP 0 100

25** 6** 2** 30*

NP NP – 45*

NP NP – 50*

Mechanical

LA(%)

23

28

40**

45**

40**

* Minimum value; ** Maximum value. wL (liquidity limit), wP (plasticity limit), VBS (Value of Blue Methylene), and SE (Sand Equivalent).

199

of the Portuguese Roads Administration for crushed natural raw materials for these applications. It is observed that the curves of the ISACs don’t fit completely in the specified ranges. Even though correction of the grading would be feasible, embankment trials have shown a good performance during compaction and mechanical behaviour, both for Maia and Seixal ISACs existing gradings (Gomes Correia et al 2008). The Specification of the Portuguese Roads Administration also establishes that the natural raw crushed materials to be applied in base and sub-base layers should be non-plastic and that the same materials, when applied in capping layers, should present a liquidity limit (wL) less than or equal to 25% and a plasticity index less than or equal to 6%. Table 1 summarizes the index properties of ISACs and the Specification of the Portuguese Roads Administration for the natural raw crushed materials to be applied in base, sub-base and capping layers. In view of results obtained with the tested ASICs, it is concluded that these materials fulfil the requirements of the Specification of the Portuguese Roads Administration. 3

ISACS ELASTIC YOUNG’S MODULI

The preparation procedure of the ISACs specimens, to study the Young’s modulus, is the same for all the tests: the ISACs are sieved to remove the coarse grains greater than 19.1 mm, as the triaxial specimens sizes were only 150 mm in diameter and 300 mm high, then the ISAC is mixed up with the right quantity of water to obtain the desired water content; after that, it is placed in a sealed plastic bag for 24 hours to allow the hydric equilibrium to be established. The specimens were compacted in 6 layers by vibrating hammer with a static weight of around 7 kg and a plate of 146 mm. The time of vibration was that necessary to achieve, approximately, the same dry density found by the modified Proctor curves (Table 2). The decision to compact the samples to a very dense state is because this is representative of typical compacted pavement layers. The modified Proctor curves were obtained in accordance with the Portuguese Specification E 197, and the results, as well the state conditions of studied samples, are shown in Table 2. In the same table are also presented the results for two standard base course materials (granite aggregate 0/31.5 and limestone aggregate 0/19), which will be used for moduli comparison purposes. The ISACs moduli were evaluated by precision triaxial test with the equipment available at the Civil Engineering Laboratory of the University of Minho. Axial and radial strains were locally measured using 3 vertical LDT (Local Deformation transducer- Goto et al 1991) and 1 horizontal LDT. All the LDT’s were manufactured at University of Minho. A standard pressure transducer and a sensitive load cell located inside the triaxial cell are used to measure boundary stresses (cell and deviatoric stresses). The interstitial air in the material specimen is at the atmospheric pressure through the drainage system. Figure 4 shows a detail of the LDT’s used during the tests. The test procedure to obtain the material Young’s modulus uses several stresses following a test protocol presented by Gomes Correia et al (2005). For each confining pressure (100, 200 and 300 kPa), after consolidation, the test starts with a deviatoric loading applied up to around 1 × 10–3 of axial strain, to obtain the decay curve of secant Young’s modulus with vertical strain. The strain rate of the test is approximately around 0.03 mm/min. During the Table 2. Modified Proctor testing results and compacted specimen state conditions. Modified proctor

State conditions

Material

ρd (×103 kg/m3)

w (%)

ρd (×103 kg/m3)

w (%)

Seixal ISAC (0/19) Maia ISAC (0/19) Granite aggregate (0/31.5) Limestone aggregate (0/19)

2.32 2.43 2.31 2.20

5.00 3.45 5.90 5.80

2.31 2.43 2.19 2.13

5.8 3.5 3.9 3.9

200

500

Axial LDT q (kPa)

400 300 200

Lo ad/unlo ad cycles o f small amplitude

100 0

Radial LDT

0,0E+00

Figure 5.

5,0E-04 1,0E-03 A xial strain

1,5E-03

Example of loading test procedure.

Figure 4. On sample local deformation transducers of triaxial cell at University of Minho.

80

q (kPa)

60

40

Ev =1647 MPa 20

0 0,0E+00

1,0E-05

2,0E-05

3,0E-05

4,0E-05

5,0E-05

Axial strain

Figure 6.

Example of stress-strain relationship of one small amplitude loading/unloading cycle.

unloading process, very small unloading/reloading cycles of vertical stress were performed at different steps (approximately at the maximum value of deviatoric stress (qmax) applied to the specimen, at qmax/2 and at q = 0 kPa). For each step was applied five unloading/reloading cycles of small vertical stress amplitude. An example of the tests procedure for one confining pressure is shown in Figure 5. The amplitude was controlled to ensure that the cycles were closed and linear, in order to evaluate the elastic Young’s modulus. An example of one of these cycles is presented in Figure 6. The values of vertical Young’s modulus are calculated, as illustrated in Figure 6, from deviatoric stress amplitude divided by axial strain variation. Based on previous findings (e.g. Hoque and Tatsuoka 1998, Gomes Correia et al 2001) the very small strain vertical Young’s modulus (Ev) is fitted by a power law with the vertical stress σv not including the lateral stress σh as a variable (Equation 1). The results has been analysed in total stresses and the values normalised for a stress pa, of value 100 kPa. The power law, that describes such behaviour, is given by Equation 1. ⎛σ ⎞ Ev = C ⎜ v ⎟ ⎝ pa ⎠

n

(1)

The test results, for a strain level of 4 × 10–5, are shown in Figure 7. As can be seen the total stress analysis leads to a power n equal to 0.59 and 0.53 for Seixal and Maia ISACs, 201

E (ε = 4×10 -5) MPa

10000

Seixal ISAC Dmáx = 19,1 mm w = 5,8%; e = 0,330 E = 833(σv /pa)0,59 Maia ISAC Dmáx = 19,1 mm w = 3,5%; e = 0,342 E = 737(σv /pa)0,53

1000

100 10

Figure 7.

100 σv (kPa )

1000

Young’s modulus evolution of national ISACs with total stresses.

respectively. These values, for the power, are similar to the usual values found for natural materials that normally are around 0.5 (Santos 1999). From Figure 7 we can also be seen that values found for the small strain vertical Young’s modulus are too high, around 1GPa for a vertical stress of around 150 kPa. This reveals the excellent mechanical behaviour of the ISACs. 4

COMPARISON BETWEEN ISACS AND NATURAL AGGREGATES MODULI

The moduli results of ISACs materials are compared with two standard base course materials (granite aggregate 0/31.5 and limestone aggregate 0/19). The grain size distribution curves, of all studied materials, are shown in Figure 8 and the state material specimen conditions are shown in Table 2. The results presented for the granite aggregate were obtained by Gomes Correia et al (2001). These authors studied the modulus of the natural material by means of a relatively large triaxial apparatus with square prismatic specimen (580 mm high and 230 mm in cross-section). Axial and lateral strains were also measured with LDT’s. The results presented for the limestone aggregate were obtained by Coronado (2005). Coronado (2005) studied the modulus of the natural material by means of a triaxial apparatus with a specimen 150 mm in diameter and 300 mm high. Axial and lateral strains were also measured with LDT’s. To proceed with the comparison, the test results of the four materials were all normalized for the same void ratio value of e = 0.3. Equation 2 was used, where f(e) is the void ratio function and E* being the values measured on specimens. E =E*

f (0.3) f (e )

(2)

The void ratio function used was proposed by Iwasaki et al (1978) and represented by Equation 3. f (e ) =

(2.17 − e )2 1+ e

(3)

Figure 9 shows the results obtained for the elastic modulus as a function of total stress, after void ratio normalization. The values found for ISACs are around four times higher than for granite aggregate (0/31.5). This reveals that the national ISACS have much better mechanical properties than a standard base course material. These results, when considered alongside the results reported by Gomes Correia et al (2005), Gomes Correia et al (2006), 202

100 Seixal ISAC (0/19) Maia ISAC (0/19)

Cumulative % passing

80

Granite Aggregate (0/31.5) 60

Limestone Aggregate (0/19)

40

20

0 0,01

Figure 8.

1 Grain size (mm)

10

100

Studied grain size distribution curves. Seixal ISAC Dmáx = 19,1 mm w = 5,8%; e = 0,330 Enor = 877(σv/pa)0,60

E nor(e = 0,3) (MPa)

10000

Maia ISAC Dmáx = 19,1 mm w = 3,5%; e = 0,342 Enor = 791(σv/pa)0,54

1000

Granite Aggregate Dmáx = 31,5 mm w = 3,9%; e = 0,236 Enor = 170(σv/pa)0,71

100

Limestone Aggregate Dmáx = 19 mm w = 5.9%; e = 0.232 Enor = 250(σv/pa)0.57

10 1

Figure 9.

0,1

10

σv (kPa)

100

1000

Comparison of moduli for ISACs and standard base course materials.

Roque et al (2007) and Gomes Correia et al (2008), emphasize that the national ISACs could be used in geotechnical works, and particularly in transportation infrastructures (embankments, capping layers and base courses). It should be mentioned that a full scale road section has been built and field test results during construction confirm these laboratory findings (Gomes Correia et al 2008). Furthermore, field tests are being performed periodically during time in order to evaluate long term behaviour in terms of mechanical and environmental properties. 5

CONCLUSIONS

This research work seeks to promote the re-use of processed steel slags as a substitute for natural aggregates or traditional materials used in transportation infrastructures and geotechnical works. It contributes technically and scientifically to the application of the principles of sustainable development to construction, specifically to geotechnical works. It also contributes to the preservation of natural resources (natural materials) and reduction of the volumes of wastes to be deposited in landfills. The results obtained by laboratory performance-related testing show that these materials have better mechanical properties than standard base course materials. These results emphasize that the Portuguese processed steel slags could be used in geotechnical works, 203

and particularly in transportation infrastructures (embankments, capping layers and base courses). As regards the environmental aspects, the tested aggregates obtained from the processed steel slags are, from a leacheability point of view, an inert waste. Based on the experience in other countries, as well as to the technical data already collected in this national research project, the Portuguese processed steel slags should be considered as a construction material and, consequently, should be used in competition with natural aggregates for construction of transportation infrastructures and other geotechnical works. ACKNOWLEDGEMENTS The authors would like to thank FCT for the financial support given to this Project (POCI/ ECM/56952/2004), by the program POCI 2010 and cohesion found FEDER. REFERENCES ALT-MAT 1998/1999. Alternative materials in road construction, Project Funded by the European Commission under the Transport RTD Programme of the 4th Framework Programme. COURAGE 1999. Construction with unbound road aggregates in Europe, Final report: 123. E 196-1966 (1967). Soils. Sieving analysis (in Portuguese). Laboratório Nacional de Engenharia Civil, Lisboa, Portugal. E 197-1966 (1967). Soils. Compaction test (in Portuguese). Laboratório Nacional de Engenharia Civil, Lisboa, Portugal. Coronado O. 2005. Study of mechanical behaviour of unbound granular materials compacted at non saturated state under cyclic loading. Phd Thesis. Ecole Centrale Paris (in French). Gomes Correia A., Anhdan L.Q., Koseki J. & Tatsuoka F. 2001. Small strain stiffness under different isotropic and anisotropic stress conditions of two granular granite materials. In Shibuya, Tatsuoka, & Kuwano (eds). Advanced Laboratory Stress-Strain Testing of Geomaterials: 209–215. Balkema, Swets & Zeitlinger. Gomes Correia A., Ferreira S., Araújo N., Castro F., Trigo L., Roque A.J., Pardo de Santayana F. & Fortunato E. 2005. Viability study of Inert Steel Aggregates for Construction (ASIC) for base, subbase, capping layers and embankments. Internal CVR Report 257/2005: 87 (in Portuguese). Gomes Correia A., Ferreira S., Castro F., Trigo L., Roque A.J., Pardo de Santayana F. & Fortunato E. 2006. Viability study of Inert Steel Aggregates for Construction (ASIC) from Seixal Steel Company for base, sub-base, capping layers and embankments. Comparison with Maia ISAC. Internal CVR Report 24/2006: 47 (in Portuguese). Gomes Correia A., Martins J.P., Reis Ferreira S.M., Roque A.J. & Fortunato E. 2008. Trial road section in EN311 Fafe/Várzea Cova. Construction and quality control. Internal CVR Report 2/2008: 20 (in Portuguese). Goto S., Tatsuoka F., Shibuya S., Kim Y.-S. & Sato T. 1991. A simple gauge for local small strain measurements in the laboratory, Soils and Foundations 31(1): 169–180. Hoque E. & Tatsuoka F. 1998. Anisotropy in the elastic deformation of materials. Soils and Foundations 38 (1): 163–179. Iwasaki T., Tatsuoka F. & Takagi Y. 1978. Shear moduli of sands under cyclic torsional shear loading, Soils and Foundations 18(1): 39–50. N P143-1969 (1970)—Soils: Determination of Atterberg Limits (in Portuguese). Roque A.J., Gomes Correia A., Fortunato E., Pardo de Santayana F., Castro F., Reis Ferreira S.M. & Trigo L.A. 2007. The geotechnical re-use of Portuguese inert siderurgical aggregate. XIII PanAmerican Conference on Soil Mechanics and Geotechnical Engineering, Margarita Island, Venezuela 16–20 July 2007. SAMARIS 2002/2005. Sustainable and advanced materials for road infrastructures, Project funded by the European Commission under the Transport RTD Programme of the 5th Framework Programme. Santos J. A. 1999. Soils characterization by dynamic and cyclic torsion tests. Study application of piles behavior under static and dynamics horizontal actions. Phd thesis. Instituto Superior Técnico.

204

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Resilient modulus of hydraulically bound road base materials with high volume waste dust H. Al Nageim & P. Visulios Liverpool John Moores University, Liverpool, UK

ABSTRACT: The paper presents laboratory test results on hydraulically bound road base materials containing high volume of steel slag and blast furnace slag waste dusts compared with control mixtures. These mixtures contain higher levels of (4 mm-0.0 mm) dust compared to standard unbound road base mixtures. The combined influence of the steel slag and granulated blast furnace slag wastes content is to enhance the stiffness of the road base materials and save materials and cost during road construction. Triaxial repeated load tests were performed on the unbound and lightly bound materials to measure their resilient modulus. The test results show important improvements in the bond strength between the contents of road base materials. This offers the prospect of using these materials in road base materials to reduce the use of primary aggregates and thus minimize the cost of road and highway construction. 1

INTRODUCTION: FLEXIBLE PAVEMENT AND ROAD BASE MATERIALS

1.1 General Flexible and rigid road pavements are the typical two types of hard surfaced pavement; Flexible pavements are those, which are surfaced with either hot asphalt mixtures or cold laid mixed bituminous materials. Rigid pavements are composed of concrete surface courses. A flexible pavement structure is generally composed of several layers of materials, see Figure 1. Granular unbound road base layers are extraordinarily strong when properly compacted and confined. In a contrast with pavement surface bound layers of Hot Mix Asphalt (HMA) and Portland Cement Concrete (PCC), which have cohesion and tensile strength to resist the forces from traffic, unbound layers can be pulled apart if subjected to a substantial tensile forces due to the interaction with traffic loads. Therefore granular unbound road base layers are being used in the substructure of the pavement where there are confined and principally must resist compression and shear force action of the traffic on the surface layers (Boyce 1976, Sweere 1990, Niekerk 2002). 1.2 The need for alternative aggregates in unbound road base materials The main uses of unbound road base materials are beneath the HMA (Hot mix asphalt) or PCC (Portland concrete course) wearing and base courses in highways and road pavements,

Surface Course Surface layers

Base Course Sub-base Course or Road Base Materials

Road base layers

Capping Layer (Optional) Sub-grade ( Existing Soil)

Figure 1.

Typical flexible pavement structure.

205

forming the sub-base, and if required capping. Capping is essentially an improvement of the formation and is usually considered part of the earthworks. The function of unbound materials can be summarised as to: a) provide a working platform for construction traffic, b) provide a drainage layer, c) contribute to the structural performance of the finished blacktop or concrete finished pavement and d) to act as a frost protection blanket. Pavement is a key structural element in all highways, roads, walkways, industrial enterprises and airports. It is a foundation that sustains the operational loads generated from traffic, and transfers them to the supporting soil via unbound material bases with out any structural failures or unacceptable settlements. The pavement industrial sector is one of the largest users of unbound materials in the UK and EU. Currently the UK aggregate market is estimated at 270 million tonnes, recycled and secondary 65 millions and demolished and crushed waste of 40 million tonnes (Lay 2006). Unbound road base materials for pavement absorbing more than 135 million tonnes of coarse aggregates. In the last 10 years the rate of using waste and secondary aggregates in unbound materials are significantly increased and certain attention being given to the use of Steel Slag (SS) and Blast furnace Slag (BFS). Currently the market in Europe for 2004 is estimated at 25 million tonnes of which BFS (air-cooled blast furnace slag) uses covers 23% and 77% for steel slag (vitrified slag, granulated or palletised). As far as SS the total amount generated in 2004 in Europe has reached 15 million tonnes, 62% was produced as basic oxygen slag (BOS), 29% as electric arc furnace (EAF) slag and 9% as secondary metallurgical slags. The market condition in the UK shows that there is a production of 0.99 million tonnes of BOS and 0.28 million tonnes of EAF for steel slag and 3 million tonnes of BFS every year (www.aggregain.org.uk March 2006). It is clear that the partial replacement of primary aggregates with waste lime stone dust, Steel Slag (SS) and Blast Furnace Slag (BFS) dusts can make a significant contribution towards reducing current reliance on primary aggregate extraction whilst, the available amounts of waste stockpiles will be minimised. Therefore, the impact of this work is potentially very significant in two ways; first, reducing the extraction of primary aggregates will reduce the environmental impacts of quarrying and any associated social nuisance, and second, developing high value markets for significant waste stream by using alternative aggregates from steel slag and blast furnace slag wastes. Literature review in this area has shown that, steel slag is being used as bound and unbound aggregate: in road sub-base; bitumen bound base (road base) and surface (wearing) courses. Applications of BFS include aggregate used for highway capping and sub-base layers, bitumen bound base (road base), and binder base and surface wearing courses (Dunster 2001). Previous study has shown that SS and BFS posses self binding properties (Nunes 1997, Dunster 2001), and the early stages development of their stiffness and load carrying capacities properties (when they are used as unbound base materials for highway pavement applications) are not fully explored and understood by their users. Recognising the increasing need felt by the unbound and slightly bound pavement engineering practice to advance to more functional specifications for base and sub-base materials, this research application was set up with two aims: 1. To make the initial results for establishing of the early stage mechanical behaviour of road base materials containing high level of waste limestone, SS and BFS dust. 2. To further the understanding of the stress dependent mechanical behaviour of SS and BFS hydraulically bound base materials.

1.3 Blast furnace slag, BFS BFS is the by product produced simultaneously with pig-iron ore in the blast furnace and is composed mainly from calcium and magnesium silicates and alumino-silicates (BS 1047: 1983). BFS usually processed into aggregates and ground granulated blast furnace slag (GGBS), which is a hydraulic binder, often used to partially replace cement in cement bound materials. The main uses of blast furnace slags in the UK and Europe are; in road 206

23% Aircooled BF-Slag

2% Pelletized BF-Slag

75% Granulated BF-Slag

Figure 2. Production of blast furnace slag in Europe in 2004: 24.6 million tonnes (www.euroslag.com, 2006).

0.4% Internal recycling

1.5% Internal storage

1.0% Others9% Secondary steel slag

0.2% Fertilizer

0.3% Hydraulic engineering

32.6% road construction

64.0% Cement production

Figure 3.

Use of blast furnace slag in 2004: 27.2 million tonnes (www.euroslag.com, 2006).

construction as aggregate, for cement manufacture in blended cements, and in general building as a lightweight aggregate. Figures 2 and 3 show the production and uses of blast furnace slag in Europe in 2004. 1.4 Steel slag aggregates in road base materials Steel slag, is a by-product of steel making, produced during the separation of the molten steel from impurities in steel-making furnaces. The use of steel slag (SS) as coarse aggregate is common in granular bases, embankments, engineered fill, highway shoulders, and hot mix asphalt pavements. Prior to its use as a construction aggregate material, steel slag normally crushed and screened to meet the specified gradation requirements for the particular application. Researchers concluded that expansion due to hydration reactions should be addressed prior to use. Figures 4 and 5 show both the production and uses of SS in Europe respectively. 2

ROAD BASE MATERIALS AND TESTING FOR RESILIENT MODULUS

With the overall aim of this study being to make the initial results for establishing of the early stage mechanical behaviour of road base materials containing high level of SS and BFS and 207

9% Secondary Steel slag

62% BOF-Slag

29% EAF-Slag

Figure 4.

Production of steel slags in Europe 2004: 15.2 million tonnes (www.euroslag.com, 2006).

11% Final deposit 6% Others 1% Cement production 45% Road construction 3% Hydrulic engineering 3% Fertilizer 14% Internal recycling 17% Interm storage

Figure 5.

Use of steel slags in 2004: 15.0 million tonnes (www.euroslag.com, 2006).

GBS waste dusts and to further the understanding of the stress dependent mechanical behaviour of SS, GBS and BFS hydraulically bound base materials, it was considered essential to choose a wide range of road base materials as shown in table 1, that would display most clearly the benefits or disbenefits of the high level of waste materials. Four triaxial samples from each of the mixes shown in table 1 were prepared according to the British Standard (BS. EN 13286-1:2003, BS. EN 13286-7: 2004) and tested for the evaluation of Resilient Modulus, Mr, using the triaxial facility at Liverpool John Moores University (LJMU). Samples have been compacted in three equal layers at their optimum moisture contents directly into 150 mm diameter circular moulds with a height of 300 mm. 2.1 Sample preparations and testing procedures The BS EN 13286-4: 2003 Vibrating Hammer method has been applied for manufacturing the triaxial samples. According to this BS, the triaxial sample shall have a diameter larger than 5 times the largest particles size within the materials, and a height twice the diameter of the sample. Since the materials used in this research work were type 1 unbound road base material plus waste dust (4 mm-0.0 mm) as detailed in Table 1, with maximum particle size of 20 mm, therefore all the samples were made with a diameter of 150 mm and a depth of 300 mm. To produce uniform density, the samples were compacted into three equal layers at their optimum moisture contents. For resilient modulus (Mr) testing, BS EN 13286-7:2004 was the standard pattern followed. 208

Table 1.

Material types and mix descriptions.

Material type/mix no.

Mix descriptions

Mix 1 Mix 2 Mix 3 Mix 4 Mix 5 Mix 6

Blast furnace* slag/steel slag type 1 BFS 90/10 SS control Blast furnace slag/steel slag type1 BFS 90/10 + 10% SS dust Blast furnace slag/steel slag type 1 90/10 + 20% SS dust Stancombe type 1 + 20% steel slag dust Stancombe type 1 + 20% steel slag dust + 5% GBS Stancombe type 1 + 20% steel slag dust + 10% GBS

* Stancombe: Primary limestone aggregates used for road base materials in UK.

Table 2. Conditioning stress levels—method B (BS EN 13286-7, 2004). Confining stress, σ3 kPa Deviator stress, σd kPa

High stress level Low stress level

constant

min

max

70 70

0 0

340 200

In this research work, the testing starts with the following steps: i. Sample conditioning using high stress level, see Table 2. According to the road design experts, high stress level is more suitable for unbound road base materials for road and highways carrying heavy traffics, whereas low stress level is suitable for other traffic applications. For a high stress level with a maximum deviatoric stress σd = 340 kPa, the cyclic deviator stresses are applied according to Table 3 for 20,000 cycles and thus the applied stress levels should cover the stress range to which the material will be submitted in the field. The conditioning may be stopped at a lesser number of cycles if the permanent axial strain and the resilient modulus become stable (this condition is satisfied if the axial permanent strain rate becomes less than 10–7 per cycle and if the rate of variation of the resilient modulus becomes less than 5 kPa per cycle). ii. After the conditioning is over, the confining stress is reduced to σ3 = 20 kPa and allow sufficient time for strain stabilisation (e.g. a rate of change of less than 10–4 per minute). Then, according to the selected maximum stress level, in this research work 340 N/mm2, the stress levels with confining pressures of 20 kPa to 70 kPa are applied according to Table 3. If higher values of stress σ3 are likely to occur in the application envisaged for the material, the remaining stress levels in the table can be applied. Each cyclic loading is carried out for 100 cycles, recording the stress and strain values at least from cycle number 90 to cycle number 100. When the stress paths are completed, the specimen is removed from the cell, the measuring system and membrane is taken off, and the water content of the sample is determined using the entire specimen. Figure 6 illustrates a schematic sketch of the triaxial cell containing a sample ready for test. Axial linear variable displacement transducers (LVDTs) have been mounted vertically on the sample prior to putting the sample into the cell. Radial LVDTs are already installed on the cell. Having the cell sealed, the LVDTs are connected to the computer and software receives data and records them according to the BS EN 13286-7:2004 in a file. 2.2 Resilient modulus measured in triaxial tests The stress-strain relationships generally used to characterize granular materials make use of Hook’s law governing the behaviour of elastic and isotropic materials: 209

Table 3. Stress levels for the resilient behaviour—method B (BS EN 13286-7, 2004). High stress level

Low stress level

Confining stress, σ3 kPa

Deviator stress, σd kPa

Confining stress, σ3 kPa

Deviator stress, σd kPa

constant

min

max

constant

min

max

20 20 20 20 35 35 35 35 35 50 50 50 50 50 70 70 70 70 70 100 100 100 100

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

30 50 80 115 50 80 115 150 200 80 115 150 200 280 115 150 200 280 340 150 200 280 340

20 20 20 20 35 35 35 35 35 50 50 50 50 50 70 70 70 70 70 100 100 100 100

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

20 35 50 70 35 50 70 90 120 50 70 90 120 160 70 90 120 160 200 90 120 160 200

⎧ ε1 ⎫ ⎡1 ⎪ ⎪ 1⎢ ⎨ε 2 ⎬ = ⎢ −ν ⎪ε ⎪ E ⎢ −ν ⎣ ⎩ 3⎭

−ν 1 −ν

−ν ⎤ ⎧σ 1 ⎫ ⎪ ⎪ −ν ⎥⎥ ⎨σ 2 ⎬ 1 ⎥⎦ ⎪⎩σ 3 ⎪⎭

(1)

where ε1, ε2, ε3 = major, intermediate and minor principal strains respectively, σ1, σ2, σ3 = major, intermediate and minor principal stresses respectively, E = Young’s modulus, and ν = Poisson’s ratio. In unbound pavement engineering, the term Young’s modulus is replaced by resilient modulus (Mr) due to the non-linear stress-dependent behaviour of granular materials. With this replacement and for the triaxial axisymetric conditions, the previous equation becomes: Mr =

ν=

σ 12r + σ 1r σ 3r − 2 σ 32r σ 1r ε1r + σ 3r (ε1r − 2 ε 3r )

(2)

σ 1r ε 3r − σ 3r ε1r 2 σ 3r ε 3r − ε1r (σ 1r + σ 3r )

(3)

where ν = Poisson’s ratio, σ1r, σ3r = major and minor repeated principal stresses respectively, ε1r, ε3r = major and minor repeated principal strains respectively.

210

1. Specimen, 2. Membrane, 3. Specimen cap, 4. Specimen base, 5. Load cell, 6. Axial linear variable displacement transducer, 7. Radial linear variable displacement transducer, 8. Triaxial cell wall, 9. Pressure transducer, 10. Studs supporting the displacement transducer, 11. Drainage circuit Figure 6. Example of triaxial cell and systems for measuring axial and radial displacements using linear variable displacement transducers (BS EN 13286–7, 2004).

3

RESULTS & DISCUSSION

The resilient modulus (Mr) due to the non-linear stress-dependent behaviour of granular materials in road base is determined using the triaxial test. Figure 7 and 8 show the triaxial testing results of the 6 mixes. All the mixes were manufactured at their optimum moisture contents and stored in the laboratory at a temperature of approximately 20ºC for 28 days before testing. The figures show the Mr values for the following deviator stresses and their corresponding confining pressures applied. Note, at the two confining pressure values, the Mr values are the same for their corresponding deviator stress, see Table 3. According to Figures 7 and 8, the resilient modulus for all the 6 materials tested increases with the increase value of the deviator stress at the confining pressure shown in table 4. In Figure 7 and at deviator stresses of 73 and 125 and where the confining pressure value is 20 N/mm2 or 35 N/mm2, the addition of 10% Steel Slag SS waste dust (all dust used in this research work is made from 0.0–4 mm size materials) to the 90BFS/10SS control mix yields improvements in resilient stiffness Mr of 12.10% and 25% respectively, whereas adding 20% SS waste dust to the control mix yields an improvement in the values of Mr of 44.11% and 50% respectively. At a confining pressure of 50 N/mm2 or 70 N/mm2 and at a deviator stress of 210 the addition of 10% of SS waste to the control mix yields improvements in resilient stiffness Mr of 46.0%, whereas adding 20% SS waste dust to the control mix yields an improvement in the values of Mr of 58.0%. This indicates that the value of Mr is a function of both the deviator

211

1200

Resilient 1000 Modulus (N/mm2)

800 600 400 200 0 73

125

170

210

250

310

Deviator Stress (N/mm2) BFS 90/10 Control Figure 7.

BFS 90/10 + 10% SS

BFS 90/10 + 20% SS dust

Resilient modulus of mixes containing waste BFS and SS dusts.

5000 Resilient 4500 4000 Modulus 3500 3000 (N/mm2) 2500 2000 1500 1000 500 0.00 73 Limestone + 20% SS dust

Figure 8.

125

170 210 Deviator stress (N/mm2)

Limestone + 20% SS dust + 5% GBS

250

310

Limestone + 20% SS dust + 10 % GBS

Resilient modulus for the mixes containing Limestone, SS, and GBS waste dusts.

Table 4.

Deviator stresses and confining pressures applied.

Deviator stress (N/mm2) Confining pressure (N/mm2)

73

125

170

210

250

310

20, 35

20, 35

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stress and the confining pressure. In the opinion of the authors, the increase in the amount of dust in the control mix may increased the bonding and density of the internal interlocking status of the micro structure of the samples, due to the increase of hydration products which act as a binding agent in the mixes. This is under investigation in this research project and the results will be published in another paper in the near future. Figure 8 shows an outstanding increase in the resilient modulus of the following mixes compared with the limestone control mix + 20% SS dust; Mix 5: Limestone + 20% SS dust + 5% GBS, Mix 6: Limestone + 20% SS dust + 10% GBS, At both deviator 73 and 310 kPa and at confining pressure of 20 N/mm2 and 70 N/mm2 respectively, Mix 5 achieved an improvement in its Mr values of approximately 194.11% and 237% respectively. However mix 6 displayed an improvement of 370.50% and 533% respectively. A closer look at these mixes suggested that they are concrete-like road base mixes with high compressive strength. This has suggested that the lime stone dust has reacted with the SS dust in the present of the GBS dust. 212

Therefore at LJMU and in collaboration with our industrial partners, Department of Trade Industry in the United Kingdom (DTI), Aggregate Quarry Association and Tarmac ltd, more work is currently undertaken using XRD, ESM, and other normal concrete testing analysis to investigate the mechanical behaviour of these mixes. The research work was extended to include the use of other wastes materials, lime and different PFA. The research results have shown very interesting trends to explain reasons behind the increase in the moduli of the mixes and other mechanical properties at different ages. This extention of the work will be a subject of another paper to be published in the next BCR2 A conference and to include practical guidelines for the use of waste BFS and SS in road base materials. 4

CONCLUSIONS

1. Granulated blast furnace slag possesses slow and progressive setting and hardening thus has the particularity of binding ability during construction and good early-age mechanical stability. 2. The addition of steel slag dust at a percentage of 10% of the total weight of the road base materials to the control mix resulted in a significant increase in the mixes Resilient Modulus, Mr. This conclusion is also true for the BFS 90/10SS control mix when it contains 20% SS dust added to the mix. The authors contribute this increase in the Mr values to the increase in the state of dense interlocking status between the coarse and fine aggregates within the mixes and the increase of the “cement-like” hydration products. It is commonly known that the increase in the non reactive fine material within the compacted road base materials will reduce the optimum interlocking status between the graded aggregate content of the mix and hence the values of Mr. However in this research work results indicate that the SS and GBS dust have reacted and resulted in a strong road base materials. 3. When the GBS dust added to the control mix with 20% SS dust, an outstanding improvement in the values of Mr were achieved again indicating that the SS has reacted with the rest of the mixes contents and produced bound materials or concrete-like materials. 4. Mixes contain limestone + SS dust with added GBS dust show the highest improvement in the values of Mr. This has led to further research work at LJMU in collaboration with our industrial partners to explain the reasons behind this improvements using conventional concrete testing, chemical testing, XRD and EMS techniques on samples made from different mixes containing different amount of waste dusts including the use of PFA, lime and other wastes materials at different testing environment and the results will be published in another paper in the next BCR2 A conference. REFERENCES Boyce, J.R. 1976. The behaviour of a granular material under repeated loading, PhD Thesis, University of Nottingham. UK. BS. 1047–1983. Specification for air-cooled blast furnace slag aggregate for use in construction. BS. EN 13286-1:2003. Unbound and hydraulically bound mixtures. Test methods for laboratory reference density and water content. Introduction, general requirements and sampling. BS. EN 13286-7:2004. Unbound and Hydraulically bound mixtures. Part 7: Cyclic load triaxial test for unbound mixtures. Dunster, A. 2001. Information Paper 18/01. Blastfurnace slag and steel slag their use as aggregates. CRC London. Kendrick, P. et al. 5th ed. 2004, Roadwork. London: Elsevier. Lay, J. 2006. Alternative aggregates. LJMU international conference on sustainable aggregates, pavement engineering & asphalt technology, Feb. 2006. Niekerk, A.V. 2002. Mechanical behaviour and performance of granular bases and sub-bases in pavements, PhD thesis, Delft University of Technology, The Netherlands. Nunes, M.C. 1997. Enabling the use of Alternative Materials in Road Construction, PhD Thesis, University of Nottingham, UK. Sustainable Aggregate Information Service provided by WRAP www.aggregain.org.uk Sweere, G.T. 1990. Unbound Granular Bases for Roads, PhD thesis, Delft University of Technology, The Netherlands.

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Characterizing natural and recycled granular materials for (sub)base layers of roads by cyclic triaxial testing C. Grégoire, B. Dethy & J. Detry Belgian Road Research Centre, Belgium

A. Gomes Correia University of Minho, Guimarães, Portugal

ABSTRACT: The cyclic load triaxial test is a laboratory test which makes it possible to study the mechanical behaviour (resilient and permanent deformations) of unbound granular materials used in base and subbase layers of roads. This paper describes the equipment of the Belgian Road Research Centre and presents the first results obtained for a natural material commonly used in Belgium and two recycled materials (crushed concrete aggregate and steel slag). The influence of water content and the compaction method on resilient strains is analysed. 1

DESCRIPTION OF THE CYCLIC TRIAXIAL TEST EQUIPMENT

1.1 Principle of the cyclic load triaxial test The cyclic load triaxial test apparatus makes it possible to simulate in the laboratory the behaviour of unbound materials used in base and subbase layers of road pavements under moving loads. Work by Corté (1994), Paute et al. (1994), Balay et al. (1998), and Correia (2004) illustrated the use of this test to determine the resilient and permanent strains of asdug granular material while investigating the influence of parameters such as water content, dry density, or the method of compaction. In this test, a cylindrical specimen is subjected to cyclically varied axial stresses (σ1) and a confining pressure (σ3). For a given stress state, the confining pressure either remains constant (CCP tests) or varies in phase with the axial stress cycles (VCP tests). This test makes it possible to define, on the one hand, the resilient modulus required as an input in design calculations for road structures and, on the other, the permanent strains related to rutting. The cyclic triaxial test equipment presented in this paper was developped by CVR «Centro para a valorização de residuos» in Guimarães (Portugal). 1.2 Frame The steel frame (30 kN) is very stiff and is capable of absorbing the forces applied during testing. It consists of two parallel platens and four hollow columns. Each column is terminated by a threaded rod fastened by two nuts. The columns of the frame are assembled by prestressing. 1.3 Pressuring system For tests under constant confining pressure, the axial actuator is controlled by a hydraulic system and the confining pressure in the cell (“pressure chamber”) is controlled by a pneumatic system. Air is used as chamber fluid. For tests under variable confining pressure, two separate actuators (50 kN) respectively control the axial pressure and the confining pressure. The control of the two actuators is hydraulic. De-aired water is used as chamber liquid. 215

Figure 1.

Cyclic triaxial test equipment of the Belgian Road Research Centre.

1.4 Triaxial cell The diameter of the triaxial cell (35.5 cm) is large enough to accommodate a specimen 16 cm in diameter and 32 cm in height, as well as several sensors. The wall of the cell is transparent, which makes it possible to observe the test in progress. The specimen cap and base provide drainage from both ends of the specimen. When opened, the external part of the cell disconnects from the base. Access to the connectors is easy. The axial force sensor (25 kN) that measures the force applied to the specimen is inside the cell, close to the cap. This allows more accurate measurement of the force as directly applied to the specimen. The cell is also fitted with two pressure sensors, to measure the confining pressure in the cell. It is planned to equip the cell with external displacement sensors and bender elements. 1.5 Deformation sensors The standard EN 13286-7 does not impose the type of deformation sensors (Linear Variable Displacement Transducer, hall effect deformation transducer, Local Deformation Transducer…). Some possibilities are given, as for example using LVDT connected to the specimen with studs embedded in the specimen or, for the radial deformation, flexible epoxy resin rings instrumented with strain gages. The standard EN 13286-7 specifies the use of at least 2 transducers for the axial deformations and at least one transducer for the radial deformation. For our research, we choose to use LDTs because there are quite convenient for granular materials and do not require the placement of studs in the specimen. Moreover, the LDTs are capable of measuring strains smaller than 10–5 and have good resolution for strains up to 2% (Goto et al., 1991; Hoque et al., 1997). The LDTs (Local Deformation Transducers) consist of four strain gauges forming a full Wheatstone bridge, glued to a thin flexible strip of phosphor bronze (Goto et al., 1991; Hoque et al., 1997) with a low coefficient of thermal expansion. Four LDT sensors are attached to the specimen: three to measure axial strains and the fourth to measure radial strain. Each axial LDT is kept between two pseudo-hinged attachments glued to the membrane of the specimen. The radial LDT is maintained on an adapted attachment composed of two tapered pieces on which the ends of the sensor rest (Fig. 2). This attachment is maintained on the specimen by two threads and two springs. As the distance between the two attachments is slightly shorter than the length of the LTD strip, the latter is slightly pinched. The working principle of the LDTs is schematically represented in Figure 2. Deformation of the specimen causes relative displacement of the attachments and arching of the LDT. 216

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The output voltage, V, of the LDT is related to the distance between the attachments (lo at the beginning of the test (t = 0), and l at a given moment (t = t). The relation between the output voltage, V, and the distance, l, between the attachments is a second-degree polynomial. Calibrations by the Belgian Road Research Centre are made with a device fitted with a micrometer which has a resolution of 10 microns and a range of 25 mm. The micrometer checks the movement of the LDT. The axial LDTs are calibrated at intervals of 0.1 mm over a relative displacement of the attachments of 4 mm (Δ – Δo)—corresponding with a strain of 2%—, in loading and release. The radial LDTs are calibrated at intervals of 0.1 mm for a relative displacement of the attachments of 2 mm, in both loading and release. For each position 217

of the LDT data is captured for some ten seconds, to define a mean voltage. A second-degree polynomial describing the “distance between attachments/voltage” relation is defined for each calibration. The hysteresis between the curves in loading and release is small. The successive calibrations have demonstrated good repeatability of “distance between attachments/voltage” curves. Comparison of calibration curves made at different moments reveals minor variations between the different curves, viz. in slope (see Figure 3). 2

TESTS

2.1 Objectives of the tests The tests aim at characterizing the resilient behaviour of a reference material commonly used in (sub)base layers of Belgian roads and of two recycled materials, for comparison. The reference material is limestone 0/20 mm. The two recycled materials tested are crushed concrete aggregate 0/32 mm and steel slag 0/32 mm. Those recycled materials are available in Belgium and are accepted to be used in (sub)base layers under certain established conditions. The particle size distributions of the analysed materials are given in Figure 4. The tests are made under constant confining pressure, using method B of European standard EN 13286-7. Various water contents and densities are tested for a given material. The repeatability of the test is analysed by performing a test under given conditions three times. It is planned to conduct similar tests under variable confining pressure (method A of the standard) at a later stage. 2.2 Preparation of specimens After homogenization and oven drying, each material is separated into four or five particle size fractions in order to manufacture specimens of equal particle size distribution for testing. For the limestone, water is added and the fractions are mixed just before the specimen is compacted. For the secondary materials, which may absorb water, the mixtures are prepared one to several days before compaction and stored in hermetically sealed bags. The specimens are compacted with a vibrating hammer (EN 13286-51), in six layers. A few specimens prepared with the natural material were compacted by vibrocompression, for CRR-OCW 21761

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comparison. With this method (EN 13286-52) it is possible to compact the specimen in a single layer, by simultaneous horizontal vibration and light axial compression in a mould. Optimum density and water content were determined by modified Proctor testing. After compaction, the mould is removed and a membrane encases the specimen during the test. 2.3 Study of reversible deformations Conditioning (20,000 cycles, as required by standard EN 13286-7) is applied to the specimen, in order to stabilize the permanent strains. To study reversible deformations, various stress paths are applied successively on the basis of one hundred cycles per stress path, according to method B of the standard. The standard specifies that the loading frequency has to be maintained between 0.2 Hz and 10 Hz. The test is done at a loading frequency of 1 Hz. The conditioning is done at a loading frequency of 2 Hz, which makes it possible to shorten the duration of the full test procedure (conditioning and the study of reversible deformations) to one day. It was verified that the imposed loading was reached at this higher frequency. From the analysis of resilient strains the resilient modulus can be determined for each stress level. The analysis of the conditioning process makes it possible to determine the characteristic permanent strain of the material. 2.3.1 Results for the limestone The optimum water content of the limestone 0/20 mm is 5.5% (wOPM) and its optimum density 2.304 g/cm3. The fines content of the limestone 0/20 mm is 7.4%. At optimum water content (wOPM) several compaction densities were tested: 95, 100, and 102% of the optimum density (ρOPM). At optimum density different water contents were tested: wOPM – 1%, wOPM, wOPM + 1%, and wOPM + 2%. With water contents above the optimum value, the limestone specimen is close to saturation. The analysis of permanent strains at the end of conditioning is based on characteristic permanent strain which characterizes the resistance to permanent deformations. This parameter is defined in the standard EN 13286-7 and is used for ranking of materials. This is the difference between axial permanent strain at the end of conditioning—after 20,000 cycles—and axial permanent strain after 100 cycles:

ε1c = ε1p (20000 ) − ε1p (100 )

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Characteristic permanent strain decreases with increasing degree of compaction. When density is increased from 95% to 102% ρOPM, this strain drops from 58.10–4 to 2.10–4 (see Figure 5). Characteristic permanent strain increases significantly when water content rises from wOPM—1% to wOPM. It rises from 10.10–4 to 30.10–4 (see Figure 6). The resilient modulus is calculated as M r = Δq / Δε1r where q is the deviator stress (or σd) as in Eqn. 3 and q = (σ1 – σ3)

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As shown in Correia et al. (2001), the increase of the resilient modulus with vertical stress, σ1, is a power law (see Figure 7). The resilient modulus increases with density and decreases with water content (Fig. 8). The resilient modulus is analysed for a reference stress state approximating the stress state defined by the standard to calculate a characteristic elastic modulus (EN 13286-7, annex C; p = 233 kPa and q = 400 kPa). 220

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At this reference stress state, the resilient modulus varies from 490 MPa to 660 MPa when density is increased from 95% ρOPM to 102% ρOPM. At this stress state and at optimum density, the resilient modulus varies from 600 MPa to 510 MPa when water content is increased from wOPM – 1% to wOPM + 2%. 2.3.2 Results for the crushed concrete aggregate The optimum water content of the crushed concrete aggregate 0/32 mm is 10% (wOPM) and its optimum density 2.006 g/cm3. Fines content is 5.3%. At optimum water content (wOPM) several compaction densities were tested: 95, 97, and 100 of the optimum density (ρOPM). At optimum density different water contents were tested: wOPM – 1%, wOPM, and wOPM + 1%. At wOPM + 1%, the specimen is close to the saturation and it is why specimens at wOPM + 2% were not tested. Characteristic permanent strain decreases with dry density (Fig. 5). At optimum water content it is smaller than for the reference limestone. Characteristic permanent strain increases considerably when water content rises from wOPM to wOPM + 1% (see Figure 6). At this water content it is much greater than for the reference limestone. As for the limestone, the increase of the resilient modulus with vertical stress, σ1, is a power law (Fig. 7). The resilient modulus of the crushed concrete aggregate increases with density and decreases with water content (see Figure 8). In the reference stress state (p = 233 kPa and q = 400 kPa) it is 550 MPa, 640 MPa and 670 MPa, respectively for compaction levels of 95, 97 and 100% of optimum density. In this reference stress state and at optimum density, the resilient modulus varies from 820 MPa to 460 MPa when water content is increased from wOPM – 1% to wOPM + 1%. This indicates that the crushed waste concrete tested is more sensitive to water than the reference limestone. The resilient moduli of the crushed concrete aggregate are higher than those of the reference limestone. For the reference stress level and at optimum density and water content, the resilient moduli of the crushed concrete aggregate and the limestone are 670 and 530 MPa, respectively. 2.3.3 Steel slag The optimum water content of the 0/32-mm slag is 6% (wOPM) and its optimum density 2.554 g/cm3. Fines content is 4.0%. At a water content equal to the optimum (wOPM) several compaction densities were tested: 95, 97, and 100% of the optimum value (ρOPM). At a density equal to the optimum, different water contents were tested: wOPM – 1% and wOPM. It was not possible to make a specimen at water contents higher than wOPM. 221

Figure 9. Influence of the compaction method on the characteristic permanent strains (left) and the resilient modulus of limestone 0/20 (right).

Characteristic permanent strain decreases with dry density (see Figure 5). At optimum water content it is smaller than for the reference limestone. Characteristic permanent strain does not increase significantly when water content rises from wOPM – 1% to wOPM (see Figure 6). At these water contents it is smaller than for the reference limestone and of the same order of magnitude as for the crushed concrete aggregate. As for the limestone, the increase of the resilient modulus with vertical stress, σ1 is a power law (see Figure 7). The resilient modulus of the slag increases with density and decreases with water content (see Figure 8). At the reference stress state (p = 233 kPa and q = 400 kPa) this modulus varies strongly when density is increased from 97% to 100% of the optimum: values are, respectively, 390 MPa, 510 MPa and 850 MPa for rates of compaction of 95, 97 and 100%. At densities of 97% ρOPM and above the resilient modulus of the slag is higher than for limestone. At this reference stress state and at optimum density, the resilient modulus varies from 1,050 MPa to 850 MPa when water content is increased from wOPM – 1% to wOPM. This means that the tested slag is more sensitive to water than the reference limestone. At these water contents the slag has higher resilient moduli than the reference limestone and the crushed concrete aggregate. 2.3.4 Influence of the compaction method A few tests were made on specimens of limestone, to analyse the influence of the compaction method. These specimens were compacted by vibrocompression. The specimens compacted by vibrocompression have higher characteristics permanent strains than those compacted by the vibrating hammer method (see Figure 9). On the other hand, the compaction method does not seem to have any influence on resilient strains (see Figure 9). 3

CONCLUSION

Cyclic load triaxial tests under constant confining pressure were performed on a natural material (limestone) and on two secondary materials (crushed concrete aggregate and steel slag). The loading frequency was 2 Hz during conditioning and 1 Hz during the actual test. This made it possible to complete the full test procedure in one day. For all stress states analysed, the resilient moduli at optimum density and water content of the slag and the crushed concrete aggregate are higher than those of the limestone. The slag has a higher resilient modulus than the crushed concrete aggregate. For the three materials tested, the increase of the resilient modulus with vertical stress, σ1, is a power law. The influence of water content and dry density on the resilient modulus was investigated for a reference stress state. For the three materials the resilient moduli decrease with water 222

content and increase with dry density—at water contents close to the optimum value. The resilient modulus of the secondary materials is more sensitive to water than that of the limestone. Dry density has a strongly marked effect on the resilient modulus of the slag. Characteristic permanent strain increases with water content and decreases with dry density, for the three materials. At water contents equal to or lower than the optimum, the limestone exhibits the highest value for characteristic permanent strain. The characteristic permanent strains of the slag and the crushed concrete aggregate are of the same order of magnitude. At water contents above the optimum, the crushed concrete aggregate has a higher characteristic permanent strain than the limestone. The method used to compact the specimens (vibrating hammer or vibrocompression) does not seem to affect resilient strains, but does have a strong influence on characteristic permanent strains. In the next stage of this study the same tests will be performed under variable confining pressure. ACKNOWLEDGEMENTS The authors thank the geotechnical department of the University of Minho, especially Mr. Nuno Araújo and Ms. Sandra Ferreira for their help in using the equipment. REFERENCES Balay, J., Gomes Correia, A., Jouve, P., Hornych, P. & Paute J.-L., 1998. Etude expérimentale et modélisation du comportement mécanique des graves non traitées et des sols supports de chaussées—Dernières avancées. Bulletin liaison Labo. P. et Ch. 216: 3–18. Corté, J.-F., 1994. Caractéristiques mécaniques des graves non traitées au triaxial à chargements répétés. Bulletin liaison Labo. P. et Ch. 190: 17–26. Gomes Correia, A., Anhdan, L.Q., Koseki, J. & Tatsuoka, F., 2001. Small strain stiffness under different iso-tropic and anisotropic stress conditions of two granular granite materials. In Shibuya, Tatsuoka & Kuwano (eds). Gomes Correia, A., 2004. Evaluation of mechanical properties of unbound granular materials for pavements and rail tracks. Proceedings of the international Seminar on Geotechnics in Pavement and Railway Design and Construction. Gomes Correia & Loizos eds., Millpress Rotterdam, Netherlands, Athens, 16 December 2004: 35–60. Goto, S., Tatsuoka, F., Shibuya, S., Kim, Y.-S. & Sato, T., 1991. A simple gauge for local small strain measurements in the laboratory. Soils and foundations, Vol. 31, 1: 169–180. Hoque, E., Sato, T. & Tatsuoka, F., 1997. Performance evaluation of LDTs for use in triaxial tests. Geotechnical testing Journal, Vol. 20, 2: 149–167. Paute, J.-L., Hornych, P. & Benaben, J.-P., 1994. Comportement mécanique des graves non traitées. Bulletin liaison Labo. P. et Ch. 190: 27–38. EN 13286-7 Unbound and hydraulically bound mixture—Part 7: Cyclic load triaxial test for unbound mixtures.

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Resilient modulus of unbound base material containing extra waste Stancombe limestone dust B. Saghafi & H. Al Nageim Liverpool John Moores University, Liverpool, UK

ABSTRACT: The principal aim of this project is to reduce the demand for the extraction and use of primary aggregates and the associated environmental impacts. To monitor the effect of adding Stancombe limestone dust on resilient modulus of the unbound aggregates. 10%, 20% and 30% dust were added to the Stancombe Type 1 road base material and were tested at different moisture contents using triaxial machine. Samples were left air cured for one month, because it was predicted that binding might happen due to high free-lime content of the Stancombe limestone dust. The results show that control samples, which contain no dust, were the strongest at their optimum moisture content and samples containing extra dust had lost considerable amount of their resilient modulus, verifying previous conclusions regarding fine particle negative effects on the behaviour of unbound samples; however, less water content sensitivity of the samples with extra dust amount has been remarked. 1

INTRODUCTION

Direct demand for investigation on recycling waste materials and accommodate them among other common construction materials comes from UK government policy as well as waste producers, waste managers, construction clients and the construction products industry. The cost of waste disposal is increasing and alternative solutions will be needed by producers in order to control this. Creating a market for common wastes will reduce volumes and provide economic advantage over disposal, as well as reducing the associated environmental and social impacts. Waste managers need to predict and control waste streams in order to manage their businesses effectively. Construction clients are becoming increasingly aware of the need to act in a more sustainable way and to welcome the use of alternative materials. This is particularly the case for government construction clients who must respond to government policy as expressed through the UK Office of Government Commerce. The construction industry is actively looking for ways to increase reuse or recycling, both to meet the needs of its customers and to place itself within an emerging market for alternative materials. Recent investigations indicate that 106 million tonnes of limestone rock, usually crushed at quarry sites, has annually been extracted during 2002, which produced nearly 22 million tonnes of fine aggregate in industrial sections at the end of each year (Manning 2004). Fine aggregate refers to the range of aggregate less than 4 mm in size. All these materials are produced from the various quarries around the UK where their total number reaches up to 1300 quarries. Further to the UK and as examples, production of annually 18 million tones of limestone dust in Greece and 30 million tones in Turkey have been reported (Manning 2004, Galetakis & Raka 2004). Disposal of limestone dust causes dust distribution, environmental problems and pollutions because of its fine nature. It contaminates the air with the storms in the summer and spring seasons and therefore causes serious health hazards including specifically asthma and lung diseases (Turgut & Algin 2006, Felekoglu 2007). The industry suffers to store limestone dust due to the costs of storage. The principal aim of this project is to reduce the demand for the extraction and use of primary aggregates and the associated environmental impacts. This will be achieved by technical development of alternative aggregates to replace some of the coarse and fine aggregate 225

fractions in unbound base and subbase materials used beneath the roads, highways and airfield blacktops or concrete wearing. A secondary aim is to develop high value markets for significant waste streams by using alternative aggregates produced from limestone dust. The dust issue exists for many quarries, some to greater extents than others. Limestone dust is a type of waste produced during quarry activities on extracted limestone rocks and refers to waste aggregate of 0 to 4 mm in size. Limestone dust has made problems for the UK and all around the world. Currently, the blocks of limestone are extracted via chain saw, diamond wire and diamond saws from quarries and then the blocks are cut into smaller suitable sizes to be used as building material. Assuming annual production of aggregates from 2007 in Great Britain is around 238 million tonnes (British Geological Survey 2007) then the total annual production of limestone quarry fines in Britain is estimated to be of the order of 41 million tonnes (Manning 2004, Turgut & Algin 2006). According to a recent research in the UK (Manning 2004), limestone is the most common type of rock used in the UK and 20–25% of the rock changes into fines during crushing process. Most of these wastes are disposed of in landfills or open-dumped into uncontrolled waste pits and open areas. Disposal of this product waste is a major problem for many small businesses as well. Therefore, any acceptable solution of this problem with a commercial value is crucial. Stancombe is a Tarmac quarry, containing a great amount of carboniferous limestone, situated just outside of Bristol, the UK. A historic issue for the quarrying industry has been the production of ‘quarry dust’ when extracting and subsequently crushing the rock. Outlets exist for this excess dust such as concrete plants, however, not to the quantity that the dust is produced and for this reason Stancombe quarry has a stockpile in excess of 250,000 tonnes of this 0–4 mm dust for which Figure 1 shows the grading. Using high amount of fine in unbound aggregate decreases the strength of mix because of high surface area of fine material, which absorbs more water, leading to particles sliding on each other under load application, friction lessening, and finally, loss in mix stability will be resulted. In addition, the mix aggregates interlocking characteristics will be reduced and thus both the mix shear strength and rutting resistance will be minimised too comparing with the normal Type 1 grading commonly recommended by road engineers. But nowadays, the increased interest in the successful using of high volume dust in different construction applications such as cement and asphalt concrete, self-compacting concrete, and artificial stones, tiles and building materials can be seen (Terzi & Karashin 2007, Galetakis & Raka 2007, Turgut 2007, Felekoglu 2007, Turgut & Algin 2006, Manning 2004, Bosilikov 2003, Felekoglu & Baradan 2003). All these have led the UK Government to invest into this research project.

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40

20

0 63

31.5

16

8

4

Size (mm)

Figure 1.

Grading diagram of Stancombe 0–4 mm dust.

226

2

1

0.5

0.063

Chemical analysis of the Stancombe limestone dust shows that this material is a CaOrich dust; therefore, it should be helpful in gaining extra strength with time for the road base material containing high volume of limestone dust at the presence of enough moisture and can compensate the loss of shear strength. Consequently, the research team decided to carry out some repeated load triaxial tests to measure the resilient modulus of the road base materials with different dust amounts at different moisture contents and compared them with the resilient modulus of the control mix containing no extra dust. Normally, when a new material is being used for a base course, it should be tested for some criteria mentioned in practical manuals and pavement design books. Resilient modulus, Mr, in addition to shear strength and rutting resistance are is a very important characteristic of the unbound materials that are normally used by road engineers. This parameter affects base course and asphaltic layer thickness directly. Obviously, the material should be tested for other issues such as permeability, durability, permanent deformation, etc. (Huang 2004, Yoshida et al. 2003, Croney 1977). CBR (California Bearing Ratio) is a traditional, empirical value for characterising the materials total strength and is one of the input parameters for most of non-mechanistic asphalt pavement design methods (Huang 2004, Yoshida et al. 2003). 2

DUST USAGE BACKGROUND

A report published by the Mineral Solution Ltd. in 2004 includes using quarry fines in different applications (Manning 2004). Indicating the use of limestone dust in unbound road base materials, he cites a 2002 project of using quarry fines instead of coarse aggregate in road base construction. He has not indicated the type of the quarry fines used in the mixes. In his document, he has cited a project, published in 1996, implying the strengthening limestone fill by another fine material, which puts forward another use of limestone dust in the field of bound mixes. Uthus (2007) has concluded that presence of fine mica decreases mechanical properties of unbound aggregate of Norwegian Gneiss, leading to more permanent deformation. Cheung & Dawson (2002) studied the effects of particle and mix characteristics on the performance of some granular materials and have related unbound granular material behaviour to the particles’ surface roughness, surface friction, angularity and roughness, indicating increase in stiffness with surface roughness and friction without stating grading. Citing several researches since 1970, Lekarp et al. (2000) believe that the researches on the effect of fine material on unbound aggregate stiffness have not been investigated completely clearly. Generally, decrease in resilient modulus and increase in permanent deformation have been reported when the fine content increases. Although most of the conclusions have led into negative effect (both minor and dramatic influence) of fine materials on mechanical properties of unbound aggregates, a few enhancement cases have been reported. Lekarp et al. (2000) stated that Jorenby & Hicks (1986) had experienced some initial stiffness increasing and then a notable drop when fine material had been added to crushed aggregate. The results of a similar research indicated that adding stone dust up to 10% by mass improves the bearing capacity of the base course in terms of CBR (California Bearing Ratio) while 5% fine material has been determined as the maximum range for clay (Babic et al. 2000). Thom & Brown (1987) did a vast study on the properties of crushed-limestone road base, investigating the effect of moisture and fine on the structural performance of crushed-limestone road base. They have pointed out decrease in elastic stiffness with increasing moisture for broadly graded materials as well as stiffness reduction by fine amount increase. There are other studies and applications of limestone dust for the industry of construction. Turgut (2007) and Turgut & Algin (2006) have investigated some of the physical and mechanical properties of brick materials having various levels of limestone powder waste co-operated by wood sawdust wastes. The obtained mechanical properties such as compressive strength, flexural strength, unit weight, etc. can satisfy the relevant international standards. Using these materials as cement composites in manufacturing concrete bricks has led to lightweight bricks that can meet the standard criteria. Galatakis & Raka (2003) have applied limestone dust for artificial stone production consisting mainly of limestone dust 227

in an experimental level. The results show mixing limestone quarry wastes and cement can be used for making concrete stones with acceptable mechanical properties. Felekoglu (2007) aimed to change limestone quarry wastes into a valuable resource. He has investigated the usability of limestone dust in self-compacting paste and concrete. 3

RESEARCH METHODOLOGY

Manufactured samples were made from Stancombe Type 1 aggregate as a control mix and other three mixes with additional 10%, 20%, and 30% Stancombe limestone dust. All the mixes were manufactured at optimum moisture content (OMC), OMC – 2%, OMC – 1% and OMC + 2%. Type 1 base course material is a common grading used for unbound base and subbase materials in the UK (Figure 2), and indicates a special range of unbound aggregate which normally makes the base layer able to work as a sustainable one for carrying the loads from the pavement structure and the traffic. The grading envelope of this layer, which is defined in the UK Design Manual for Roads and Bridges/Pavement Design, has two upper and lower limits and thus control the amount of coarse and fine particles to be included in the road base material; the former contains more fine and the latter contains more coarse aggregate. Therefore, adding extra dust will lead research work to have a curve closer to the upper limit. As the material becomes close to the upper limit, its bearing capacity will be affected. The new material should be tested using the common tests normally required by road engineers to make sure that all the criteria necessary for an unbound base course material are met. Although shear strength and rutting resistance ability of the unbound material are very important, at this stage, the research project team decided to test the materials for resilient modulus and depending on the results, the amount of fines in the control mix will be optimised to produce a road base materials containing high level of dust and satisfying the strength requirements of such layer. According to BS EN 13286-7:2004, “Unbound and Hydraulically Bound Mixtures—Part 7: Cyclic load triaxial test for unbound mixtures”, cylinder samples of 15 cm in diameter and 30 cm high were used. The samples were prepared into seven layers compacted by a vibrating hammer, conforming to BS EN 13286-4:2004, which is able to apply a downward force of 300 to 400 N on the sample surface. The samples were tested in accordance with BS EN 132867:2004 by applying 29 different sequences of dynamic load and confining pressure (100 repetitions per sequence) after a 10,000 repetition (or less if the permanent deformation tends to stop increasing) of a specified deviator stress and confining pressure at conditioning stage.

Stancombe Type 1

Spec Min

Spec Max

100

Passing (%)

80

60

40

20

0

63

31.5

16

8

4

2

1

0.5

0.063

Size (mm)

Figure 2. Grading diagram of the common Type 1 aggregate in the UK and the limitations of the UK Design Manual for Roads and Bridges/Pavement Design.

228

Table 1.

Stress levels for the resilient behaviour test (BS 13286-7:2004). Deviotor stress σd (kPa)

Stage

Confining stress σ3 (kPa) constant

min

max

Conditioning 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

70 20 20 20 20 35 35 35 35 35 50 50 50 50 50 70 70 70 70 70 100 100 100 100 100 150 150 150 150 150

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

200 20 35 50 70 35 50 70 90 120 50 70 90 120 160 70 90 120 160 200 90 120 150 200 240 120 160 200 240 300

All samples will be subjected to conditioning pre-tests according to the above BS before completing the repeat load triaxial test. Conditioning eliminates the effect of specimen disturbance from sampling, compaction, and specimen preparation procedures and minimizes the imperfect contacts between platens and the specimen. Table 1 shows the amounts of stresses applied in accordance with BS 13286-7:2004. Typical results from triaxial machine for granular material cover the resilient behaviour of the mixes under different deviator stresses of 20 to 300 kPa and various confining pressure of 20 to 150 kPa as it is well known that the resilient modulus of unbound aggregate is a function of deviatoric and confining stress. A software programme designed for this purpose and installed on the machine controls the loads and cycles, records the stresses and strains, and calculates the resilient modulus automatically. The samples have being tested at an age of one month when the material should have had enough time for developing some paste hydrated products, which may yield some bonding between the different elements of the sample. 4

MATERIALS

Limestones are sedimentary rocks composed mainly of calcium carbonate (CaCO3). With an increase in magnesium carbonate (MgCO3) content, they grade into dolomite (CaMg(CO3)2). Most limestones and dolomites are hard, durable, and useful for use in the construction 229

industry as aggregate. They are common rock types and consequently widely extracted for aggregate materials. In Great Britain, limestone (including dolomite) provides 54% of the crushed rock aggregate produced. Limestones of Carboniferous age are the major source of limestone aggregate and it represents one of the largest resources of good-quality aggregate in Britain. These limestones are commonly thickly bedded and consistent, which enable them to be quarried extensively and economically. They typically produce strong and durable aggregates, with low water absorption, suitable for roadstone (road aggregate layers) and concreting. There are different types of limestone but most of them are used for construction purposes rather than industrial one (British Geology Survey 2007). In surface mineral workings, dust is potentially generated from a range of activities like site preparation, stockpiling, loading, transportation and mineral processing operations. Fines may accumulate if the material is of poor quality, particularly if it has high filler content or is highly absorptive. Some chemical and physical tests were done on the Stancombe limestone dust prior to study. Physical tests and petrographic details pointed out fine and slightly muddy nature of Stancombe rock dust in irregular, angular shape. Also, 45% void in its bulk structure has been measured. Chemical tests demonstrated that Stancombe limestone dust is a 100% limestone dust with equivalent calcium carbonate amount of 98.55%. It is a weak alkaline material (pH value of 8.6) and carries trace amounts of water-soluble chlorides, acidsoluble sulphate, and sulphur content (less than 0.01%). Using this dust in road structures and eliminating it from ground surface may contribute in carbon dioxide emission as 43.51% of CO2 content has been reported for this type of dust. Chemical analysis presents that Stancombe limestone dust contains 49.6% free lime (CaO) next to trace elements of MgO (1.2%), Al2O3 (1.7%) and SiO2 (5.7%), implying that Stancombe limestone dust is a potential material for bounding purposes although a slow binding rate is expected. 5

RESULTS AND DISCUSSION

16 types of mixes containing different amounts of dust and water have been tested and three samples for each mix have been manufactured and tested for repeatability purposes. Diagrams of resilient modulus versus stress paths have been developed and all presented a normal increase of resilient modulus when the stress amounts increased. In order to make the results comparable, they should be demonstrated at a specified stress. The results from a triaxial test contain a set of resilient modulus calculated at different stress sequences for a sample. Because only one value representative of the sample behaviour is required for comparison and model development purposes, the stress path that can stand for the actual pressure when an element is under traffic load should be picked out. Furthermore, pavement design methods use a single value of the resilient modulus of each layer in the thickness selection process of the unbound layers. Therefore, to select design resilient modulus, the representative stress state acting upon each layer must be either known or assumed. The result from a recent research (NCHRP 1-28A 2003) recommends using a deviator stress ( d) of 103 kPa and a confining pressure (σc) of 34 kPa for calculating the design resilient modulus of subbase or base course out of triaxial test results. Bulk stress (θ) is a combination and sum of three principal stresses, σ1, σ2 and σ3: θ = σ1 + σ2 + σ3

(1)

where σ1 is the major principal stress, and σ2 and σ3 are the minor principal stresses. Because, in triaxial test process, the confining pressure is provided by in-cell air pressure then σ2 = σ3 = σc, and as σd = σ1 – σ3, the bulk stress of 205 kPa will be the representative bulk stress for calculating resilient modulus according to the equation below: θ = σd + 3σc

(2)

Figure 3 is a column diagram of resilient modulus versus mix dust content where the applied bulk stress is 205 kPa. The values of resilient modulus corresponding bulk stress of 230

Stancombe Type 1 + different dust amounts @ different moisture contents for bulk stress (θ) of 205 kPa 800 The percentage on each column is the mix moisture content.

3%

Resilient Modulus (MPa)

600

3% 2%

2.5%

4.5% 4%

2.5%

3.5%

2%

6%

400

3.5%

5.5%

6.5%

OMC-2% OMC-1% OMC OMC+2%

5%

200

0 0%

1 0%

20 %

30%

Dust Amount (%)

Figure 3. Resilient moduli of Stancombe Type 1 containing different amount of dust and moisture at the bulk stress of 205 kPa.

205 kPa have directly been extracted out of the data file developed by the triaxial machine. Figure 3 is to show the behaviour of Stancombe Type 1 material with different dust and moisture contents at a specified bulk stress. As the dust amount varies, so does the OMC. To make judgment easier, moisture content (MC) of each sample has been mentioned on the relevant column. Looking to Figure 3, two results of 0% and 10% dust content band are missing since they collapsed during triaxial test as they were too loose and dry to withstand triaxial test stress sequences. This implies that the compaction of the material has not been perfect as a direct result of low water content. The rest of the mixes were tested successfully as they could resist triaxial test stress paths. The first group of columns, representing a mix of Stancombe Type 1 without extra dust, has its tallest column when the moisture content is at OMC. It reflects this point that determining optimum moisture content according to the philosophy of the highest dry density, mentioned in BS 1377, can lead to the best resilient behaviour of Type 1 material at which there is enough water just to help the compaction for adequate interlocking among the aggregates and prevent excess sliding of the particles on each other under the action of traffic load. Looking to the column groups of samples containing additional 10% and 20% dust, the first shining point is the change in the tallest column of each group. Resilient modulus values for the samples at OMC – 1% are higher than those at OMC. Since this trend is seen for both groups, it can be concluded that when the dust amount is increased for up to 20%, the highest resilient modulus occurs when the MC is 1% less than the optimum moisture content of the material, measured according to BS 1377. In other words, when dust amount is high, water content needs to be decreased to allow the fines, instead of water, fill in the voids and increase the material resilient modulus. Of course, this idea is considered as a hypothesis as it needs to be checked for consistency with the philosophy of the highest dry density method used for OMC calculation, where it is assumed that the highest dry density, corresponding to the optimum moisture content, happens when the voids have been filled in at their best. So, it may make more sense if this phenomenon is interpreted as a better resilient behaviour is 231

experienced at OMC – 1% when there is extra 10% to 20% dust in mix structure although the highest dry density is gained at the mix OMC. The group of 30% dust amount presents an ambiguous trend which makes it difficult to explain. Although the samples at OMC have responded with the highest resilient modulus, it is not easy to sentence that the samples with 30% extra dust would show the best performance when they have been manufactured at their OMC because nearly similar resilient modulus has been recorded for the mix of this category at OMC – 2%. On the other hand, low resilient moduli of the samples at OMC – 1% do not help to carry on with the idea developed for the samples containing 10% and 20% dust. In addition, sampling material with 30% dust was not as perfect as it should have been since fine material used to escape from beneath the compaction plate at the end of each compaction path, making it very difficult to manufacture uniform samples. Hence, developing an explanation that can cover the uncertain trend of resilient modulus for the samples containing 30% extra dust needs a deeper investigation. Taking into account the effect of moisture variation on the behaviour of the samples indicates that changing moisture content beyond OMC drops the resilient modulus of Type 1 limestone material dramatically—where there is 28% under 4 mm dust in the mix texture. Unlike the samples with no extra dust, this rule is less applicable when extra dust exists in sample mixture. Varying moisture content beyond OMC does not steer to a significant reduction of sample resilient modulus when extra dust has occupied 10% to 20% of the whole sample mass, meaning that the high-dust-volume containing mixes are less sensitive to the changes in moisture in terms of resilient behaviour. Therefore, it looks like that adding extra dust to the Type 1 material causes the mix not to be very much sensitive to the moisture content. Comparing the resilient modulus of the control material, i.e. Stancombe Type 1 at OMC (3% MC), with other mixes containing extra dust amount helps to confirm the conclusions made by previous researches pointing out the negative effect of excess fine material on resilient modulus and bearing capacity of the samples. Reduction of at least one-third in resilient modulus values for the mixes containing extra dust is considered as a significant decrease and is a clear, direct result of added fine particles. Even if a case of binding—because of high free-lime content of Stancombe limestone dust—has happened, the samples have not gained enough strength to be comparable with control mix on resilient modulus. Further researches are on track to investigate if any binding takes place when extra Stancombe limestone dust is used. With such a range of resilient modulus for the samples containing 10%, 20% and 30% dust content, it can be drawn that the resilient moduli are roughly around 400 MPa. The reasons behind this kind of behaviour are originated either in the probable binding or in the physical structure of the samples. If the binding is the case, then slight binding and consequently a unique structure of coarse and fine aggregate may have been developed. It can also be stated that extra dust amount has widely separated coarse aggregate so that the resilient respond of the samples under testing loads are mostly based on the contribution of the fine aggregate and the mortar within the mix. 5.1 Resilient modulus prediction model Modeling is an important requirement in dealing with material performance. As the industry is willing to be able to predict the behaviour of the mixes for further research and applications, a model which can predict the resilient modulus of the materials with enough accuracy, and is easy and understandable for the industry is desired. Lepark et al. (2000) have collected some kinds of resilient modulus models developed since 1963 in their state of the art, and have introduced the K-θ model as a simple and extremely useful model for analysis of stress dependency of material resilient respond although some modifications can be found in the literature. The mathematical approach of this model has been based on a stress-dependent resilient modulus (to fulfil stress-strain relationship) and a constant Poisson’s ratio. Therefore, the K-θ model was selected as a base model to develop the stiffness-stress relationship of the mixes of this study and will be checked to find out if it fits research particular data. K-θ model has been suggested as a simple hyperbolic relationship between the resilient modulus and the related bulk stress: 232

M r = k1θ k2

(3)

where Mr is the resilient modulus of the material; θ is the amount of bulk stress, sum of principal stresses; and k1 and k2 are the parameters obtained by fitting the test results to the model as a results of test repetition. Power models have been raised using MS-Excel software for each group of mixes. As a sample, the models and their mathematical demonstrations for the mixes containing 10%

Stancombe Type 1 + 10% dust @ different moisture contents 1200

2.5% MC 3.5% MC (opt) 5.5% MC Power (2.5% MC) Power (3.5% MC (opt)) Power (5.5% MC)

Resilient Modulus (MPa)

1000

800

mix MC

600

Model 0.55

2.5%

Mr = 25.41θ 2 R = 0.999

3.5%

Mr = 36.86θ R2 = 0.988

5.5%

Mr = 37.81θ 2 R = 0.993

0.47

400

0.43

200

0 0

100

200

300

400

500

600

700

800

Bulk Stress (kPa)

Figure 4. Scatter plot of resilient modulus versus bulk stress for Stancombe Type 1 + 10% dust at different moisture contents and their behaviour models.

Table 2. K-θ models developed for the mixes. Mix description*

K-θ model

R2 value

STAN T1 @ 2% MC STAN T1 @ 3% MC STAN T1 @ 5% MC STAN T1 + 10% dust @ 2.5% MC STAN T1 + 10% dust @ 3.5% MC STAN T1 + 10% dust @ 5.5% MC STAN T1 + 20% dust @ 2% MC STAN T1 + 20% dust @ 3% MC STAN T1 + 20% dust @ 4% MC STAN T1 + 20% dust @ 6% MC STAN T1 + 30% dust @ 2.5% MC STAN T1 + 30% dust @ 3.5% MC STAN T1 + 30% dust @ 4.5% MC STAN T1 + 30% dust @ 6.5% MC

Mr = 25.25θ0.53 Mr = 67.74θ0.45 Mr = 22.29θ0.48 Mr = 25.41θ0.55 Mr = 36.86θ0.47 Mr = 37.81θ0.43 Mr = 35.41θ0.49 Mr = 44.77θ0.46 Mr = 78.88θ0.33 Mr = 30.18θ0.50 Mr = 47.91θ0.43 Mr = 41.13θ0.43 Mr = 84.85θ0.34 Mr = 42.06θ0.43

0.996 0.994 0.979 0.999 0.988 0.993 0.997 0.999 0.994 0.971 0.996 0.990 0.983 0.981

*

STAN T1 stands for ‘Stancombe Type 1’ and MC stands for ‘Moisture Content’.

233

dust amount have been shown in Figure 4. Also, the K-θ model for each mix has been developed and inserted into Table 2. The R2 values of the models are reflecting outstanding correlations between the resilient modulus of the materials and the sum of principal stresses to which the samples were subjected. This good agreement can also point out the sufficient accuracy paid in both sample manufacturing process and testing the samples, indicating that the developed models are effective in predicting resilient modulus of the granular materials of this series according to the laboratory (triaxial test results), and industry can conclusively use them for construction or further research purposes. Besides, it is concluded that the K-θ model is a good base model for developing resilient modulus prediction models according to the subjected laboratorial deviator and confining stresses. That the resilient modulus is a stress dependent characteristic of the granular materials is a conclusion, which can be easily made considering high R2 values, and verifies the K-θ model assumption of stress dependency of resilient modulus. After analysis on the results, the authors believe that further research is necessary to address the impacts of adding more dust to road base material in flexible pavement performance and design. 6

CONCLUSIONS

In order to clarify the effect of extra Stancombe limestone dust usage on the resilient performance of Stancombe Type 1 material—a common base and subbase material in the UK— samples containing different dust and water amounts have been manufactured and tested. Results indicate that a significant resilient modulus drop (at least 30%) can be expected when extra dust amount has been applied, confirming previous conclusions regarding negative effects of fine material on the strength and resilient respond of the mixes. Also, any moisture content other than optimum moisture content for pure Stancombe Type 1 material ends in less resilient modulus; however, the mixes with extra dust amount are less sensitive to the moisture content variation in comparison with the samples of Type 1 material. The highest resilient modulus for the samples containing 10% and 20% dust was gained when the samples had 1% less water than the optimum moisture amount of those samples, meaning that a more desirable resilient behaviour has been experienced when the moisture content of the samples were 1% less than the optimum amount which represents highest dry density of the mixture. While the resilient respond of the samples containing 10% and 20% extra dust looked to be rational, ambiguous trend has been recorded for the samples of those containing 30% Stancombe limestone dust. Although obvious similarity in the resilient moduli of dust-elevated samples is seen and it is predicted that a slight binding may have taken place in these samples, no clear statement can be issued before further research work can be executed. High R2 values of the models developed on the general K-θ model, according to the triaxial test results help to take this conclusion that the resilient modulus is a stress dependence characteristic of the dust-elevated Stancombe Type 1 material and is predictable using the K-θ model. Also, it shows that laboratory resilient modulus can be predicted upon the correspondent bulk stresses. ACKNOWLEDGMENT Great contribution of Tarmac Group Ltd. in providing required material and sample manufacturing facilities is highly appreciated. REFERENCES Babic, B., Prager, A. & Rukavina, T. 2000. Effect of fine particles on some characteristics of granular base courses. Journal of Materials and Structures 33(231): 419–424. Bosilikov, V.B. 2003. SCC mixes with pooely graded aggregate and high volume of limestone filler. Journal of Cement and Concrete Research 33(9): 1279–1286.

234

British Geological Survey 2007. Construction aggregate. Mineral Planning Section Factsheet, Office of the Deputy Prime Minister: Available from: http://www.bgs.ac.uk/ [Accessed 20 December 2007] BS 13286-7. 2004. Unbound and Hydraulically Bound Mixtures—Part 7: Cyclic load triaxial test for unbound mixtures. UK: British Standard Publications. BS 1377-4. 1990. Methods of test for soils for civil engineering purposes. Compaction-related tests. UK: British Standard Publications. Croney, D. 1977. The Design and Performance of Road Pavements. UK: Crown. Dawson, A.R. & Cheung, L.W. 2002. The effect of particle and mix characteristics on the performance of some granular material. Transportation Research Record 1787: 90–98. Felekoglu, B. 2007. Utilisation of high volumes of limestone quarry wastes in concrete industry (Selfcompacting concrete case). Journal of Resources, Conservation & Recycling 51: 770–791. Felekoglu, B. & Baradan, B. 2003. Utilisation of limestone in self-levelling binders. Proceeding of International Symposium of Recycling and Reuse of Waste Materials: 475–484. Galetakis, M. & Raka, S. 2004. Utilization of limestone dust for artificial stone production: An experimental approach. Journal of Mineral Engineering 17: 355–357. Huang, Y.H. (2nd ed.) 2004. Pavement Analysis and Design. Upper Saddle River: PEARSON Prentice Hall. Jorney, B.N. & Hicks, R.G. 1986. Base course contamination limits. Transportation Research Record 1095: 86–101. Cited in: Lekarp et al. 2000. Lekarp, F., Isacsson, U. & Dawon, A. 2000. State of the art. I. Resilient response of unbound aggregates. Journal of Transportation Engineering 126(1): 66–75. Manning, D. 2004. Exploitation and use of quarry fines (Final report). UK: Mineral Solution Ltd. NCHRP 1-28A 2003. Harmonized test methods for laboratory determination of resilient modulus for flexible pavement design. USA: Transportation Research Board. Terzi, S. & Karashin, M. 2007. Evaluation of marble waste dust in the mixture of asphaltic concrete. Journal of Construction and Building Materials 21(3): 616–620. Thom, N.H. & Brown, S.F. 1987. Effect of moisture on the structural performance of a crushed-limestone road base. Transportation Research Record 1121: 50–56. Turgut, P. 2007. Cement composites with limestone dust and different grades of wood sawdust. Journal of Building and Environment 42: 3801–3807. Turgut, P. & Algin, H.M. 2006. Limestone dust and wood sawdust as brick material. Journal of Building and Environment 42: 3399–3403. Uthus, L. 2007. Deformation Properties of Unbound Granular Aggregate. (PhD Thesis) Trondheim: Norwegian University of Science and Technology. Yoshida, N., Sugisako, Y., Nakamura, H. & Hirotsu, E. 2003. Resilient Modulus of Hydraulic Mechanically Stabilized Slag Base-course Material. Proceeding of the 3rd International Symposium on Deformation Characteristics of Geomaterials. France.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Characterizing aggregate permanent deformation behavior based on types and amounts of fines D. Mishra, E. Tutumluer & J. Kern University of Illinois, Urbana, Illinois, USA

A. Butt Engineering and Research International Inc., Savoy, Illinois, USA

ABSTRACT: Construction of a working platform is often needed on soft, unstable soils to provide sufficient stability and adequate support for equipment mobility during paving operations without developing excessive rutting or sinkage of the equipment. One method of verifying the adequacy of such a layer is through conducting permanent deformation tests in the laboratory. This paper presents permanent deformation test results from an ongoing research project at the University of Illinois aimed at characterizing strength, stiffness, and deformation behavior of three different aggregate types commonly used in Illinois for subgrade replacement and subbase. Aggregate gradations were carefully engineered in the laboratory to study the effects of increasing amounts of both plastic and non-plastic type fines on permanent deformation behavior. Aggregate type or angularity, plasticity of fines and moisture conditions in relation to optimum water content were found to significantly affect the permanent deformation behavior. 1

INTRODUCTION

Subgrade replacement and capping is one of the most common methods for building pavements on soft, unstable soils. The purpose is to make the subgrade strong enough so that it can take the loads from heavy equipment used during pavement construction. An unstable subgrade may result in sinkage of the construction equipment and will hamper equipment mobility (Tutumluer et al., 2005). The Illinois Department of Transportation (IDOT) currently uses subgrade replacement and aggregate cover as a means of providing construction platforms on top of weak subgrade soils. The thickness of such an aggregate layer is determined as a function of the unsoaked California Bearing Ratio (CBR) value of the subgrade soil from a chart in the current IDOT Subgrade Stability Manual (IDOT SSM 2005). The aggregate cover chart provided does not, however, distinguish between different aggregate types and properties used for this purpose. Previous research in this area shows that the load carrying capacity of an aggregate layer is significantly affected by the percentage of fines in the base. For a dense-graded crushed aggregate base material having a 25-mm (1-in.) top size, maximum strength is achieved at a fines content of about 8% (Gray, 1962). As the maximum aggregate size increases, the optimum amount of fines that gives the maximum strength typically decreases (Barksdale & Itani, 1989). An ongoing laboratory research study at the University of Illinois has focused on investigating effects of different aggregate types and properties and construction conditions on the aggregate cover thickness requirements. Three different aggregate types, i.e. crushed limestone and dolomite and uncrushed gravel commonly used in the state of Illinois for subgrade replacement and aggregate cover, are studied to compare the effects of different laboratory test matrix variables on aggregate strength, modulus and deformation behavior. The test matrix variables considered are aggregate shape and angularity (crushed and uncrushed), 237

amount of fines, types of fines (plastic, with a plasticity index or PI of 10, and non-plastic) and moisture state in relation to the optimum moisture content. Engineered aggregate gradations in the laboratory ensure that all aggregate test samples have consistent grain size distributions, and therefore, the only difference in aggregate behavior could be attributed to the effect of one variable studied at a time. The effects of types and amounts of fines on the moisture-density relationships and unsoaked CBR values of the three aggregate types have already been reported elsewhere (Mishra et al. 2008). This paper presents results from the permanent deformation tests conducted on the aggregate samples during the course of this research study. The test procedure adopted to consistently prepare samples with engineered gradations is described first. Then, the permanent deformation test results are presented to highlight different trends in the observed behavior such as the individual effects of test matrix variables on the permanent deformation behavior. 2

ENGINEERED GRADATIONS AND PROPERTIES

One of the primary variables in any laboratory test study of aggregate materials is the grain size distribution. Differences in aggregate gradations can lead to significantly different behavior for the same aggregate type. Therefore, before conducting any parametric study on the aggregate properties affecting behavior, it was deemed important to keep the gradations consistent. This would enable the researchers to attribute the change in behavior to the induced changes in the variable parameters, e.g. fines percentage and plasticity of fines. Figure 1 shows the different engineered gradations used to prepare samples for the laboratory test matrix. Accordingly, aggregate test specimens were prepared for 5 different target fines contents, i.e., 0%, 4%, 8%, 12%, and 16% fine material passing the No. 200 sieve or 0.075 mm, and tested in all the moisture-density, unsoaked CBR, rapid shear strength, resilient modulus and permanent deformation tests conducted following the experimental program. It should be noted that the blending of aggregates for sample preparation was done based on dry sieving results. However, wet sieving was conducted to check any differences between the results obtained from dry and wet sieving. It was noticed that gravel samples blended with different fine amounts to achieve target percentages passing the No. 200 sieve size or 0.075 mm actually contained higher percentages of fines based on wet sieving, e.g., 4% target from dry sieving resulted in 6.8% actual fines based on wet sieving. This could be attributed to the fines that were sticking to the surfaces of larger particles during dry sieving and affecting aggregate layer performances. Therefore, actual fines contents were always calculated based on wet sieving and adequately accounted for when studying effects of fines on the aggregate strength, 100 80 70 60 50 40 30 20

Cumulative % Passing

90 Engineered_0% Engineered_4% Engineered_8% Engineered_12%

10 10 Figure 1.

1 Particle Size (mm)

0.1

0 0.01

Engineered gradations of the aggregate specimens prepared and tested in the laboratory.

238

Table 1.

Standard Proctor moisture-density properties of dolomite & uncrushed gravel materials. Optimum moisture content, wopt (%)

Maximum dry density, γdmax kN/m3 (pcf)

Material

Fines (%)

4

8

12

16

4

8

12

16

Dolomite

Non-plastic fines Plastic fines

10.6

8.5

6.8

6.6

10.4

7.4

6.6

6.6

Non-plastic fines Plastic fines

9.2

8.1

7.1

7.1

8.0

7.3

7.1

6.9

20.80 (132.4) 21.18 (134.8) 20.75 (132.1) 21.10 (134.3)

21.71 (138.2) 21.68 (138.0) 21.08 (134.2) 21.29 (135.5)

22.18 (141.2) 22.00 (140.1) 21.58 (137.4) 21.54 (137.1)

22.45 (142.9) 22.15 (141.0) 21.68 (138.0) 21.44 (136.5)

Gravel

modulus and deformation behavior. Table 1 lists the compaction properties of uncrushed gravel and dolomite with different amounts of plastic and non-plastic fines. 3

LABORATORY PERMANENT DEFORMATION TESTS

Repeated load triaxial testing is one of the most commonly used and widely accepted laboratory test methods for determining modulus and deformation characteristics of granular materials and subgrade soils due to traffic loading. Both resilient modulus and permanent deformation accumulation can be quantified based on the appropriate repeated load testing data. In a well designed pavement system and after the shakedown of pavement materials takes place during construction and initial trafficking, most of the permanent deformation accumulated per load cycle is often quite small compared to the total deformation. The permanent deformation data are often obtained in the laboratory from the first 500 to 1,000 load cycles of the resilient modulus tests and considered indicative of the long term permanent deformation behavior. Resilient modulus and permanent deformation tests were conducted in this study following the AASHTO T307 test procedure utilizing the University of IllinoisFastCell (UI-FastCell), an innovative testing device developed at the University of Illinois. Detailed explanations of the capabilities of the UI-FastCell device can be found elsewhere (Tutumluer and Seyhan, 1999; Seyhan and Tutumluer, 2002). 3.1 Sample preparation For each engineered gradation, samples were prepared at three moisture contents: (i) optimum moisture content (wopt) corresponding to maximum dry density, (ii) 90% of wopt, to simulate dry conditions in the field, and (iii) 110% of optimum moisture content to simulate near saturation field conditions. Compaction characteristics for the three aggregate types were established using the method specified in ASTM D698 as described elsewhere by Mishra et al. (2008). The achieved dry densities at optimum moisture contents matched closely with the maximum Proctor densities. The achieved water contents were in general very close to the optimum values except for very wet conditions, where the excess water drained out of the sample. Cylindrical specimens, 150 mm in diameter by 150 mm high were prepared to fit in the confinement chamber of the UI-FastCell for the permanent deformation testing. The split mold was assembled and a nitrile membrane 0.6-mm thick was folded over the top of the mold and secured with an o-ring. A vacuum line was attached to the mold to hold the membrane tight against the mold. The aggregate mixed with the required amount of water was placed in the mold in three lifts with each lift compacted using a drop hammer to a precalculated thickness, based on the target density. Each lift was then scarified up to a depth of approximately 12-mm, and the next lift then placed, and compacted. After compaction, the vacuum was removed from the split mold and applied to the bottom of the platen to create 239

suction through the specimen thereby causing a confinement by the membrane. The loading platen was placed at the top of specimen. The split mold was then removed and a 0.3-mm thick nitrile membrane was placed on the specimen and secured to the top and bottom platens with o-rings. The second membrane was required because the first membrane generally was punctured while compacting the specimen. Next, the specimen was placed on the base plate, centered by the pivot screw on the base plate, and fitted the hole at the bottom platen of specimen. A 2-kPa (0.3 psi) hydrostatic seating pressure was applied, and the vacuum was removed. The drainage port was left open to perform the test under drained condition. 4

ANALYSIS OF TEST RESULTS

The permanent deformation tests were conducted by subjecting the triaxial cylindrical samples to 1,000 cycles of haversine type dynamic pulse loading applied at 0.1-second with a 0.9second rest period at a confining stress level of 103 kPa (15 psi) and an axial deviator stress of 103 kPa (15 psi). The permanent deformation values were recorded for each load cycle. 4.1 Effect of percent fines on permanent deformation Figure 2 shows the effect of increasing the amount of non-plastic fines on the permanent deformation behavior of dolomite tested at dry of optimum moisture contents. Similar trends were in general observed for the limestone samples, which will not be presented here for brevity. It should be noted that the permanent deformation curve for 8% fines is lower than that for 4%. However, as the fines content increases from 8% to 12% and then subsequently to 16%, the permanent deformation values increase significantly. The exact same trend can be observed for non-plastic dolomite fines tested at optimum water content (see Figure 3). This behavior at relatively low fines contents can be explained by the unstable aggregate matrix due to the presence of high void space in the crushed dolomite sample. As the amount of fines is increased, the voids are gradually filled up to provide better rearrangement and packing of particles. However, as the fines content is increased beyond 8%, the behavior of the matrix starts to be governed by the fines, and therefore, the permanent deformation value at 12% fines becomes higher than that at 8% 0.7

Permanent Deformation (mm)

0.6 0.5 0.4 0.3 0.2

4% Fines 8% Fines 12% Fines 16% Fines

0.1 0 0

100 200 300 400 500 600 700 800 900 1000 Number of Cycles

Figure 2.

Percent non-plastic fines affecting permanent deformation of Dolomite at 90% of wopt.

240

1.6

Permanent Deformation (mm)

1.4 1.2

4% Fines 8% Fines 12% Fines 16% Fines

1 0.8 0.6 0.4 0.2 0 0

100 200 300 400 500 600 700 800 900 1000 Number of Cycles

Figure 3.

Percent non-plastic fines affecting permanent deformation of Dolomite at wopt.

fines. Moreover, the permanent deformation at 16% fines is drastically higher and may lead to catastrophic failure of the aggregate layer. This observation is in agreement with the recommendation made by Tutumluer and Seyhan (2000) that an acceptable limit for non-plastic fines should be set around 8% for crushed aggregate layers. Figure 4 shows the permanent deformation trend of dolomite, this time with plastic fines (plasticity index or PI of 10%) and when measured on the wet side of optimum moisture content. The typical trend of permanent deformations accumulating at much higher rates with increasing fines contents actually changes when the samples are tested on the wet side of optimum moisture content, as compared to the dry side, or at optimum conditions. For the dry and optimum conditions, the aggregate matrix develops much lower permanent deformations at 8% fines when compared to the samples tested at 4% fines. This can be attributed to the fact that at 4% fines, the amount of voids in the aggregate structure was too high, and therefore, the particles had to move and rearrange to achieve a more stable configuration. However, Figure 4 shows that 8% fines gave higher permanent deformation values as compared to 4% fines. The samples at 12% and 16% fines were extremely unstable and the deformation values were too high for the LVDTs in the triaxial test device to measure these deformations immediately after load application. That is why the permanent deformation values for samples tested at 12% and 16% fines are not given in Figure 4. When plastic fines got wet, they resulted in an immediate deteriorating effect on the aggregate performance, irrespective of the void structure of the aggregate matrix. This implies that different limits need to be established for maximum amounts plastic and non-plastic fines, which should be allowed in the field for constructing aggregate cover layers. This is particularly important when the pavement is likely to be exposed to high amounts of moisture. In case of plastic fines, the allowable fines content should be kept at the lowest possible value. Further, an increase in moisture content combined with existing high percentages of plastic fines may lead to catastrophic failures. Figure 5 presents permanent deformation test results for the gravel samples with non-plastic fines tested at dry of optimum moisture conditions. From the figure, the permanent deformation values increase consistently when the amount of fines is increased. Unlike in the case of the crushed dolomite, the uncrushed gravel aggregate matrix does not show lower permanent 241

Permanent Deformation (mm)

0.4 0.35 0.3 0.25 0.2 0.15 0.1

4% Fines

0.05

8% Fines

0 0

100 200 300 400 500 600 700 800 900 1000 Number of Cycles

Figure 4.

Percent plastic fines affecting permanent deformation of Dolomite at 110% of wopt.

Permanent Deformation (mm)

0.6

0.5

0.4

0.3

0.2

4% Fines 8% Fines 12% Fines 16% Fines

0.1

0 0

100 200 300 400 500 600 700 800 900 1000 Number of Cycles

Figure 5.

Percent non-plastic fines affecting permanent deformation of gravel at 90% of wopt.

deformation values at 8% fines when compared to the case at 4% fines. The exact same trend was observed for gravel with plastic fines; however, not all plots are shown in this paper. Figure 6 presents a comparison of the permanent deformation trends of the tested samples of gravel and dolomite. Both dolomite and gravel permanent deformation curves are plotted for samples with 4% and 8% non-plastic fines tested at dry of optimum moisture contents. Note that at 4% fines content the dolomite sample accumulates much higher permanent deformations as compared to the gravel sample. The interpretation of results shown 242

Permanent Deoformation (mm)

0.4 0.35 0.3 0.25 0.2 0.15 0.1 0.05

Gravel Non-Plastic 4% Fines Dolomite Non-Plastic 4% Fines Dolomite Non-Plastic 8% Fines Gravel Non-Plastic 8% Fines

0 0 100 200 300 400 500 600 700 800 900 1000 Number of Cycles Figure 6.

Comparison of permanent deformation trends of gravel and dolomite at 90% of wopt.

in Figure 6 is that at 4% fines, the crushed dolomite aggregate matrix contains higher void space, and therefore, the aggregate particles rearrange themselves to achieve a more stable configuration. As the amount of fines increases to 8%, permanent deformation values for the gravel become higher than those for the dolomite. This implies that when the amount of fines is somewhat low, crushed aggregates may show higher permanent deformation values than uncrushed aggregates due to lower packing orders. Standard compaction efforts are often unable to bring the crushed aggregate matrix to the densest configuration at low fines contents. Some rearrangement may take place under the application of construction traffic and as such, aggregate layers containing crushed particles should be better shaken down under construction equipment and traffic. 4.2 Effects of aggregate angularity and plasticity of fines In an effort to better understand the suitability of different aggregate types for aggregate cover application, it is important to evaluate the relative impacts of the different test matrix variables on the permanent deformation behavior of the aggregate types studied. For this purpose, Figure 7 compares the relative impact levels of aggregate angularity and plasticity of fines on the permanent deformation behavior. The dolomite sample with 8% non-plastic fines tested at dry of optimum conditions is considered here as the reference curve. To compare the effect of aggregate type or angularity on permanent deformation behavior, the test results for the gravel have also been plotted under the same conditions. Note that the gravel shows higher permanent deformation accumulations as compared to the dolomite indicating that particle angularity is an important factor governing aggregate behavior. On the other hand, for the dolomite sample also tested with plastic fines under the exact same conditions, the test results clearly show that plastic fines resulted in the highest permanent deformations. This implies that if plastic fines are present, aggregate angularity or type affecting permanent deformation behavior may shift to become a secondary consideration. Figure 8 shows a similar comparison for aggregate samples with 12% actual fines tested on the wet side of optimum water content. A drastic reduction in aggregate performance can be clearly seen when excess moisture is introduced in the sample with high-plastic fines. The gravel sample with 12% non-plastic fines tested at 110% of optimum moisture content has been used here as the reference curve. As the aggregate type is changed to crushed dolomite (all the other parameters remaining the same), there is no significant change in the 243

0.4

Permanent Deformation (mm)

0.35 0.3 0.25 0.2 0.15 0.1 0.05

Dolomite 8% Non-Plastic Fines Gravel 8% Non-Plastic Fines Dolomite 8% Plastic Fines

0 0 100 200 300 400 500 600 700 800 900 1000 Number of Cycles Figure 7.

Relative effects of angularity and plasticity of fines evaluated on dry side of wopt.

Permanent Deformation (mm)

3

2.5

2

1.5

Gravel 12% Non-Plastic Fines Dolomite 12% Non-Plastic Fines Gravel 12% Plastic Fines

1

0.5

0 0 100 200 300 400 500 600 700 800 900 1000 Number of Cycles Figure 8.

Relative effects of angularity and plasticity at high fines contents at 110% of wopt.

permanent deformation behavior. However, as the type of fines is changed from non-plastic to plastic (curve plotted for gravel with 12% actual plastic fines tested at 110% of wopt), there is a significantly higher rate of permanent deformation accumulation. The effects of increasing percent fines on the permanent deformation behavior can be quite different depending on the void structure of the aggregate matrix and whether the aggregate particles are crushed or uncrushed. As for the implications of these experimental findings, the amount of fines may often vary in actual aggregate mixes delivered to construction sites. Accordingly, different limits may need to be set for the maximum amount of fines permitted 244

Permanent Deformation (mm)

0.6 0.5 0.4 0.3 0.2 Dolomite Non-Plastic 90% Wopt

0.1 0

0 100 200 300 400 500 600 700 800 900 1000 Number of Cycles Figure 9.

Relative effects of varying moisture content and plasticity of fines at high fines contents.

in the gradation depending on whether the aggregate material is crushed or uncrushed for the best field performance. When plastic fines are introduced with excessive moisture, the aggregate layer strength may be dramatically reduced. Further, when high amounts of fines (whether non-plastic or plastic) are considered at elevated moisture levels, the angular particles alone can no longer govern the behavior, i.e. both uncrushed and crushed aggregates may behave similarly. Then, the types and amounts of fines and the moisture conditions may primarily dictate the behavior. 4.3 Effects of moisture content and plasticity of fines Figure 9 compares relative impacts of moisture content and plasticity of fines on aggregate permanent deformation behavior. The comparisons are presented for dolomite with 12% fines and the reference curve is for non-plastic fines tested at 90% of optimum water content. As the moisture content is increased to 110% of wopt, the permanent deformation values increase by about 25%. This shows the adverse effect of moisture even on non-plastic fines at relatively high fines contents. However, if the type of fines is changed from non-plastic to plastic (represented by dolomite with 12% plastic fines tested at 90% of wopt) at the same moisture content, the permanent deformation value increases even more dramatically. This clearly shows that increase in moisture content is not as critical for non-plastic fines when compared to the case of plastic fines. These results combined with the previously reported ones in Figure 8 indicate that the control of moisture is much more important for aggregate layers containing plastic fines than for those containing non-plastic fines. Moisture control and drainage provisions should become an essential concern during construction especially when plastic fines are present in the aggregate gradations. 5

SUMMARY OF OBSERVATIONS FROM LABORATORY TESTING

From the permanent deformation tests conducted on crushed dolomite and uncrushed gravel type aggregate samples, it appears that the most important parameter at low fines (passing No. 200 sieve size or smaller than 0.075 mm) contents is the aggregate type governing the angularity, i.e. crushed or uncrushed particles. Unless all voids in aggregate matrix are completely filled with fines, particle angularity, i.e. crushed or uncrushed particles, typically 245

governs the permanent deformation behavior. The second most important parameter that affected aggregate behavior was the plasticity of fines. High amounts of plastic fines, considered here by a plasticity index or PI of 10, at wet of optimum moisture conditions were found to quickly destruct the aggregate load transfer matrix thus resulting in excessive permanent deformations. The effect of moisture content on aggregate performance varied significantly depending on the amount and plasticity of fines. For low percentages of non-plastic fines, moisture content did not have a significant effect on aggregate performance, and often aggregate type or angularity was the most important factor. However, for aggregates with plastic fines, moisture becomes the most important factor that governs aggregate behavior. Moisture when combined with plastic fines created the worst effect. To incorporate the most significant findings from these laboratory test results, a flow chart based approach will need to be adopted for constructing the aggregate cover thickness designs in the field. For example, the criticality of moisture content undergoes a drastic change based on whether the fines are plastic or non-plastic. Similarly, the effect of amount of fines will have to take into account the actual fines content including the fines sticking to larger particles in the case of gravel. When the fines content is low (often below 8%), there is not a significant effect of fines on aggregate deformation behavior except for cases when plastic fines were combined with high moisture. ACKNOWLEDGEMENTS AND DISCLAIMER This paper is based on the partial results of ICT R27-1, “Characterization of Illinois Aggregates for Subgrade Replacement and Subbase” research study. ICT R27-1 project is conducted at the Illinois Center for Transportation (ICT) in cooperation with the Illinois Department of Transportation, Division of Highways, and the U.S. Department of Transportation, Federal Highway Administration. The contents of this paper reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Illinois Department of Transportation or the Federal Highway Administration. This paper does not constitute a standard, specification, or regulation. REFERENCES Barksdale, R.D. & Itani, S.Y. “Influence of aggregate shape on base behavior,” In Transportation Research Record 1227, TRB, National Research Council, Washington D.C., 1989, pp. 173–182. Gray, J.E., 1962, Characteristics of graded base course aggregates determined by triaxial tests, Engineering Research Bulletin No. 12, National Crushed Stone Association. Illinois Department of Transportation—IDOT. “Subgrade Stability Manual,” Bureau of Bridges and Structures, May 1, 2005, 27 pages. Mishra, D., Tutumluer, E., & Butt, A. “Types and amounts of fines affecting aggregate behavior,” Proceedings of the First International Conference on Transportation Geotechnics, Nottingham, UK, 25–27 August, 2008. Seyhan, U. & Tutumluer, E. “Anisotropic modular ratios as unbound aggregate performance indicators,” Journal of Materials in Civil Engineering, ASCE, Volume 14, Number 5, September/October 2002, pp. 409–416. Tutumluer, E. & Seyhan, U. “Laboratory determination of anisotropic aggregate resilient moduli using an innovative test device,” Transportation Research Record 1687, Transportation Research Board, Washington, D.C., 1999. Tutumluer, E. & Seyhan, U. “Effects of fines content on the anisotropic response and characterization of unbound aggregate bases,” In Unbound Aggregates in Road Construction, Edited by A.R. Dawson, A.A. Balkema Publishers, Proceedings of the Unbound Aggregates in Roads (UNBAR5) Symposium, University of Nottingham, England, June 21–23, 2000, pp. 153–160. Tutumluer, E., Thompson, M.R., Garcia, G., & Kwon, J. “Subgrade stability and pavement foundation requirements,” In Proceedings of the 15th Colombian Symposium of Pavement Engineering, sponsored by Pontificia Universidad Javeriana in Bogota, Melgar, Colombia, March 9–12, 2005.

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Asphalt mixtures

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Use of polymer modified binders to reduce rutting in Nordic asphalt pavements B.O. Lerfald SINTEF Building and Infrastructure, Road and Railway Engineering, Trondheim, Norway

J. Aurstad & N.S. Uthus Norwegian Public Roads Administration, Trondheim, Norway

ABSTRACT: Rutting is a major problem in asphalt pavements in Norway. This is partly because of wear from studded winter tires and partly because of deformations from growing traffic with increasing tire pressures and heavy axle loads. This development in traffic together with more severe Nordic climatic influences now calls for innovative pavement solutions. To meet these growing traffic and climatic challenges, pavements need to exhibit improved cracking and deformation resistance (flexibility and stability). Therefore, there is now more focus on polymer modified binders (PMB). A number of Norwegian asphalt pavements with PMB from the last years are now closely monitored to evaluate the long term field performance. For some of these sections, extensive laboratory investigations have been conducted related to both wear resistance (Prall testing) and deformation properties (Dynamic creep test/Nottingham Asphalt Tester and Wheel Track). The paper presents the recent results from these studies, comparing field and laboratory data. The main objective is to learn in what way PMBs can be a practical and economical tool for obtaining longer lasting pavements in Norway. 1

INTRODUCTION

In Norway rutting of asphalt pavements is a major problem. The air temperature can vary between −40 °C in winter to +35 °C in summer. The summer pavement temperature can be at the level of 50−60 °C. At winter time the major part of the vehicles are using studded tires. The rutting in the asphalt pavements is partly due to wear from these studded winter tires and partly deformations from heavy axle loads. To meet these growing traffic and climatic challenges, pavements need to exhibit improved cracking and deformation resistance. The Norwegian Public Roads Administration (NPRA) is focusing on the use of polymer modified binders (PMB) to obtain long lasting pavements with regard to wear and deformation. A number of Norwegian asphalt pavements with PMB from the last years are now closely monitored to evaluate the long term field performance. The program will continue in the years to come, with different test sections and types of mixes. One goal with this investigation is to develop performance-based specifications according to the new European standards. This means that the deformation properties have to be documented using the wheel-track and the wear resistance has to be documented using the Prall apparatus. Basic work on this field was carried out in the Norwegian research project PROKAS, in the period 1998–2004 (Lerfald, B.O., et al. 2004). In 2007 a test section was established at the main road E18 in the southern part of Norway, near the city of Kragerö. Four asphalt mixes, two with PMB and two with unmodified bitumen pen 70/100, will be tried out at this site. This paper deals with the work that has been conducted so far in this project.

249

2

MATERIALS AND TESTING

2.1 Asphalt mixes In the E18 study, four different asphalt mixes have been analyzed. The asphalt mixes are designed for a road with traffic speed limit of 80 km/h and an annual daily traffic (ADT) of 6000 vehicles. The mixes were Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA), both with maximum aggregate size of 11 mm. Both types of mixes were produced with PMB and B 70/100, as shown in Table 1. Both cored samples from field and laboratory produced samples from each mix have been tested. The laboratory samples were produced from asphalt mixes taken from the truck just before laying. 2.2 Binder properties The binders used in the mixes are bitumen pen 70/100 (B 70/100) and SBS modified binder. The binder characteristics are given in Table 2. 2.3 Test methods The specimens were tested in the Prall apparatus with regard to resistance to studded tire wear. The Prall test is described by EN 12697–16, “Bituminous mixtures—Test methods for hot mix asphalt—Part 16: Abrasion by studded tyres”. The Prall value is expressed as: S = (m1 − m2)/ γ

(1)

where: S = Prall value (wear), cm3 m1 = weight of sample before testing, g m2 = weight of sample after testing, g γ = bulk density of sample, g/cm3 The principle of the test method is that a cylindrical specimen, having a diameter of 100 mm and a height of 30 mm, is worn by abrasive action during 15 min by 40 steel spheres. The test temperature is 5 °C. A sketch of the Prall apparatus is shown in Figure 1. The deformation properties were tested using the wheel-track apparatus and the Nottingham Asphalt Tester (NAT). The NAT is relevant for use in production control, and it is therefore of interest to evaluate the correlation between the NAT and the wheel-track.

Table 1.

Information of asphalt mixes at E18 Kragerö.

Asphalt mixture

Type of binder

Binder content, (%)

SMA 11 SMA 11 AC 11 AC 11

B 70/100 PMB B 70/100 PMB

5,80 5,80 5,70 5,70

Table 2.

Binder characteristics.

Type of binder

Penetration, (mm/10)

Softening point, (°C)

B 70/100 PMB

75 83

46 74

250

Figure 1.

Prall apparatus, principal sketch/cross section (EN 12697-16).

The NAT test is described by EN 12697-25, “Bituminous mixtures—Test methods for hot mix asphalt—Part 25: Cyclic compression test, Test method A—Uniaxial cyclic compression test with confinement”. The wheel track is described by EN 12697-22, “Bituminous mixtures—Test methods for hot mix asphalt—Part 25: Wheel tracking”. In this study small size device, procedure B, is used. The specimens are tested in air at 40 °C and 50 °C. The Proportional Rut Depth, PRD is calculated as: PRDAIR = (dN/specimen thickness (mm)) * 100

(2)

where: PRDAIR is the proportional rut depth at N cycles dN is the rut depth after N cycles (N is in this project 10 000) The laboratory produced wheel track samples are produced using roller compactor according to EN 12697-33, “Bituminous mixtures—Test methods for hot mix asphalt—Part 33: Specimen prepared by roller compactor”. The laboratory produced samples tested in NAT and Prall are produced according to method 14.5533 in handbook 014 Laboratory Tests (Norwegian Public Roads Administration Manual, 2005). 3

VOID CONTENTS

The void content is an important factor when evaluating both deformations and wear resistance properties. In Table 3 the mean void content for field samples are given, while the mean void content for the laboratory compacted samples are given in Table 4. 251

Table 3.

Mean void content in field samples (%).

Asphalt mixture

Wheel-track

NAT

Prall

SMA 11 SMA 11 with PMB AC 11 AC 11 with PMB

4.3 2.0 2.6 3.2

3.0 1.7 2.4 3.4

3.3 2.6 3.9 4.3

Table 4.

Mean void content in laboratory samples (%).

Asphalt mixture

Wheel-track

NAT

Prall

SMA 11 SMA 11 with PMB AC 11 AC 11 with PMB

0.5 0.5 2.0 2.2

0.5 0.3 1.4 1.3

0.5 0.5 0.7 1.0

Field samples 40°C 4.00

Rut depth, RDAIR (mm)

3.50 3.00 2.50 2.00 1.50 1.00 0.50

9600

10000

9200

8800

8400

8000

7600

7200

6800

6400

6000

5600

5200

4800

4400

4000

3600

3200

2800

2400

2000

1600

1200

800

0

400

0.00

Load cycles SMA 11

Figure 2.

4

SMA 11 PMB

AC 11 PMB

AC 11

Deformation of field samples at 40 °C in wheel track.

RESULTS AND DISCUSSION

This section presents the main results from the laboratory testing of the asphalt mixes. 4.1 Results from testing of deformation properties in wheel-track The results from testing field samples at 40 °C and 50 °C are shown in Figures 2 and 3, respectively, while Figures 4 and 5 show the results from testing laboratory compacted samples. 252

Field samples 50°C 9.00

Rut depth, RDAIR (mm)

8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 8400

8800

9200

9600

10000

8800

9200

9600

10000

8000

8400

7600

7200

6800

6400

6000

5600

5200

4800

4400

4000

3600

3200

2800

2400

2000

1600

800

1200

0

400

0.00

Load cycles SMA 11

Figure 3.

SMA 11 PMB

AC 11 PMB

AC 11

Deformation of field samples at 50 °C in wheel track.

Laboratory samples 40°C 3.50

Rut depth, RDAIR (mm)

3.00 2.50 2.00 1.50 1.00 0.50

8000

7600

7200

6800

6400

6000

5600

5200

4800

4400

4000

3600

3200

2800

2400

2000

1600

1200

800

0

400

0.00

Load cycles SMA 11

Figure 4.

SMA 11 PMB

AC 11 PMB

AC 11

Deformation of laboratory compacted samples at 40 °C in wheel track.

253

Laboratory samples 50°C 6.00

Rut depth, RDAIR (mm)

5.00 4.00 3.00 2.00 1.00

10000

9600

9200

8800

8400

8000

7600

7200

6800

6400

6000

5600

5200

4800

4400

4000

3600

3200

2800

2400

2000

1600

800

1200

0

400

0.00

Load cycles SMA 11

Figure 5.

SMA 11 PMB

AC 11 PMB

AC 11

Deformation of laboratory compacted samples at 50 °C in wheel track.

Rut depth (mm) and proportional rut depth (%) 20.0 18.0 16.0 14.0 SMA 11

12.0

SMA 11 PMB

10.0

AC 11 PMB

8.0

AC11

6.0 4.0 2.0 0.0 Lab 40°C Lab 50°C

Field 40°C

Field 50°C

Lab 40°C Lab 50°C

RDair (mm)

Figure 6.

Field 40°C

Field 50°C

PRDair (%)

The mean rut depth, RDair, and the proportional rut depth, PRDair.

254

In Figure 6 the mean rut depth, RDair, and the proportional rut depth, PRDair, are shown. The results presented in Figures 2–6 show that the deformation properties are improved when using polymer modified binders. The deformation properties for laboratory compacted samples are better than the deformation properties of the core samples from field. Figure 7 shows a comparison between asphalt mixes with B 70/100 and asphalt mixes containing PMB, expressed as deformation ratio. 4.2 Results from testing of deformation properties in NAT The results from testing deformation properties in NAT are shown in Figures 8 and 9, for laboratory compacted samples and field samples respectively. It is expected that the asphalt mixtures with PMB have better deformation properties than the asphalt mixtures with conventional binder. The results shown in Figure 8 are therefore “normal”, while the results in Figure 9 show only minor effects of the modification. 4.3 Results from testing of wear resistance properties in Prall The results after testing laboratory and field samples with regard to wear resistance are shown in Figure 10. Figure 10 shows that the wear resistance is improved for asphalt mixes containing PMB compared with asphalt mixes containing B 70/100. 4.4 Comparison of results from wheel-track and NAT The results obtained from these wheel-track and NAT-testings have been compared. This is due to the fact that requirements for deformation properties of the asphalt mixtures will be based on the European standards. There wheel-track is the chosen test for declaration, while NAT is a possible test for production control. In Figure 11, the correlation between the two methods is shown for laboratory compacted samples. The correlation for field samples is shown in Figure 12.

Ratio between asphalt mixes with B 70/100 and asphalt mixes with PMB 2.00 1.80

Ratio

1.60 1.40 1.20

1.00 0.80 Lab 40°C

Lab 50°C

Field 40°C Field 50°C

RDair (mm)

Lab 40°C

Lab 50°C

Field 40°C Field 50°C

PRDair (%)

SMA11/SMA 11 PMB

AC 11/AC 11PMB

Figure 7. The ratio between asphalt mixes with B 70/100 compared with asphalt mixes with PMB with regard to deformation properties.

255

Mean values - NAT- Laboratory samples 12000

Deformation, μstrain

10000 8000

6000

4000 2000

0 0

500

1000

1500

2000

2500

3000

3500

Load cycles SMA 11

Figure 8.

SMA 11 PMB

AC 11 PMB

AC 11

Mean values—NAT—Laboratory compacted samples.

Mean values - NAT - Field samples 35000

Deformation, μstrain

30000 25000 20000 15000 10000 5000 0 0

500

1000

1500

2000

2500

3000

Load cycles SMA 11

Figure 9.

SMA11 PMB

Mean values—NAT—Field samples.

256

AC 11 PMB

AC 11

3500

Prall - Comparison field and laboratory samples 40.0 35.0

30.0

Prall value (cm3)

25.0 20.0 15.0

10.0 5.0 0.0 SMA 11

SMA 11 PMB Field samples

Figure 10.

AC11 PMB

AC 11

Laboratory samples

Prall values—comparison of laboratory compacted samples and field samples.

Correlation NAT (Lab.samples) - Wheel-track (Lab.samples 50 °C)

Proportional rut depth in wheel-track, PRDair (%)

16.0 14.0

y = 0.0012x + 0.4045 R2 = 0.9871

12.0 10.0 8.0 6.0 4.0 2.0 0.0 0

2000

4000

6000

8000

10000

12000

Deformation - NAT (μstrain)

Figure 11. Correlation between results from wheel track (lab. compacted samples, 50°C) and NAT results.

257

Correlation NAT (Field samples) - Wheel-track (Field samples 50 °C)

Proportional rut depth in wheel-track, PRDair (%)

19.0 18.0 17.0

y = 0.0007x - 3.1586 R2 = 0.6076

16.0 15.0 14.0 13.0 12.0 11.0 10.0 0

5000

10000

15000

20000

25000

30000

35000

Deformation - NAT (μstrain)

Figure 12. Correlation between results from wheel track (field cored samples, 50 °C) and NAT results.

As can be seen from Figure 11, there is good correlation between NAT and wheel track for laboratory samples, while the correlation for field samples is considerably poorer, as shown in Figure 12. 5

CONCLUSIONS

In this project the deformation properties and wear resistance properties of four asphalt mixes have been measured using wheel track, Nottingham Asphalt Tester (NAT) and Prallapparatus. The findings can be summarized as follows: – The results indicate that use of polymer modified binders improves both the deformation resistance and the wear resistances of asphalt mixes, compared with asphalt mixes containing ordinary bitumen. – The effects of polymer modification seem to vary with temperature level. – Generally, laboratory compacted samples have better deformation and wear resistance compared with cored samples from field. – The results indicate better correlation between laboratory and field samples when tested in wheel track compared with tested in NAT. – The results shows good correlation between wheel track and NAT for laboratory compacted samples. – The results show poor correlation between wheel-track and NAT for core samples from field. The results presented in this paper are based on a limited investigation, and further test sections and types of mixes will be followed up in the years to come. REFERENCE Norwegian Public Roads Administration. 2005. Handbook 014 Laboratory Tesst (in Norwegian). Oslo. Lerfald, B.O., et al. 2004. PROKAS Summary report, SINTEF report no. STF22 A04354 (in Norwegian).

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Contribution of asphalt mix components to permanent deformation resistance P.M. Muraya Norwegian University of Science and Technology, Trondheim, Norway

A.A.A. Molenaar & M.F.C. van de Ven Delft University of Technology, Delft, The Netherlands

ABSTRACT: This paper describes the results of a research study that was conducted to investigate the contributions of the different components in an asphalt mixture to the resistance to permanent deformation. As part of this research, extensive triaxial tests were performed on the stone skeletons of dense, stone mastic and porous asphalt concrete. An extensive characterization of the bituminous mortar was also performed using the dynamic shear rheometer and the direct tension tests. The results showed that aggregate skeletons exhibit a high tendency to dilate implying tensile stresses and strains in the bituminous mortar. The results also showed that plastic deformation is much more important than viscous deformation for the stone skeleton mixtures and that viscous deformation is more important for the dense mixture. The findings of the research were used to analyze the permanent deformation that occurred in accelerated pavement test sections. 1

INTRODUCTION

The main aim of this research was to provide more insight into the contribution of the different components in asphalt mixtures towards resistance to permanent deformation. In order to meet this aim it was necessary to investigate the separate contribution of the different components in asphalt mixtures. The composition of the asphalt mixtures investigated in this study was based on a Marshall mix design that was performed in accordance to the Dutch pavement specifications for porous (PAC 0/16), stone mastic (SMA 0/11) and dense (DAC 0/16) asphalt mixtures (Muraya et al. 2004). shows the composition and the densities of the three asphalt mixtures. The composition of the aggregate skeleton specimens was based on the composition of the designed asphalt mixtures. Prior to the specimen preparation, a mixing procedure was developed and the aggregate skeleton in each of the three asphalt mixtures identified. The aggregate skeleton was identified to consist of the aggregates above 0.5 mm for the PAC, 2 mm for the SMA and 0.063 mm for the DAC. For purposes of discrimination, the mortar was defined as a mixture of bitumen and any of the aggregates below the minimum aggregate skeleton size and the mastic as the mixture of bitumen and the filler. Based on this definition, the bituminous binder in the PAC and SMA consisted of both mortar and mastic while the bituminous binder in the DAC was composed of the mastic only. Because of time limitations, only the DAC bituminous binder which consisted of only the mastic was investigated in this research (Muraya 2007). An extensive testing program was performed to characterize the different components. The aggregate skeletons of the three mixtures were characterized by means of triaxial testing. The triaxial testing involved displacement controlled monotonic constant confinement (DCMCC) failure tests and permanent deformation (PD) tests conducted under cyclic confinement. The tests conducted on the asphalt mixtures involved displacement controlled

259

monotonic compression (DCMC) and displacement controlled monotonic tension tests (DCMT). The DAC mastic was characterized using the direct tension test (DTT). The Desai flow surface (Desai et al. 1986) was used to describe the behavior of both the asphalt mixture and the aggregate skeleton under monotonic loading. The expression for this surface is given in Equation 1.

( )

( )

2 ⎡ I +R n I +R ⎤ + γ 1p −α 1p ⎢ ⎥ a a J ⎦ =0 f = 2 −⎣ pa (1 − β cos3θ )

I1 = σ xx + σ yy + σ zz : p =

where

σ xx + σ yy + σ zz 3

: cos 3θ =

(1)

3 3 J3 3 2 ( J2 ) 2

1 1 J 2 = ( s12 + s22 + s32 ) = ⎡⎣(σ xx − σ yy )2 + (σ yy − σ zz )2 + (σ zz − σ xx )2 ⎤⎦ + τ 2xy + τ 2yz + τ 2xz 2 6 J3

= (σ xx − p )(σ yy − p )(σ zz − p ) + 2τ xyτ yzτ xz

− (σ xx

− p )τ yz2

− (σ yy

− p )τ xz2

− (σ zz

− p )τ xy2

I1 = the first stress invariant, J2 = the second deviatoric stress invariant, J3 = the third deviatoric stress invariant, p = isotropic stress, si = ith principal deviator stress, pa = 0.1 [MPa], α, γ, n and R = model parameters which are temperature and strain rate dependent for the asphalt mixtures. Table 1.

Composition of the PAC, SMA and DAC asphalt mixtures.

Cumulative percentage passing by mass [%] Sieve size [mm]

PAC

SMA

DAC

16 11.2 8 5.6 2 0.063 Bitumen contentc [%] Air voids content [%] Density [kg/m3]

100.0 74.0 37.0 16.5 15.5 3.9 4.3 20.6 2040.6

100.0 94.9 51.5 28.5 20.8 7.4 6.7 5.2 2371.5

100.0 88.5 78.0 66.5 42.5 6.1 5.8 2.8 2428.1

Table 2. Test pavements. Layer

APT section 1

APT section 2

Top layer Second layer Third layer Fourth layer Fifth layer Subbase Subgrade

Dense asphalt concrete, h = 40 mm Open asphalt concrete, h = 60 mm Stone asphalt concrete, h = 80 mm Stone asphalt concrete, h = 90 mm Cement bound RAP, h = 250 mm Sand, h = 5 m Clay, CBR = 2%

Porous asphalt concrete, h = 50 mm Stone asphalt concrete, h = 60 mm Stone asphalt concrete, h = 80 mm Stone asphalt concrete, h = 90 mm Cement bound RAP, h = 250 mm Sand, h = 5 m Clay, CBR = 2%

Wheel load Temperature

Wide base tyre, wheel load 45 kN, tyre pressure 0.9 MPa, speed 20 km/h Between 38–400C at the top and 32–34oC at the bottom of total asphalt thickness

260

The test results obtained in the laboratory testing program were used to explain the permanent deformation behavior of two accelerated pavement test (APT) sections. Details of these two structures are given in Table 2. The two test pavements consisted of four asphalt layers and cement bound asphalt granulate base layer constructed on a well compacted sand subgrade. During testing, the test section was sheltered from climatic influences such as rain and sunshine by a housing hall, which covers the entire installation. The temperature of the test pavement was controlled through an infrared heating system. The strain in the asphalt layers was measured by means of strain transducers while the permanent deformation on the pavement surface was measured using a transverse profilometer. Further details regarding these test pavements can be found in Muraya et al. (2002). 2

TEST CONDITIONS FOR THE AGGREGATE SKELETONS

The DCMCC tests and the PD tests for the aggregate skeleton were conducted on 100 mm diameter by 200 mm height specimens. The aggregate skeleton specimens were compacted by means of a vibrating hammer to such an extent that the void content was equal to the void content in the aggregate skeleton (VMA) of the respective asphalt mixture. The VMA of the mixtures was determined as part of the mixture design. The Marshall mix design procedure as described in the Dutch specifications was used. Table 3 shows the test conditions for the aggregate skeletons. The PD tests were conducted under cyclic confinement and cyclic vertical stress. 3

TEST CONDITIONS FOR THE ASPHALT MIXTURES

The DCMC tests and the DCMT tests were performed on 65 mm diameter specimens with a height of 121 mm specimens. These specimens were cored from Gyratory compacted specimens which had a diameter of 150 mm and a height of approximately 160 mm. The specimens had to be cored from the inner part of the Gyratory specimens because of the large amount of variation in void content over the height and width of the Gyratory specimen. The test specimens cored from the central part of the Gyratory specimens showed only a very limited amount of variation in void content.

skeleton

Test condition for the aggregate skeleton. axial strain rate [%/s]

PAC SMA

0.02

DAC

confining stress σ3 [MPa] 0.031;

0.063;

0.188;

0.031;

0.188;

0.25

0.031,

0.063;

0.125

0.313

rate of displacement [mm/s]

DCMCC tests

PAC - DCMC & DCMT tests

3

0

Figure 1.

stress ratio = vertical stress/maximum vertical stress in DCMCC tests PD tests: maximum load repetitions = 20 000

6

0

confining stress [kPa] skeleton 50 150 250 PAC 0.62 0.82 1.06 0.60 0.97 1.03 0.63 0.83 1.01 DAC 0.42 0.68 0.81 0.43 0.47 0.50 0.58 0.19 0.39 0.64 SMA 0.55 0.92 1.03 1.16 0.82 0.98 1.03 0.52 0.91 0.95 1.03

20 temp. [°C] 40

rate of displacement [mm/s]

Table 3.

SMA & DAC - DCMC & DCMT tests 6 4 2 0 0

20 temp. [°C] 40

DCMC and DCMT target test conditions for the three asphalt mixtures.

261

Figure 1 shows the target test conditions for the asphalt mixtures. These tests conditions were based on the two-factor central composite design (Robinson 2000). The maximum test temperatures for PAC, SMA and DAC were 30, 35 and 35°C respectively. These temperatures were adopted from some initial tests that indicated that these were the maximum temperatures at which the specimens could be handled. Because of their high void content (>20%) especially the PAC specimens could not be tested at higher temperatures. Prior to these tests resilient indirect tension tests were conducted to determine the temperature susceptibility of the asphalt mixtures. 4

MASTIC TEST CONDITIONS

The mastic was characterized using the DTT tests. Prior to DTT tests, the dynamic shear rheometer (DSR) test was used to determine the temperature susceptibility of the DAC mastic. Since permanent deformation occurs at high temperatures, the idea behind the DTT test conditions was to characterize the mastic failure behavior in tension at the highest possible temperatures within the limits of the DTT test set up. The lowest displacement rate for each temperature was identified after which the tests were performed at displacement rates within the minimum and the maximum possible rate of displacement. The tests were performed at temperatures of 5, 7.5, 10, 12.5 and 15°C. Strain rates between 1.23 and 7.4%/s were used at 5°C and at 15°C a strain rate was used of 18.89%/s. Intermediate values were used at the intermediate temperatures. 5

TEST RESULTS

5.1 Comparison of the behavior of the aggregate skeletons The maximum stress of the aggregate skeletons from the DCMCC test results was modeled using the power model shown in Equation 2. The permanent deformation behavior of the aggregate skeleton was characterized by the permanent deformation model shown in Equation 3 that was developed by the Belgian road research centre (Verstraeten et al. 1977). More details about the modeling can be found elsewhere (Muraya 2007). fca = aσ 3b

(2) DN

ε p = AN B + C (e 1000 − 1)

(3)

where fca = maximum stress in DCMCC tests, a, b = regression parameters, ε = permanent deformation, N = number of load repetitions, A, B, C and D are model parameters.

1.2

0.8

0.4

SMA 1% PAC ≥ 10% 10% DAC 1% PAC 1% DAC

1

SMA PAC

0.5

I 1 [MPa]

I 1 [MPa]

0

0

0

1

2

Stress combinations leading to ≥10 and 1% axial permanent deformation

Figure 2.

DAC

ult stress SMA 10% PAC ≥ 10% DAC 10%

SMA 10%

SQRT J 2 [MPa]

SQRT J 2 [MPa]

1.5 SMA PAC DAC

3

0

1

2

3

4

Maximum stress at failure in DCMCC tests and stress combinations leading to ≥10% axial permanent deformation

PD and DCMCC tests for PAC, SMA and DAC aggregate skeletons.

262

For purposes of illustrating the permanent deformation behavior of the three aggregate skeletons, the stress conditions leading to 10% and 1% axial permanent deformation after 20,000 load repetitions were determined. The left hand part of Figure 2 shows the stress combinations, presented in the SQRT J2–I1 space, resulting in 10% and 1% axial deformation. This figure clearly shows that the stone skeleton mixtures i.e. SMA and PAC can sustain much higher stresses to 10% deformation in comparison to the DAC skeleton. The figure also shows that SMA provides an excellent resistance to permanent deformation. However failure occurs almost immediately when the stresses are too high. The right hand part of Figure 2 shows a comparison of the maximum stress at failure in the DCMCC tests and the stress combinations leading to 10% axial permanent deformation in PAC, SMA and DAC aggregate skeletons. The figure shows that severe permanent deformation in the PAC and SMA stone skeletons takes place at stress conditions close to the maximum stress and that severe permanent deformation in the fine DAC skeleton occurs at lower stress combinations in comparison to the maximum stress at failure. 5.2 Comparison of stress at Initiation of dilation and Initiation of plasticity for the asphalt mixtures The test results of the asphalt mixtures were modeled using the Unified model shown in Equation 4. Further details regarding this modeling can be found in Muraya (2007). P = Phigh + ( Plow − Phigh )S

(4)

where P = stress value, Phigh and Plow = limiting stress values, S = shape function. Figure 3 shows the stress levels at initiation of plasticity and dilation as determined from the DCMC tests performed on the three asphalt mixtures. The figure shows that at high temperatures, the stress at initiation of dilation for SMA is more or less similar to the stress at initiation of plasticity. The figure also shows that the stress at initiation of dilation is for PAC is close to the stress at initiation of plasticity. 5.3 Comparison of the extent of dilation in the mix and in the aggregate skeleton In order to compare the extent of dilation in the asphalt mixture and the aggregate skeleton, the change in volume relative to the minimum volume at the point of initiation of dilation was considered. This change in volume is expressed as shown in Equation 5. The expression ensures that the points of initiation of dilation in all the tests commence from the same reference volume of zero. The change in volume was considered for the DCMCC tests conducted on the aggregate skeleton and the DCMC conducted on the mixture. In the figures that follow, numbered labels will be used for the DCMCC aggregate skeleton tests and alphabet labels for the DCMC mixture tests. change in volume strain = ε vol − ε vol min

(5)

where εvol = volumetric strain [%], εvol min = vol. strain at the point of initiation of dilation [%].

Stress [MPa]

3

PAC, SMA and DAC dilation and Plasticity stress at 35ºC PAC SMA DAC

1.5

d - dilation p - plasticity d p

0 0

Figure 3.

2 strain rate [%/s]

Stress at initiation of dilation and plasticity at 35˚C.

263

4

14

R

0

J Q

11

P

PAC

15

0 N

I

30

εa [%]

M

A B C D E F G H I J K L M N O P Q R

O εvol - εvolmin [%]

-15

5

2 3

C

6

7 9

H

13

-30

G

E

10

L

A

8

B D

1

F

K

12

4

DCMCC skeleton tests DCMC mix tests axial axial conf Temp strain strain stress σ3 Label 0 Label rate rate [ C] [MPa] [%/s] [%/s]

-45

0.21 0.21 0.20 0.20 0.21 0.20 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

0.03 0.03 0.03 0.06 0.06 0.06 0.03 0.03 0.03 0.06 0.06 0.06 0.19 0.19 0.19 0.31 0.31 0.31

1 2 3 4 5 6 7 8 9 10 11 12 13 14

30 27.1 27.1 20 20 20 20 20 20 20 12.9 12.9 10 5

2.05 0.60 3.44 0.01 2.07 2.10 2.10 2.12 2.01 4.16 0.62 3.49 2.18 4.46

Figure 4. Comparison of the dilation in the DCMCC tests conducted on the PAC aggregate skeleton and the dilation observed during the DCMC tests performed on the PAC asphalt mixture.

0

2

4

0

3

εaxial [%] 11

9

6

8

4

εvol - εvolmin [%]

-5

-10

Label

7

2

10 A B C D E F G H I

A B C

-15

D E

F G H

-20

1 I

15 8

6 13

-25

DCMCC skeleton tests

12 5

SMA

14

DCMC mix tests

axial conf Temp strain stress σ3 Label 0 rate [ C] [MPa] [%/s]

axial strain rate [%/s]

0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

32.1 32.1 25 25 25 25 25 25 25 25

0.60 3.51 0.01 2.02 2.07 2.02 2.10 2.09 2.05 2.07

11

25

4.16

12

17.9

0.60

13

17.9

3.47

14

15

2.09

15

5

3.51

0.03 0.03 0.03 0.19 0.19 0.19 0.25 0.25 0.25

1 2 3 4 5 6 7 8 9 10

Figure 5. Comparison of the dilation in the DCMCC tests conducted on the SMA aggregate skeleton and the dilation observed during the DCMC tests performed on the SMA asphalt mixture.

Figure 4 shows a comparison of the extent of dilation in the DCMCC tests conducted on the PAC aggregate skeleton and the DCMC tests performed on the PAC asphalt mixture. The figure shows that despite of confinement, the extent of dilation in the PAC aggregate skeleton was higher than in the PAC asphalt mixture. At equal axial strains, most of the DCMCC tests performed on the aggregate skeleton exhibited more dilation than the DCMC tests performed on the asphalt mixture. 14 of the 18 DCMCC tests conducted on the aggregate skeleton exhibited more dilation (higher value for εvol – εvol min at the same εa) than the DCMC tests conducted on asphalt mixture. Two DCMCC tests (P and Q) performed at a confinement level of 0.31 MPa and 2 DCMCC tests (M and N) performed at a confinement level of 0.187 MPa exhibited less dilation than the DCMC tests. Figure 5 shows a comparison of the extent of dilation in the DCMCC tests conducted on the SMA aggregate skeleton and the DCMC tests performed on the SMA asphalt mixture, while Figure 6 shows a comparison of the extent of dilation in the DCMCC tests conducted on the DAC aggregate skeleton and the DCMC tests performed on the DAC asphalt mixture. Both figures show that the dilatation of the stone skeletons is much more than the dilation of the respective asphalt mixtures. 264

5.4 Strength at failure of the DAC mixture and tensile strength of the DAC mastic The maximum stress in the DCMC, DCMT and DTT test for the DAC mixture were compared using equivalent strain rate at a reference temperature of 40°C. Figure 7 shows a comparison of the DCMC, DCMT and DTT tests results for the DAC on an equivalent strain rate scale. Several observations can be made from this figure: – At high strain rates, the strength of the mastic is within a comparable range to the tensile strength of the DAC asphalt mixture. This suggests that at low temperatures and high strain rate, the resistance to tensile failure in the DAC asphalt mixture is to a large extent dependent on the tensile strength of the mastic. – The aggregate skeleton has little capacity to provide the tensile strength in the DAC asphalt mixture. Consequently it is logical to conclude that most of the observed tensile strength of the DAC asphalt mixture at high temperatures and low strain rates is as a result of the mastic. 5.5 Ultimate surface for the asphalt mixture and the aggregate skeleton The ultimate flow surfaces (equation 1) for the asphalt mixture and the aggregate skeleton were based on the response developed by Desai presented in section 1. A vertical triaxial

0

2

4

6

0

8 2

9

C

εvol - εvolmin [%]

-5

εaxial [%] 10 L abel

10

B A

4 7

-10 D -15

E

1 F G

-20 H

I

14

6

3

0.02

0.03

1

35

2.06

B C D E F G H I

0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

0.03 0.03 0.06 0.06 0.06 0.12 0.12 0.13

2 3 4 5 6 7 8 9 10 11 12 13 14

32.1 32.1 25 25 25 25 25 25 25 17.9 17.9 15 5

3.51 0.61 2.14 2.09 0.01 2.03 2.09 2.00 3.96 0.59 3.34 1.99 3.44

11 13

axial strain rate [%/s]

A

5

12

-25

axial conf T emp strain stress L abel 0 σ3 rate [ C] [%/s] [MPa]

8

DAC

Figure 6. Comparison of the dilation in the DCMCC tests conducted on the DAC aggregate skeleton and the dilation observed during the DCMC tests performed on the DAC asphalt mixture.

Strength [MPa]

100

10

1

DAC fc (DCMC) DAC ft (DCMT) mastic ft (DTT) model Reduced strain rate [%/s]

0.1 0.10

10

10000

Figure 7. Comparison of the DCMC, DCMT and DTT tests results for DAC at a reference temperature of 40°C.

265

strain rate was determined to obtain pavement strain rates that could be applied on the test results. The vertical triaxial strain rate was determined for the top layers of both APT sections. The vertical triaxial strain rates were determined from the profile of the calculated vertical triaxial strain along the wheel path. The vertical triaxial strain rates were estimated by dividing the profile into different intervals depending on the slope of the profile. The ultimate surfaces of asphalt mixtures and the aggregate skeletons are compared at 40°C and at the representative strain rate and average confinement determined from the second test pavement. Interval 2 and interval 3 of the second test pavement were selected to demonstrate the effect of low and high strain rates and a high confinement on the ultimate surfaces. Figure 8 shows an illustration of the ultimate surfaces for the asphalt mixture and aggregate skeleton of the PAC, SMA and DAC. The figure shows that the tension resistance of the DAC asphalt mixture is higher than that of the SMA and PAC asphalt mixtures. This

SQRT J 2 [MPa]

2

1 PAC skel 0.49MPa DAC skel 0.49MPa SMA skel 0.49MPa PAC mix 5.98 %/s SMA mix 5.98 %/s DAC mix 5.98 %/s

0 -4

-2

0

2

4

6 I 1 [MPa]

Figure 8. Surfaces for the aggregate skeleton and asphalt mixture of PAC, SMA and DAC at a reference temperature of 40°C.

0.16

0.5

PAC-Ultimate surface pav3 top layer

SQRT J 2 [MPa]

mix ult 0.23 %/s mix pl 0.23 %/s

0.08

-0.5

0

0.1

0.2

0.3

SQRT J 2 [MPa]

0.2

pav stresses mix ult 0.91 %/s mix pl 0.91 %/s

I 1 [MPa]

0 0.5

1.5

2.5

PAC third test pavement interval 3

Figure 9.

0.5

PAC third test pavement interval 2

PAC-Ultimate surface pav3 top layer

-0.5

0

0.3

PAC third test pavement interval 1

0.1

pav stresses mix ult 6.81 %/s mix pl 6.81 %/s

0

I 1 [MPa]

0 -0.1

PAC-Ultimate surface pav3 top layer

SQRT J 2 [MPa]

pav stresses

PAC test pavement; intervals 1, 2 and 3.

266

1

I 1 [MPa] 1.5

observation suggests that the contribution of the mastic in the DAC asphalt mixture towards resistance to tensile failure is larger than that of the mortar in PAC and SMA. The figure also shows that the ultimate surface of the DAC aggregate skeleton is bigger than the ultimate skeleton of the SMA and PAC. It is also evident from this figure that the contribution of the mastic towards resistance against failure and in extension permanent deformation is more important in the DAC skeleton than in the PAC and SMA stone skeleton mixtures. 5.6 Comparison of test results and pavement stress and strain conditions Since the top layer of the second and third test pavements was composed of DAC and PAC respectively, the test results of the PAC and DAC asphalt mixtures were compared to the stress conditions in the top layer of both APT sections. The ultimate flow surface and the surfaces representing initiation of plasticity surfaces of the asphalt mixture for PAC and DAC were determined based on the Desai surface (Desai et al. 1986) at the vertical triaxial strain rates occurring in the three intervals. The surfaces were then compared to stress conditions in the pavement. Limitations in space only permit us to discuss the comparison made for the PAC test section. 5.6.1 PAC test pavement Error! Reference source not found. shows the ultimate surface (indicated by the straight line) and the initiation of plasticity surface (indicated by the curved line) at the three intervals in comparison to the pavement stress conditions in the test pavement. The figures show that most of the pavement stresses are beyond the PAC surface at initiation of plasticity. This suggests that a linear visco-elastic approach cannot be used to predict the permanent deformation in this test pavement. The figures also imply that a plasticity approach would be more appropriate.

6

CONCLUSIONS

• SMA provides excellent resistance to permanent deformation even at very high stress levels but failure occurs almost immediately when the stress levels are too high. • The stress conditions for the SMA asphalt mixture at initiation of dilation and at initiation of plasticity are almost the same. In practice this implies that SMA is a very rut resistant mixture because damage or plasticity initiates at initiation of dilation. However, dilation in the pavement does not occur in the same way as in the laboratory. In reality it is hindered by the surrounding material. This means that in practice high confining stresses develop and counteract the development of permanent deformation. Almost the same phenomenon occurs in PAC where the stress at initiation of dilation is close to the stress at initiation of plasticity. This makes a PAC mixture rut resistant as well. • The results obtained on DAC indicate quite a different trend in comparison to the PAC and SMA. The ultimate surfaces of the DAC mixture suggested that the mastic has a significant contribution to the strength of the mixture. In addition, the PD tests performed on the aggregate skeleton showed that significant permanent deformation develops at stress levels well below the failure stresses. The results of the tests performed on the DAC mixture indicated that initiation of plasticity takes place at stress levels below the initiation of dilation. This means that in reality, development of plastic deformation is not counteracted immediately by increased confinement that occurs due to dilation. Given the fact that the mastic plays an important role in resistance against failure and by extension in resistance to permanent deformation, ample attention should be paid on the tensile characteristics of the mastic since they have a large effect on the location of the failure envelope in the I1–√J2 space. • Since dilation contributes significantly to the permanent deformation of PAC and SMA mixtures, ample consideration should be given to the design of stone skeleton mixtures as well as to the degree of compaction. A well designed stone skeleton which is 267

well compacted is prone to have a high tendency to dilate which helps the resistance to permanent deformation. • Despite of the application of confinement during the aggregate skeleton tests, the extent of dilation in the aggregate skeleton was higher than in the asphalt mixture tests that were conducted without confinement. This underscored the importance of the tensile strength in the bituminous mortar. • The contribution of the mastic towards resistance to permanent deformation is more important in the DAC aggregate skeleton than in PAC and SMA stone skeletons. • In the two test pavements, most of the pavement stress conditions were beyond the surface at initiation of plasticity. This implies that a linear visco-elastic approach cannot be used to predict the permanent deformation occurring in asphalt pavements. A non-linear elasto visco-plasticity should be used. REFERENCES Desai, C.S., Somasundaram, S. & Frantziskonis, G. 1986. A Hierarchical Approach for Constitutive Modelling of Geologic Materials, International Journal of Numerical and Analytical Methods in Geomechanics, vol. 10, No. 3: pp. 225–257. Muraya, P.M. 2007. Permanent Deformation of Asphalt Mixtures, Doctor of Philosophy Thesis, Road and Rail Research Laboratory, Delft University of Technology, Delft. Muraya, P.M., Molenaar, A.A.A. & van de Ven, M.F.C. 2004. Permanent deformation behavior in asphalt mixes, 5th International PhD Symposium in Civil Engineering, pp. 765–772, vol. 2, Delft. Muraya, P.M., Houben, L.J.M. & Dommelen, A.E. van. 2002. LINTRACK research into Rutting of Asphalt Concrete Test Pavement, Report 7-02-200-43M, Road and Rail Research Laboratory, Delft University of Technology, Delft. Robinson, G.K. 2000. Practical Strategies for Experimenting, Sussex. Verstraeten, J., Romain, J.E. & Veverka, V. 1977. The Belgian Road Research Center’s Overall Approach to Asphalt Pavements Structural Design. Proceedings of 4th International Conference Structural Design of Asphalt Pavements, Michigan, United States of America.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A new rutting evaluation indicator for asphalt mixtures K. Su Tongji University, Shanghai, China Pot and Airport Research Institute, Yokosuka, Japan

L. Sun Tongji University, Shanghai, China

Y. Hachiya Service Center of Port Engineering, Yokosuka, Japan

R. Maekawa Pot and Airport Research Institute, Yokosuka, Japan

ABSTRACT: Considerable research indicates that shear deformation rather than densification in asphalt mixture layer accounts for most of the rutting in hot mix asphalt (HMA) pavements. This paper is aimed to use a newly developed test method to evaluate this type of shear flow rutting instead of the conventional wheel tracking test. A relationship between the shear strength derived from SUPT test and rutting of asphalt mixtures is well established. Then, the shear strength as an indicator to control rutting is put forward for various traffic volumes. 1

INTRODUCTION

Rutting is one of the major distresses in asphalt concrete pavements. Recent studies indicated that it was primarily contributed by the shear flow of hot mix asphalt (HMA) rather than the deformation occurring in each layer when the asphalt pavement was well compacted during the construction (Drakos et al., 2001; Fwa et al., 2005; Su et al., 2008). The mechanism can be explained as follows: when the HMA layer is loaded at high temperature, there may occur within a plane where the shear stress exceeds the shear strength of HMA and in turn aggregate particles begin to slide by or shear with respect to each other, which results in permanent deformation. Therefore, the key to properly evaluate mixture resistance to rutting is to measure the shear resistance of HMA. In the current practice of evaluating the rutting susceptibility of asphalt mixture, wheel tracking test is widely recognized as a proof test in the mix design and quality control/quality assurance. However, this kind of test method often fails to differentiate the good and bad mixtures in rutting resistance. As an alternative, the shear performance tests in terms of triaxial test and repeated simple shear test at constant height are used by some pavement researchers in the past. But due to the complexity and time-consuming, these tests have not been routinely used. Motivated by pursuing a compact but efficient method to evaluate the rutting of asphalt mixture instead of the wheel tracking test, this paper tried adopting a newly developed test method to evaluate the shear strength of asphalt mixture. Based on the laboratory test results as well as in reference to the previous research, the shear strength criteria to rutting were put forward.

269

2

LABORATORY EXPERIMENT

2.1 Materials and aggregate gradation This study focused on the asphalt mixtures with the nominal maximum aggregate size of 13 mm, which were normally used in surface course in China. Four dense-graded asphalt mixtures (AC 13 A, AC13B, AC13C and AC13D) and a gap graded mixture (AC13E) were evaluated as shown in Figure 1. A diabase and a conventional asphalt binder with the penetration of 60/80 were, respectively, selected as aggregates and binder. 2.2 Mixtures design and specimen fabrication All the mixtures were designed by the Marshall mix design method with 75 blows per side on the specimen. At the selected optimal asphalt content (OAC), the volumetric properties of all the mixtures can meet the specification limits. The slab specimens for wheel tracking test were compacted by steel roller compactor and the specimens for shear strength test were compacted by Superpave gyratory compactor (SGC). The wheel tracking test specimen was duplicated in the shape of 300 × 300 × 50 mm and the sample for shear strength test was 100 mm in diameter and 100 mm in height. The air voids for two kinds of specimens have the same level of around 4%. Samples were tested triplicate and the average of the three test results were used for analysis in the following sections. 2.3 Wheel tracking test The laboratory wheel tracking test used is presented in Figure 2. It can be conducted at the temperature ranging from 20 to 60°C. After the specimens were held in an environmental chamber at the prescribed temperature for 6 hours to reach the temperature equilibrium, they were tested by a rubber faced tire, which moved back and forth with the speed of 42 passes/min to apply a load of 0.72 MPa for an hour. The rutting depth was automatically recorded in the test. 2.4 Shear strength test In general, rutting occurs mainly along the wheel path, while the rest part of asphalt pavements are not deformed by the repeated load. When a circular load sitting on the pavement, mainly the 100

AC13A AC13B AC13C AC13D AC13E

Percent passing (%)

80

60

40

20

0 0.075 Figure 1.

0.15

0.3

0.6 1.18 Sieve Size (mm)

Aggregate gradation of evaluated asphalt mixtures.

270

2.36

4.5 13.2

circular area will suffer the deformation and the surrounding limited section will just provide a barrier to restrain the load-underneath materials to shear flow. In other word, the load-induced deformation can be analyzed at the limited area instead of the whole section. For this limited area, when it receives the same load as that in the whole section, it can deform similar with that occurring in the infinite pavement. This mechanism is schematically shown in Figure 3. On the basis of this mechanism, a new test method called SUPT test (Static Uniaxial Penetration Test) was developed to study the load induced spot deformation, where a circular load with the diameter of 28.5 mm sitting on the cylindrical specimen of 100 × 100 mm can produce a similar stress/strain response as that in the real pavement by the same load (Sun, 2006). As shown in Figure 4, it is usually performed at the temperature of 60°C. As the strength derived from SUPT test can reflect the capacity of HMA mixture to resist shear flow, it is designated as shear strength. The shear strength is calculated as the peak point of loading deformation curve as shown in Figure 5 multiplied by the shear coefficient of 0.339, which is in fact the maximum shear stress in the semi-infinitive space when receiving a unit uniform circular load. Though the SUPT test with uniform contact pressure and the linear elastic assumption can not represent the reality, such an expression does reflect the direct correlation between the average contact pressures and shear

Figure 2.

Laboratory wheel tracking test.

Equal to

In situ pavement

Figure 3.

Schematic mechanism of the shear strength test.

271

Figure 4.

Static uniaxial penetration test (SUPT test).

4.0

SUPT strength (MPa)

3.5 Peak point 3.0 2.5 2.0 1.5 1.0 0.5 0.0 0.0

0.5

1.0

1.5

2.0

2.5

Deformation (mm)

Figure 5.

Typical load induced deformation curve in SUPT test.

strength of asphalt mixtures. Currently, the SUPT test is only available for the HMA mixture with 13 mm nominal maximum aggregate size. 3

TEST RESULTS AND ANALYSIS

3.1 Test results The AC13 A mixture was firstly tested by wheel tracking test with the results showing that the deformation at 20°C was negligible and consequently other mixtures were only tested at 40°C and 60°C. The results of wheel tracking test and SUPT test are summarized in Figure 6. 3.2 Correlation of rutting and shear strength The rutting from wheel tracking test and the shear strength by SUPT test was correlated by the commonly used power equation as expressed by the general form of Equation 1, which can account for the rutting accumulation with the number of loading repetitions. RD = a × (N )b × (T )c × (1/B)d 272

(1)

6

6

Shear strength = 1.06 MPa 60 oC

4 3 o

40 C

2 1

60 oC

4 3 40 oC

2 1

20 oC

0

0 0

500

1000

1500

2000

0

2500

500

1000

1500

2000

Number of loading pass

Number of loading pass

(a) Mix AC13A

(b) Mix AC13B

6

2500

8

4 3 40 oC

2

Shear strength = 0.86 MPa

7

60 oC

60 oC

6

Deformation/mm

SUPT strength = 0.98 MPa

5

Deformation/mm

Shear strength = 1.15 MPa

5

Deformation/mm

Deformation/mm

5

5 4 3

40 oC

2

1

1 0 0

500

1000

1500

2000

0

2500

0

500

1000

1500

2000

Number of loading pass

Number of loading pass

(c) Mix AC13C

(d) Mix AC13D

2500

4

Deformation/mm

SUPT strength = 1.46 MPa 3

60 oC

2 40 oC 1

0 0

500

1000

1500

2000

2500

Number of loading pass

(e) Mix AC13E Figure 6.

Results of wheel tracking and SUPT tests.

where, RD = rutting depth (mm), B = shear strength (MPa), N = loading repetitions (cycles), T = temperature (°C), a, b, c and d = model constants. Using the test results described in Figure 6 to fit Equation 1, the model constants (a, b, c and d) were determined by the least square method. Then, Equation 1 can be written in Equation 2, which has an excellent regression variant (R2 = 0.96). RD = 0.43 × 10–4 × (N )0.38 × (T )2.13 × (1/B)0.90 273

(2)

Table 1.

Recommended criterion of shear strength for different traffic volumes.

Traffic level

Extreme-heavy

Ultra-heavy

Heavy

Moderate

ESAL* (×1000) Rutting depth (mm) Shear strength (MPa)

>80,000 <2.0 >1.93

40,000∼80,000 2.0∼3.0 1.34∼1.93

12,000∼40,000 3.0∼4.0 1.03∼1.34

4,000∼12,000 4.0∼5.0 0.85∼1.03

ESAL*: Equivalent Single Axle load = 100 kN.

3.3 Criteria of shear strength to rutting To provide enough rutting resistance within the design period, Chen et al. (2007) suggested that the rutting depth of an asphalt mixture measured in laboratory wheel tracking test should be less than a critical value. These criteria for different traffic levels were illustrated in Table 1 (Chen et al., 2007). In reference to this research, the criteria of shear strength against rutting were recommended according to the relationship of shear strength and rutting depth (see Table 1). 4

CONCLUDING REMARKS

Through laboratory wheel tracking tests and SUPT tests, the criteria of shear strength to control rutting were established. Thanks to the efficiency and simplicity of SUPT test relative to the wheel tracking test, these criteria are promising to evaluate the rutting resistance of asphalt mixtures in the laboratory. Further research is recommended to extend these conclusions to other asphalt mixtures with difference asphalt binders and aggregate sizes. REFERENCES Chen, X.W., Huang, B.S. and Xu, Z.H. 2007. Comparison between flat rubber wheeled loaded wheel tester and asphalt pavement analyzer. Road Materials and Pavement Design. 8(3): 595–604. Drakos, C.A., Roque, R. and Birgisson, B. 2001. Effect of measured tire contact stresses on Nearsurface rutting. Journal of the Transportation Research Board. TRR 1764: 59–69. Fwa, T.F., Tan, S.A. and Zhu, L.Y. 2004. Rutting prediction of asphalt pavement layer using C – Φ Model. ASCE Journal of Transportation Engineering. 130(5): 675–683. Su, K., Sun, L.J. and Hachiya, Y. 2008. A new method for predicting rutting in asphalt pavements employing Static Uniaxial Penetration Test. International Journal of Pavement Technology and Research. 1(1): 24–33. Sun, L.J. 2006. Theory of structural behavior of asphalt pavement. Beijing: The people communication press.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of different predictive dynamic modulus models of asphalt mixtures used in Argentina F.O. Martínez & S.M. Angelone Road Laboratory, School of Engineering, University of Rosario, Rosario, Argentina

ABSTRACT: The dynamic modulus of asphalt mixtures is one of the most important inputs for mechanistic empirical pavement design procedures. Several researchers have proposed different procedures for the estimation of the dynamic modulus from the volumetric mix properties, binder characteristics and aggregate gradation. This paper presents a comparison between measured and estimated dynamic modulus values using three different predictive procedures. The obtained results show that reliable first order dynamic modulus estimates for asphalt mixtures typically used in Argentina can be obtained using any of the predictive procedures considered in this study. 1

INTRODUCTION

Argentina is trying to implement a Mechanistic Empirical Pavement Design Procedure based on the MEPDG developed under the NCHRP 1-37 A Project (NCHRP 2004) and adjusted to local conditions of materials, traffic and climate. In this procedure, the primary stiffness property of interest for asphalt materials is the time-temperature dependent dynamic modulus Ed. According with this procedure, the majority of the roads in Argentina should be considered under the Level 2, or even 3, of the hierarchical approach presented in the NCHRP 1-37 A Project. For these levels of analysis and for the hot-mix asphalt materials, the dynamic modulus could be estimated from conventional data including aggregate gradation, volumetric properties of the mixture and binder characteristics. However, it is important to know if this estimation is applicable to our local conditions of materials and construction procedures. During the last year, a significant amount of data from surface and base layers of flexible pavements have been collected from different construction projects in Argentina including experimentally determined dynamic modulus results, volumetric mix properties and recovered binder characteristics. Other set of data include the same results but for samples compacted in laboratory. Using the Witczak equation, the Hirsch model and the procedure developed by Heukelomp and Klomp (1964), the dynamic modulus of these mixtures have been estimated from the volumetric and binder properties and then compared with the experimental results. Several researchers have conducted studies comparing predicted and measured dynamic modulus values (Kim et al. 2005, Birgisson et al. 2005, Garcia & Thompson 2007). However, these studies have been mainly focused on the comparison of predicted values obtained with the Witczak predictive equation and the Hirsch model and measured values using the simple performance tester according to the procedure described in NCHRP Report 465 (Witczak et al. 2002a). In this paper, the measured dynamic modulus values have been obtained using the indirect tension (IDT) mode with sinusoidal loads at different frequencies and testing temperatures using an experimental equipment developed at the Road Laboratory of the University of Rosario, This paper presents the comparison of the estimated and measured dynamic modulus for the mixes analyzed in order to assess the predictive capability of these models. In general, results indicate that these models provide reasonable predictions of dynamic modulus within the scope of the implementation of a mechanistic-empirical pavement design procedures. 275

The experimental materials and methods, the utilized models, the obtained results, the comparisons and the statistical analysis are presented and discussed. 2

MATERIALS AND PROCEDURES

2.1 Asphalt mixtures Two different sets of asphalt mixtures have been considered. The first set named as PAVEMENT CORES, was a group of cores obtained from 17 different sections of asphalt pavements recently built around Rosario in the Littoral region of Argentina. In these sections, 33 locations were selected where asphalt concretes with different formulations were used for the surface and the base layers in order to obtain 42 different asphalt mixtures conventionally used in Argentina for surface and base layers of asphalt pavements. All of these mixtures can be classified as dense graded asphalt concretes with conventional binders. The second set denominated LABORATORY SAMPLES, was composed with laboratory compacted samples of 8 different asphalt concretes formulated with conventional binders. For the PAVEMENT CORES, six cores were taken at each location. Two of these cores were used for the determination of the dynamic modulus as is described later. The other four cores were used in the laboratory for the determination of the volumetric properties of each mixture, the properties of the recovered binders (viscosity at different temperatures, penetration and softening point) and the aggregate gradation. A database containing the information of the 42 mixtures was elaborated covering a wide range of properties used as inputs for the different predictive procedures and equations considered in this study. The same procedure has been used for the LABORATORY SAMPLES. Six samples were compacted at the laboratory according with the Marshall procedure. Two of these samples were reserved for the dynamic modulus test and the other four were used in the laboratory for the determination of the volumetric properties of each mixture, the properties of the recovered binders and the aggregate gradation. Also, a database containing the information of these 8 mixtures was elaborated. 2.2 Dynamic modulus determination The Dynamic Modulus Ed of the cores was experimentally measured with the Indirect tension (IDT) mode with sinusoidal loadings following a procedure very similar as it was developed by Kim et al. 2004. Assuming the plane stress state, the linear viscoelastic solution for the dynamic modulus of asphalt mixtures under the IDT mode results: Ed =

P (K1 + μ ⋅ K 2 ) Δh ⋅ t

(1)

where Ed = dynamic modulus; P = amplitude of the applied sinusoidal load; Δh = amplitude of the resulting horizontal deformation; t = thickness of specimen; K1 and K2 = coefficients depending on the specimen diameter and gauge length; and μ = Poisson’s ratio. Testing was performed using a servo-pneumatic machine, developed at the Road Laboratory of the University of Rosario, using a 5000 N load cell, which is capable of applying load over a range of frequencies ranging from 0.01 Hz to 5 Hz. A proportional valve controlled by the computer is used to generate the sinusoidal loadings at the required frequency. The test frame is enclosed into a temperature chamber. The temperature control system is able to achieve the required testing temperatures ranging from 0°C to 50°C. The data acquisition system was also developed at the Road Laboratory of the University of Rosario and is capable of measuring and recording data from three channels simultaneously: two for horizontal displacements and one for the load cell. In order to increase the simplicity of the test, only horizontal deformations were measured. From previous studies (Gschösser 2008), the Poisson’s ratio was adopted as a function of the test temperature in the form: 276

μ =a+bT

(2)

where μ = Poisson’s ratio, T = test temperature; and a and b = regression constants. The horizontal deformations were measured using LVDTs mounted on each of the specimen faces using a 35 mm gauge length. The applied load and the average horizontal deformation were calculated fitting sinusoidal functions to the measured experimental data. For the adopted gauge length and for specimens with 100 mm diameter, the coefficients K1 and K2 result: K1 = 0.188 and K2 = 0.595. The cores and the samples used for the determination of the dynamic modulus were trimmed to the test thickness approximately equal to 50 mm using a laboratory concrete saw. In this study, four temperatures (10, 20, 30 and 40°C) and five frequencies (4, 2, 1, 0.5 and 0.25 Hz) were used. Then, the experimental values of the two specimens coming from the same location were used to build dynamic modulus master curves using nonlinear regression techniques to fit experimental data to a sigmoidal function and solving the shift factors, based on the Arrhenius equation, simultaneously with the coefficients of that function. A more detailed description of the testing equipment and the data analysis procedures were reported by Martínez & Angelone (2006). The master curve was used to average the experimental values of the dynamic modulus of each mixture at the same temperature and frequency experimentally considered. Thus, a database containing 840 experimental dynamic modulus values (42 mixtures, 4 temperatures and 5 frequencies) was developed for the PAVEMENT CORES set. Also, other database containing 160 experimental dynamic modulus values was developed for the LABORATORY SAMPLES set. All of these values were used in the comparisons with the estimated dynamic modulus values from the different predictive equations and procedures considered in this study. 3

CONSIDERED PREDICTIVE PROCEDURES

In this study, three different procedures (equations, models) have been considered for the prediction of the dynamic modulus Ed. These procedures are designed as: – The Heukelomp and Klomp procedure – The Witczak predictive equation – The Hirsch predictive model. 3.1 The Heukelomp and Klomp procedure Heukelomp and Klomp have developed a predictive procedure using the binder stiffness Sbit, the effective binder content by volume Vb and the aggregate content by volume Vg of the mixture as variables for the dynamic modulus prediction (Heukelomp & Klomp 1964). The volumetric concentration of the aggregates Cv is calculated as: Cv =

Vg Vg + Vb

(3)

with Vg = aggregate content, % by volume; and Vb = effective bitumen content, % by volume. Then, the dynamic modulus Ed is calculated as: ⎛ 2.5 Cv ⎞ Ed = Sbit ⎜1 + ⎟ n 1 − Cv ⎠ ⎝

n

⎛ 4 ⋅ 1010 ⎞ n = 0.83 log ⎜⎜ ⎟⎟ ⎝ Sbit ⎠ with Ed = dynamic modulus of the mixture in MPa; and Sbit = binder stiffness in MPa. 277

(4)

(5)

The binder stiffness Sbit was calculated with de Van der Poel nomograph (Van der Poel 1954) from the binder properties and for the same conditions of temperatures and frequencies used experimentally. The Heukelomp and Klomp procedure was developed for asphalt mixtures containing approximately 3% air voids contents. Later, van Draat & Sommer 1965 introduced a modification in the volumetric concentration of aggregates for air voids contents different from 3% in the form of: C′v =

100 Cv (100 + Va − 3)

(6)

with C′v = modified volumetric concentration of aggregates; and Va = air voids content in percent. 3.2 The Witczak predictive equation The Witczak model (Andrei et al. 1999) is a result of refinement over many years and of development of a database with more than thousands of dynamic modulus measurements. The model is capable of predicting dynamic modulus of hot-mix asphalt from the viscosity of asphalt binder and volumetric properties of the aggregate mix that are usually obtained from the mix design process and asphalt binder specifications. log Ed = 3.750063 + 0.02932 p200 − .001767( p200 )2 ⎛ Vb ⎞ − 0.002841 p 4 − 0.058097 Va − 0.802208 ⎜ ⎟ ⎝ Vb + Va ⎠ +

(7)

3.871977 − 0.021 p 4 + 0.003958 p38 − 0.000017( p38)2 + 0.00547 p34 1 − e[ −0.603313 − 0.31335(log f ) − 0.393532(log η )]

where Ed = dynamic modulus in 105 psi; η = bitumen viscosity at the test temperature in 106 Poises; f = loading frequency in Hz; Va = air void content in percent; Vb = effective bitumen content in percent by volume; p34 = cumulative percent retained on the #3/4 sieve; p38 = cumulative percent retained on the #3/8 sieve; p4 = cumulative percent retained on the #4 sieve; and p200 = percent passing the #200 sieve. For the comparisons, the dynamic modulus values in psi were converted to MPa. 3.3 The Hirsch model The Hirsch model is a rational, though semi-empirical method of predicting asphalt concrete modulus in which the dynamic modulus of the asphalt concrete Ed is directly estimated from binder modulus Gb*, voids in the mineral aggregate VMA and voids filled with asphalt VFA in the form (Christensen et al. 2003): ⎡ ⎛ VMA ⎞ * ⎛ VFA ⋅ VMA ⎞ ⎤ Ed = Pc ⋅ ⎢ 4200000 ⋅ ⎜1 − ⎟ + 3Gb ⎜ ⎟⎥ 100 ⎝ ⎠ ⎝ 10000 ⎠ ⎦ ⎣ ⎡ 1 − VMA VMA ⎤ 100 + + (1 − Pc ) ⎢ *⎥ ⎢⎣ 4200000 VFA ⋅ 3Gb ⎥⎦

( 20 + Pc = 650 +

) )

VFA ⋅ 3 Gb* 0.58 VMA VFA ⋅ 3 Gb* 0.58

(

VMA

278

−1

(8)

(9)

where Ed = dynamic modulus of the mixture in psi; Gb* = dynamic shear modulus of the binder in psi; VMA = voids in the mineral aggregate n percent; VFA = voids filled with asphalt in percent; and Pc = aggregate contact factor. In Argentina, there is only one DSR for the determination of the Gb*. As this equipment was not available for this study and, in order to obtain estimations of the dynamic modulus of the asphalt mixtures to be applied for pavement design purposes, an alternative approach has been adopted. The dynamic shear modulus of the binder Gb* was estimated using a procedure based on the ASTM A-VTS relationship as (Bari & Witczak 2006): A′ = 0.9699 f −0.0527 ⋅ A

(10)

VTS ′ = 0.9668 f −0.0575 ⋅VTS

(11)

log log η f ,T = A′ + VTS ⋅ log TR

(12)

where f = loading frequency in dynamic shear mode as used in the Gb* testing in Hz; A = regression intercept from the conventional ASTM A-VTS equation; VTS = slope from the conventional ASTM A-VTS equation; A′ = adjusted A from loading frequency; VTS′ = adjusted VTS from loading frequency; ηf,T = viscosity of the asphalt binder as a function of loading frequency f and temperature T in cP; and TR = temperature in Rankine scale. Then:

δ b = 90 + ( −7.3146 − 2.6162 VTS ′) ⋅ log( f ⋅ η f ,T ) (13)

+ (0.1124 + 0.2029 VTS ′) ⋅ [log ( f ⋅η f ,T )]2 Gb* = 0.0051 ⋅ f ⋅ η f ,T ⋅ [sin(δ b )]7.1542 − 0.4929 f + 0.0211 f

2

(14)

with δb = phase angle in degrees; and Gb* = dynamic shear modulus of the binder in Pa. 4

OBTAINED RESULTS AND ANALYSIS

Figures 1 to 3 show the comparison between the logarithm of the measured dynamic values and the logarithm of the predicted dynamic modulus values for the different predictive procedures used in this study corresponding to the set PAVEMENT CORES. Figures 4 to 6 show the same comparisons for the set LABORATORY SAMPLES. In these figures, the line of equality is also shown. For these comparisons, measured and predicted values have been expressed in MPa. In general and for both sets of results, the predictive procedures considered in this study were able to produce reasonable predictions of dynamic modulus Ed when compared to data from mixtures tested in laboratory. Also, the predicted values are in good agreement with those measured dynamic modulus for all the frequencies and temperatures used in this analysis. To evaluate the performance of the predictive procedures, the correlation of the measured and predicted values was assessed using goodness-of-fit statistics according to the subjective criteria proposed by Witczak et al. 2002b, and shown in Table 1. The statistics include correlation coefficient, R2 and Se/Sy (standard error of estimate values/standard deviation of measured values). Table 2 presents the evaluation of the different predictive procedures according to these criteria for the results of the PAVEMENT CORES set expressed in arithmetic and logarithmic space. Table 3 show the corresponding evaluation for the LABORATORY SAMPLES set. In general, all the analyzed predictive procedures have a good to excellent correlation to the measured dynamic modulus values and the goodness-of-fit statistics show a good to excellent performance, according to the subjective criteria used and for both sets of results considered. 279

4.5 PAVEMENT CORES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

4

4.5

log Ed measured

Figure 1.

Comparison of values using the Heukelomp and Klomp procedure.

4.5 PAVEMENT CORES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

4

4.5

log Ed measured

Figure 2.

Comparison of values using the Witczak predictive equation.

4.5 PAVEMENT CORES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

log Ed measured

Figure 3.

Comparison of values using the Hirsch model.

280

4

4.5

4.5 LABORATORY SAMPLES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

4

4.5

log Ed measured

Figure 4.

Comparison of values using the Heukelomp and Klomp procedure.

4.5 LABORATORY SAMPLES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

4

4.5

log Ed measured

Figure 5.

Comparison of values using the Witczak predictive equation.

4.5 LABORATORY SAMPLES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1.5

2

2.5

3

3.5

log Ed measured

Figure 6.

Comparison of values using the Hirsch model.

281

4

4.5

Table 1.

Table 2.

Criteria for goodness-of-fit statistical parameters.

Criteria

R2

Se/Sy

Excellent Good Fair Poor Very poor

≥0.90 0.70–0.89 0.40–0.69 0.20–0.39 ≤0.19

≤0.35 0.36–0.55 0.56–0.75 0.76–0.89 ≥0.90

Evaluation of the predictive procedures for the PAVEMENT CORES. Arithmetic space

Logarithmic space

Procedure

R2

Se/Sy

Evaluation

R2

Se/Sy

Evaluation

Heukelomp & Klomp Witczak equation Hirsch model

0.77 0.80 0.79

0.30 0.35 0.22

Good/Good Good/Excellent Good/Excellent

0.89 0.91 0.91

0.30 0.19 0.22

Good/Excellent Excellent/Excellent Excellent/Excellent

Table 3.

Evaluation of the predictive procedures for the LABORATORY SAMPLES. Arithmetic space 2

Procedure

R

Heukelomp & Klomp Witczak equation Hirsch model

0.64 0.77 0.80

Logarithmic space

Se/Sy

Evaluation

R2

Se/Sy

Evaluation

0.55 0.53 0.51

Good/Good Good/Good Good/Good

0.88 0.89 0.92

0.43 0.22 0.22

Good/Good Good/Excellent Excellent/Excellent

For the PAVEMENT CORES set, the predicted values with the Heukelomp and Klomp procedure are in very good agreement without any noticeable bias. For the Witczak equation, the predicted values are in good agreement for medium and high values of the dynamic modulus but the lower modulus values are overestimated. This observation has been reported by several researchers (Dongre et al. 2005, Schwartz 2005) indicating that the original Witczak model would over predict the lower values of dynamic modulus, which pertain to high temperature and/or low frequency. The Hirsch model predicts lower dynamic modulus values than the measured ones in the range of high modulus values. On the other hand, the model predicts higher values than the measured ones in the range of low modulus values. For the LABORATORY SAMPLES set, the three considered procedures predict slightly higher values than those measured. The LABORATORY SAMPLES used in this study were compacted using the Marshall procedure. The samples used for the development of the Witczak equation and the Hirsch model were compacted using kneading or gyratory procedures and that could be the reason for these observed differences but, in order to confirm this hypothesis, additional research could be required. Thus, the conclusions pertaining to the LABORATORY SAMPLES set should be considered with caution because the procedures have been developed to estimate the dynamic modulus of asphalt mixtures for the real conditions of in service pavements. Among the considered procedures in this study, the Heukelomp and Klomp procedure could be considered as the most promising according to the simplicity of the involved equations and the number of required parameters. Based on the obtained results for both sets of datapoints, it could be concluded that when testing results are not available, reliable first order dynamic modulus estimates for mixtures 282

4.5 PAVEMENT CORES Ed in MPa

log Ed predicted

4 3.5 3 2.5 2

Line of equality 1.5 1 .5

2

2.5

3

3.5

4

4.5

log Ed measured

Figure 7.

Comparison of values for the recalibrated Witczak equation.

typical to Argentina can be obtained using any of the three predictive procedures considered in this study. In order to correct the bias observed in the considered models, adjustments to local conditions of binder characteristics, volumetric properties and testing mode could be introduced with correction factors (Birgisson et al. 2005) or by a recalibration of the models. This recalibration could be done assuming the same functional form and adjusting the numerical coefficients using nonlinear least squares regression. As an example based on the Witczak equation, the recalibration of this model to the experimental results of the PAVEMENT CORES set results: log Ed = 5.280812 + 0.14729 p200 − 0.010276( p200 )2 − 0.114953 Va 2 ⎛ Vb ⎞ 1.791422 + 0.034422 p38 − 0.000716( p38) − 1.692467 ⎜ ⎟+ 1 − e[−−0.293418 − 1.174594(log f ) − 1.104758(logη )] ⎝ Vb + Va ⎠

(15)

The comparison between measured and predicted values using this “recalibrated” Witczak equation is shown in Figure 7. The observed bias for the original Witczak procedure has been corrected and the goodness-of-fit statistics result slightly improved compared with those obtained with the original Witczak procedure (R2 = 0.82, Se/Sy = 0.35 in arithmetic space, R2 = 0,93, Se/Sy = 0.26 in logarithmic space). 5

CONCLUSIONS

From the analysis of the obtained results, it can be concluded that in general, the predictive procedures considered in this study generate sufficiently accurate and reasonable dynamic modulus estimates adequate for use in mechanistic-empirical pavement design procedures. All the models are based on volumetric mixture properties, binder characteristics and aggregate gradation that are available from material specifications or volumetric mix design. The goodness-of-fit statistics showed that all the considered procedures perform with similar accuracy ranging between good to excellent according to the subjective criteria presented. The observed bias in the predictive dynamic modulus of some models could be corrected introducing correction factors or model recalibrations in order to take into account local conditions related to binder characteristics, asphalt mixture properties and testing procedures. When testing results are not available, reliable first order dynamic modulus estimates for asphalt mixtures typically used in Argentina can be obtained using any of the predictive procedures considered in this study. 283

Finally, the indirect tension (IDT) mode with sinusoidal loads as was used in this study was able to produce experimental dynamic modulus results that are in good agreement and comparable with those obtained with different experimental testing methods, temperatures and frequencies used for the development and the adjustment of the predictive procedures. REFERENCES Andrei, D., Witczak, M. and Mirza, W. 1999. Development of a revised predictive model for the dynamic (complex) modulus of asphalt mixtures. Design Guide for New & Rehabilitated Pavements. Appendix CC-4. NCHRP Project 1-37 A, National Research Council, Washington DC. Bari, J. and Witczak, M. 2006. Development of a new revised version of the Witczak E* predictive model for hot mix asphalt mixtures. Journal of the Association of Asphalt Paving Technologists, Vol. 75: 381–423. Birgisson, B., Sholar, G. and Roque, R. 2005. Evaluation of predicted dynamic modulus for Florida mixtures. 84th Annual Meeting of the Transportation Research Board, Paper No. 05-1309, Washington D.C. Christensen, D.W., Pellinen, T.K. and Bonaquist, R.F. 2003. Hirsch model for estimating the modulus of asphalt concrete. Journal of the Association of Asphalt Paving Technologists, Volume 72. Dongré, R., Myers L., D’Angelo J., Paugh C. and Gudimettla J. 2005. Field evaluation of Witczak and Hirsch models for predicting dynamic modulus of hot-mix asphalt. Journal of the Association of Asphalt Paving Technologists, Volume 74. Garcia G. and Thompson M. 2007. Hma dynamic modulus predictive models—a review. Research Report FHWA-ICT-07-005. Illinois Center for Transportation. University of Illinois. Urbana IL. Gschösser, F. 2008. Modeling the mechanical behaviour of asphalt mixtures. Thesis for the degree of Civil Engineer, Leopold Franzens University, Innsbruck. Heukelomp, W. and Klomp A.J.G. 1964. Road design and dynamic loading. Journal of the Association of Asphalt Paving Technologists, Vol. 33: 92–125. Kim, Y.R., Seo Y., King M. and Momen M. 2004. Dynamic modulus testing of asphalt concrete in indirect tension mode, Transportation Research Record: Journal of the Transportation Research Board 1891: 163–173. Kim, Y.R., King, M. and Momen, M. 2005. Typical Dynamic Moduli for North Carolina Asphalt Concrete Mixtures, Final Report No. FHWA/NC/2005-03 to the North Carolina Department of Transportation, North Carolina State University, Raleigh, NC. Martínez F. and Angelone S. 2006. Un modelo para la descripcion del modulo dinamico de mezclas asfalticas. II Simposio Iberoamericano de Ingenieria de Pavimentos. Trabajo N° 12. Quito. (In Spanish). NCHRP 1-37 A 2004. Mechanistic-Empirical design of new and rehabilitated pavement structures. Draft Report. Transportation Research Board, National Research Council, Washington DC. Schwartz, C.W. 2005. Evaluation of the Witczak dynamic modulus prediction model. 84th Annual Meeting of the Transportation Research Board Paper No. 05-2112, Washington DC. Van Draat, W.E.T. and Sommer P. 1965. Ein gerät zur bestimmung derdynamischen elastizitätsoduln von asphalt, Strasse und Autobahn, Number 6: 206. (In German). Van der Poel, C. 1954. A general system describing the viscoelastic properties of bitumen and its relation to routine test data, Journal of Applied Chemistry, Volume 4, Part 5, p. 221. Witczak, M.W., Kaloush, K., Pellinen, T., El-Basyouny, M. and Von Quintus, H. 2002a. Simple performance test for Superpave mix design. NCHRP Report 465. Transportation Research Board. Washington, DC. Witczak, M.W., Pellinen T. and El-Basyouny M. 2002b. Pursuit of the simple performance test for asphalt concrete fracture/cracking. Journal of the Association of Asphalt Paving Technologists, Volume 71.

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Development of wear resistant pavements using polymer modified binders R.G. Saba, L.J. Bakløkk & J. Aksnes Norwegian Public Roads Administration, Road Technology Section, Trondheim, Norway

B.O. Lerfald SINTEF Building and Infrastructure, Road and Railway Engineering, Trondheim, Norway

ABSTRACT: Pavement wear caused by studded tires continues to be a major cause of rutting in asphalt pavements in Norway and other Nordic countries. Research work conducted in the 1970s and 80s with focus on wear resistant pavements has led to the development of asphalt mixtures containing relatively large-sized hard stone materials. In recent years, however, environmental concerns with respect to noise and dust pollution have led to re-examination of these pavement surfacing materials. To mitigate these environmental problems the development of asphalt mixtures with small size aggregates containing polymer modified binders in which the mortar component plays greater role in resisting wear is being considered. For this purpose a laboratory investigation was conducted on asphalt mortars containing various polymer modified binders. The results of the laboratory investigation showed that mortars containing polymer modified binders have significantly better resistance to studded tire wear than those containing unmodified binders. This paper reports the results obtained from testing of these mortars and a mixture in the laboratory. 1

INTRODUCTION

Pavement wear caused by the use of studded tires in winter times is a major cause of rutting in asphalt pavements in Norway and other Nordic countries. The problem of pavement wear due to studded tires has been extensively studied in the 1970s and 80s. As a result of this work several measures were introduced to reduce the wear including the use of large and hard stone materials in the asphalt, development of so-called environmental studs, development of stud-free winter tires and introduction of fee for using studded tires in some urban centers. In combination, these measures have led to a substantial reduction in pavement wear resulting in an increase in service life of pavements. The proportion of vehicles driving with studded tires in winter times has also fallen to about 47% (Norwegian Public Roads Administration 2007). Despite the reduction in the use of studded tires, however, the wear caused by these tires continues to be significant. The use of asphalt mixtures with relatively large maximum aggregate size as surfacing materials has also resulted in other environmental problems; namely noise and dust (suspended particulate matter). Owing to the rough surface texture resulting from the use of large aggregate sizes, these pavements generate significantly more noise compared to asphalt pavements with lower maximum aggregate sizes. Suspended matter from road traffic is composed of particles resulting from wear of the pavement and vehicles and emission from the vehicles. Measurements show that the mineral component in the dust is about 70–80% in the winter, as compared to only 15–25% in the summer (Baklokk et al. 1997). A study from 2005 showed that 87% of the dust downfall collected in the period March–May close to a heavily trafficked road in Trondheim, Norway was comprised of inorganic materials (Snilsberg et al. 2006). This shows, as one would expect, that the major portion of the suspended particulate matter coming from the road traffic consists of mineral matter originating from the wear of stone materials 285

used in asphalt pavements. The particles coming from wear of hard stone materials tend to be small in size with aerodynamic diameter of less than 10 μm. These particles can be inhaled and depending on the quantity and mineral type can have potentially detrimental health effects. During the winter the contribution of road traffic to suspended matter in the air in the urban areas can be more than 90% (Berthelsen et al. 2005). This is because the emission from road traffic takes place close to the ground where people live, travel and stay, and emitted suspended matter will be whirled up by vehicles and wind over and over again. The problem of dust emission from pavement wear is even more severe in tunnels. The Norwegian Public Roads Administration spends millions of dollars every year to maintain and run cleaning equipment in the tunnels. Thus development of wear resistant pavements for use in the tunnels can yield significant financial benefit. The objective of this study is to investigate the resistance to wear of asphalt mortar containing polymer modified binders with a view of developing wear resistant thin pavements that can be used in tunnels and on roads where there is a need for reduction of dust emission. The study aims to develop a filler-rich asphalt mixture with relatively high binder content. The hypothesis of this study is that, with reduced maximum aggregate size, the mortar plays greater role in resisting wear and the use of polymer modified binders in this kind of mixtures will lead to highly flexible pavements with rubber-like properties such that the energy coming from the action of studded tires will be absorbed in elastic deflection of the material. In this regard the elastic recovery of the binder is considered to be very important and an attempt is made to see if this property of the binder correlates with the measured resistance to wear. This paper reports the results form testing of binder properties and the resistance to wear of asphalt mortar in the laboratory.

2

EFFECT OF POLYMER MODIFICATION ON PERFORMANCE OF ASPHALT MIXTURES

The purpose of modifying bituminous binders with polymers has been to reduce the temperature susceptibility of the binders and thereby produce asphalt mixture with satisfactory resistance to cracking and to permanent deformation (rutting). There are three main categories of polymers used for modification of bituminous binders: thermoplastic elastomers, plastomers and reactive polymers. Of these three categories it is the thermoplastic elastomers that are commonly used for modification of binders for road construction purposes. Elastomers impart elastic properties to the binders. In essence, the modification of binders with elastomers increases the binder’s capacity for elastic recovery after loading and unloading over a wider temperature span. The most commonly used elastomer for bitumen modification is the SBS (styrene-butadiene-styrene) copolymer. Plastomers and reactive polymers, on the contrary, impart high rigidity to the binders and strongly reduce deformation under load. The beneficial effects of polymer modification on the performance of asphalt materials have been reported by many researchers. Yildirim (2005) published review of research that has been conducted on polymer modified binders in the last three decades. The vast majority of the research work reviewed indicated that pavements with polymer modification exhibited greater resistance to rutting and thermal cracking, and decreased fatigue damage and stripping. Polymer modified binders have successfully been used at intersections of busy streets, airports, vehicle weigh stations, and race tracks (Yildirim 2005). Several other authors including Uddin (2003), Lu (1996), Bouldin & Collins (1992), and Newcomb et al. (1992) have reported results from studies that showed that polymer modification of binders significantly improved the performance of asphalt mixtures containing those binders. Most of the research that have been conducted on the use of polymer modified binders for paving applications have concentrated on evaluating the performance with regard to rutting, fatigue cracking, and low temperature cracking. It is thus difficult to find a systematic study that has evaluated the effect of polymer modification on the resistance of asphalt mixtures to wear due to studded tires. Few of the studies that attempted to evaluate the resistance to wear of asphalt mixtures containing modified binders have given mixed results. 286

A study conducted at the Norwegian University of Science and Technology in 1989 compared the resistance to wear of asphalt mortar containing various types of modified binders in a Troger test (Rønnes 1989). The mortars were produced by taking aggregate material less than 4 mm in size from gradation curves (specifications) for asphalt concrete, stone mastic asphalt, topeka, and støpeasfalt (a filler-rich asphalt mixture similar to Gussasphalt) and mixing with binders in the laboratory. The study also evaluated the effect of the polymer content of the modified binders. The results of the test showed that mortars containing polymer modified binders had significantly better resistance to wear compared to unmodified binders. The study also concluded that increasing polymer content gave increasing resistance to wear up to a level that produces continuous polymer phase in the binder, but increasing beyond this level gave little improvement in the resistance. Jacobson (1995) reported an extensive study conducted in Sweden on wear resistance of bituminous mixes. The study involved testing of asphalt pavement slabs produced in the laboratory and inserted in real road pavements as well as testing of those slabs in a pavement testing machine (an accelerated pavement testing device). Some of the slabs were produced using polymer modified binders although little information was given on the type and content of the polymer. The results showed that, for stone mastic asphalt mixes, the polymer modified binder had no appreciable effect on the wear resistance. However, for dense graded asphalt concrete, the result was different; the wear was 20–40% less for sections containing modified binders than the reference section containing the conventional B85 binder. Uthus (1990) reported results of a field research conducted in the city of Trondheim, Norway. The research work included constructing and monitoring test sections containing a polymer modified binder and a reference section. Based on field measurements after two winters, the author concluded that the sections containing polymer modified binder had better resistance to wear than the reference section. In a state-of-the-art report on modification of binders prepared for the Norwegian chapter of the Nordic Road Association group 33, Ruud (1985) reported that there were several test sections in Norway containing modified binders that were built to study the effect of modification on performance, particularly resistance to wear. Based on short time observation (mostly one winter), the author concluded that some of the sections containing modified binders showed better resistance to wear than the reference section, while others did not show any appreciable difference from the reference section. Unfortunately, those sections were not monitored for longer periods to draw firm conclusions. 3

MATERIALS AND TESTING

In this study asphalt mortars containing polymer modified binders were tested to determine their resistance to wear. The mortar material is basically filler- rich asphalt mix with maximum aggregate size of 2 mm known as støpeasfalt (in Norwegian). This material is primarily used as a water tight membrane on bridges. In addition an ordinary asphalt concrete with maximum aggregate size of 11 mm (Ab 11 in Norwegian specification) containing unmodified B160/180 binder was tested for comparison purposes. 3.1 Binder testing Six SBS modified binders were supplied by three suppliers. In addition, the unmodified B70/100 was used as a reference. The tests that were conducted on the binders and the standard procedures are listed in Table 1. Binder test results are discussed under section 4 of this paper. 3.2 Filler The density and particle size distribution for the limestone filler material used in this study was determined using respectively AccuPyc 1330 pycnometer and Coutler LS Particle Size analyzer. Figure 1 shows particle size distribution for the filler. 287

Table 1.

Procedures for binder testing.

Condition

Standard

Test

Original binder

EN 1426 EN 1427 EN 13398 14.5133 (Norwegian handbook 014) EN 12607-1

Penetration Softening point Elastic recovery Viscosity (using Brookfield viscometer) Determination of the resistance to hardening Penetration Softening point Elastic recovery Aging BBR

After RTFOT

EN 1426 EN 1427 EN 13398 EN 14769 EN 14771

After PAV

Figure 1.

Remark

Viscosity determined at 160, 180 and 200οC

PAV aging at 100οC S and m values at −24οC

Particle size distribution for the filler material.

100,0 90,0 80,0

% Passing

70,0

mix

60,0 50,0

min

40,0

max

30,0 20,0 10,0 0,0 0,001

0,01

0,1

1

Sieve size (mm)

Figure 2.

Aggregate gradation curve.

288

10

100

Figure 3.

The Troger apparatus.

3.3 The mixture The aggregate gradation curve for the mixture as well as the specification limits for the gradation (maximum and minimum) is shown in Figure 2. The binder content was 12.5% by weight. Test specimens were compacted using a vibrating table. Initial specimens with height of 12–13 cm and diameter of 10 cm were produced. These specimens were cut to produce several test specimens with height of 3 cm. Three specimens were tested for each binder type. The testing for the resistance to wear was conducted both in wet and dry conditions. 3.4 Testing the resistance to wear The specimens were tested for their resistance to wear in the Troger apparatus. The Troger test is described by EN 1871:2000 Annex K. This method was originally designed for testing abrasion of road marking materials, but has also been used to determine the resistance of asphalt pavements to wear caused by studded tires. The apparatus is shown in Figure 3. The test specimen (height 30 mm and diameter 100 mm) is mounted on an eccentric rotating table (30 rotations per minute (RPM)). Steel needles (52 needles with 2 mm in diameter) hammer the sample driven by a compressed air gun (5 Bar), simulating the hammering and scratching influence of the tire studs. In this study the wet specimens were tested at 0ºC and the dry specimens were tested at –5°C. The wear, W (cm3), is expressed as: W=

(Mi − M s ) ρ

(1)

where Mi = mass of original test specimen (g); Ms = mass of test specimen after testing (g); and ρ = density of tested material (g/cm3). Research conducted earlier at the Swedish Road and Transport Research Institute has shown that the result of Troger test correlates with wear due to studded tires measured on the road with correlation coefficient, R2, of 0.68–0.99 (Jacobson 1995). 4

RESULTS AND DISCUSSION

This section presents results from the laboratory testing of the binders and the mortars. Results of the binder testing are summarized in Tables 2 and 3. The binder suppliers are numbered 1 to 3 and the different binders provided by one supplier are identified using number indices 1-1, 1-2, 2-1, 2-3, etc. Figure 4 shows the elastic recovery before and after RTFOT. As would be expected there is slight drop in elastic recovery values after the short term aging. The elastic recovery values 289

Table 2.

Test results for original binder. Viscosity (CPS) at

Binder

Penetration at 25oC

Elastic recovery at 10oC (%)

160oC

180oC

200oC

1-1 1-2 2-1 2-2 2-3 3-1 3-2 B70/100

56 60 82 88 34 68 97 95

78 82 90 94 Broke at 119 mm 65 79 14

314 452 750 745 262 354 436 111

138 232 384 392 125 175 234 –

81 132 202 220 66 92 126 –

Table 3.

Test results for aged binder. RTFOT

PAV

Binder

Weight loss (%)

Penetration at 25oC

Elastic recovery at 10oC

S value

m value

1-1 1-2 2-1 2-2 2-3 3-1 3-2 B70/100

−0.08 −0.04 0.03 0.03 −0.02 −0.02 −0.06 0.09

38 37 61 74 21 46 76 55

69 71 85 88 Broke at 61 mm 62 75 −

608 514 437 410 704 511 268 583

0.208 0.194 0.221 0.232 0.180 0.253 0.300 0.191

100

Elastic recovery (%) at 10ºC

90 80 70 60 Elastic recovery, original binder

50 40

Elastic recovery, after RTFOT

30 20 10

00

2 3-

B7 0/ 1

3 2-

2 2-

21

2 1-

1-

1

0

Binder type

Figure 4.

Elastic recovery before and after RTFOT.

for modified binders after RTFOT however are still by far higher than that of the unmodified binder in its original state. Figures 5 and 6 show the S and m values, respectively, from the bending beam rheometer testing. These values, developed under the Strategic Highway Research Program (SHRP), were meant to be used to evaluate the low temperature properties of unmodified binders. 290

800 700 600

S-value

500 S-value

400 300 200 100 0 1-1

1-2

2-1

2-2

2-3

3-2

B70/100

Binder type

Figure 5.

The S-values at –24oC.

0,35 0,3

m-value

0,25 0,2 m-value 0,15 0,1 0,05 0 1-1

1-2

2-1

2-2

2-3

3-2

B70/100

Binder type

Figure 6.

The m-values at –24oC.

14 12

Wear (cm3)

10 8

Wet Dry

6 4 2 0 1-1

1-2

2-1

2-2

2-3

3-2

B70/100

Binder type

Figure 7.

Results of the Troger test.

The test procedures that were developed for unmodified binders, however, have been shown to be not suitable for modified binders (Bahia et al. 2001). In this study, this test was conducted to get an idea of the low temperature performance of the modified binders. As can be seen from Figure 5, binders 1-1 and 2-3 have S value, which are greater than that of the reference binder indicating that they may not have the required flexibility at low 291

13

12

Wear (cm3)

11

10

Elastic Recovery 9 R2 = 0,8311 8 7

6 75

80

85

90

95

Elastic recovery (%)

Figure 8.

Correlation between wear and elastic recovery.

14 12

Wear(cm3), wet

10 8 Viscosity - Troger 6 4 2 0 0,00

100,00 200,00 300,00 400,00 500,00 600,00 700,00 800,00 Viscosity at 160°C (CPS)

Figure 9.

Relationship between binder viscosity at 160oC and wear.

14 12

Wear (cm3), wet

10 8 Penetration - Troger 6 4 2 0 0,00

20,00

40,00

60,00

80,00

Penetration at 25°C

Figure 10.

Relationship between penetration and wear.

292

100,00

120,00

14 12

Wear (cm3)

10 8

Wear - wet Wear - dry

6 4 2 0 1-1

1-2

2-1

2-2

2-3

3-2

B70/100

Ab 11

Material

Figure 11.

Comparison of the resistance to wear of mortars and asphalt concrete.

temperatures. It is only the binder 3-2 that fulfills the Superpave requirement of maximum S value of 300 MPa at this particular temperature (–24oC). With regard to the m-values, all the modified binders with the exception of binder 2-3 have m-vales, which are greater than that of the reference binder. However it is again only the binder 3-2 that fulfills the Superpave requirement for minimum m value of 0.3 at this temperature. Results form Troger test (resistance to wear) are shown in Figure 7. As can be seen from Figure 7, the mortar containing binder 2-1 has the best resistance to wear closely followed by those containing binders 2-2 and 3-2. Compared to the mortar containing the commonly used ordinary binder (B70/100), all of the mortar samples containing modified binders with exception of binder 2-3 have significantly better resistance to wear. Binder 2-3, which was shown to be relatively more stiff/brittle by the elastic recovery test, showed more or less the same level of resistance to wear as the unmodified binder. Figure 8 shows the plot of the wear measured in the Troger test against the elastic recovery values for the modified binders (the elastic recovery value of the unmodified binder was excluded because of the large difference from that for modified binders). It appears that the elastic recovery correlates well with the measured resistance to wear (R2 = 0.83); the higher the elastic recovery the lower the wear (the Troger vale). On the other hand viscosity and penetration values of the binders correlate poorly with the resistance to wear as measured in the Troger test. This is illustrated in Figures 9 and 10.This indicates that viscosity and penetration might not be the suitable parameters to evaluate the binder’s contribution to the resistance to wear. Figure 11 shows the measured wear for the asphalt concrete mixture as well as for the mortars. One can see from the figure that mortars containing modified binders 2-1, 2-2, and 3-2 have better resistance to wear than the asphalt concrete while the mortars containing binders 1-1 and 1-2 have nearly the same resistance to wear as the asphalt concrete in the wet condition but better resistance in the dry condition. This indicates that, with proper choice of binders, one can produce asphalt mixtures with smaller maximum aggregate size, which have equal or better resistance to wear than the conventional mixtures. However, more extensive test on the various mixture types should be conducted to be able to draw firm conclusion. 5

CONCLUSIONS

Results of the tests conducted in this study showed that mortars containing polymer modified binders have significantly better resistance to studded tire wear than a mortar containing unmodified binder. The degree of the improvement however varied depending on the type of the modified binder. It appears that the elastic recovery of the binder correlates well with the resistance to wear indicating that the flexibility of the material may play greater role in resisting 293

studded tire wear. Comparison of the wear resistance of mortars containing polymer modified binders and that of asphalt concrete showed that some of the mortars have better resistance than the asphalt concrete. It might thus be possible to develop asphalt materials with smaller maximum aggregate size that are rich in mortar and that have better resistance to studded tire wear by using appropriate polymer modified binders. Such materials may benefit the environment in reducing both the suspended particulate matter originating from pavement wear and noise. It is recommended to do more extensive testing of mixtures containing various modified binders and to investigate the frictional and deformation properties of asphalt mixtures with small maximum aggregate size. The performance of the materials should also be investigated in the field by building and monitoring field test sections to check if the results obtained in the laboratory can be replicated in the field. ACKNOWLEDGEMENT The authors would like to thank personnel at the Road Laboratory of SINTEF building and infrastructure and the Norwegian University of Science and Technology who conducted the tests reported in this paper. REFERENCES Bahia, H.U., Hanson, D.I., Zeng, M., Zhai, H., Khatri, M.A. & Anderson, R.M. 2001. Characterization of modified asphalt binders in Superpave mix design. National Cooperative Highway Research Program, NCHRP report 459. Bakløkk, L., Horvli, I. & Myran, T. 1997. Studded tire wear and dust development: a literature review; STF22 F97509 (in Norwegian). Trondheim: SINTEF Civil and environmental engineering, Road engineering section. Bakløkk, L. 1997. Studded tire wear on the road network: development trends; STF22 F97516 (in Norwegian). Trondheim: SINTEF Civil and environmental engineering, Road engineering section. Berthelsen, B.O., Berg, T., Martinsen, S., Vodahl, S., Blakstad, F. & Obereque-Cardenas, M. 2005. Better air quality in Trondheim—Analysis of suggested measures for better local air quality (in Norwegian). Trondheim: Trondheim city council. Bouldin, M.G. & Collins, J.H. 1992. Influence of binder rheology on rut resistance of polymer modified and unmodified hot mix asphalt. In Wardlaw, K.R. & Shuler, S. (editors), Polymer modified asphalt binders; ASTM STP 1108. Philadelphia: ASTM. Jacobson, T. 1995. Study of the wear resistance of bituminous mixes to studded tires—Tests with slabs of bituminous mixes inserted in roads and in the VTI’s road simulator; VTI report no. 245. Linkoping: Swedish Road and Transport Research Institute. Lu, X. 1996. Fundamental studies on styrene-butadiene-styrene polymer modified road bitumens; Licentiate thesis. Stockholm: Division of highway engineering, Royal Institute of Technology. Newcomb, D.E., Stroup-Gardiner, M. & Epps, J.A. 1992. Laboratory and field studies of polyolefin and latex modifiers for asphalt mixtures. In Wardlaw, K.R. and Shuler, S. (editors), Polymer modified asphalt binders; ASTM STP 1108. Philadelphia: ASTM. Norwegian Public Roads Administration. 2005. Handbook 014 Laboratory Test (in Norwegian). Oslo: Norwegian Public Roads Administration. Norwegian Public Roads Administration. 2007. Condition survey 2007—The use of studded tires (in Norwegian). Oslo: Road and Traffic Department, Section for traffic safety. Ruud, O.E. 1985. Modification of binders: State-of-the-art report from Norway (in Norwegian). Oslo: Nordic Road Association , Group 33. Rønnes, E.1989. Wear resistance of polymer modified asphalt; Masters thesis (in Norwegian). Trondheim: Norwegian University of Science and technology, Department of road and railway engineering. Snilsberg, B., Myran, T. & Saba, R.G. 2006. Analysis of dust emission from pavement abrasion in Trondheim, Norway, Proceedings of the TRA (Transportation Research Arena) Conference, Götenburg, 12-15 June 2006. Uddin, W. 2003. Viscoelastic characterization of polymer modified asphalt binders for pavement applications. Applied Rheology vol. 13, no. 4: 191–199. Uthus, N.S. 1990. ELF test pavements 1987/1988; SINTEF report STF61 F90001 (in Norwegian). Trondheim: SINTEF. Yildirim, Y. 2005. Polymer modified asphalt binders. Construction and building materials vol. 21.

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Permanent deformation evaluation of Idaho Superpave mixes using the gyratory stability F. Bayomy & A. Abu Abdo Department of Civil Engineering, University of Idaho, Moscow, Idaho, USA

M.J. Santi Idaho Transportation Department, Boise, Idaho, USA

ABSTRACT: With the full implementation of Superpave mix design in the State of Idaho, a performance parameter, referred to as the Gyratory Stability, has been developed. It is calculated from the accumulated shear energy in the mix during compaction. Results of the Gyratory Stability (GS) of thirteen tested mixes from the lab and field compared well with various performance indicators. Performance evaluation of these mixes was conducted using Asphalt Pavement Analyzer (APA), Dynamic Modulus (E*) and the Flow Number (FN). The GS results showed good correlation with rut-depth measured in APA and with E*, phase angle and the FN parameters measured in the Superpave Performance Tester (SPT). The results also showed that GS was more sensitive to the changes in mix design parameters. Overall, the results indicate that GS has the potential to be used as a screening tool for HotMix Asphalt design and as a quality control indicator onsite. 1

INTRODUCTION

Significant research has been conducted since the introduction of the Superpave mix design, in order to supplement this design methodology with performance tests (Witczak et al. 2002). These performance tests are extremely important to allow design engineers to evaluate Hot Mix Asphalt (HMA) during the mix design stage. In addition to these performance tests, there has been an interest in using the Superpave gyratory compaction data to evaluate mixes based on the resistance of the aggregate structure to the applied loads (DeSombre 1998, Mallick 1999, Guler et al. 2000, Andersen et al. 2002, Bayomy et al. 2002, Bahia et al. 2003a, b & Dessouky et al. 2004). It is not intended to replace performance tests, but rather to identify mixes with weak aggregate structures prior to more involved performance testing. It can also be used in the field to rapidly detect any changes in the mix that would adversely affect the aggregate structure and mix performance. This approach is based on internal stresses, such as shear stress, generated in the sample due to compaction. Therefore, several approaches have been proposed to develop experimental tools and analysis methods to measure the shear stress during compaction and relate them to stability. McRea (1962 & 1965) proposed an equation to determine the shear stress in HMA during compaction in the gyratory machine. This equation was developed based on equilibrium analysis of HMA and the compaction mold. Subsequently, it was used to predict the mix stability and performance by several researchers (e.g. Kumar & Goetz 1974, Sigurjonsson & Ruth 1990, Ruth et al. 1991& Mallick 1999). Butcher (1998) used the same equation with data from Servopac Superpave Gyratory Compactor and showed that the calculated shear stress is sensitive to changes in binder type. A recent study by De Sombre et al. (1998) estimated the shear stress and the compaction energy in asphalt mixes by using the Finland gyratory compactor. Guler et al. (2000) equipped the Superpave gyratory compactor with a load cell assembly referred to as the Pressure Distribution Analyzer (PDA) to measure the forces applied at the bottom of a specimen 295

during compaction. These forces were used in an equation to calculate the developed shear stress in the compacted sample. Research conducted under NCHRP 9-16 project (Andersen et al. 2002) proposed the use of the number of gyrations at maximum stress ratio in order to group laboratory mixes with good, fair, and poor expected rutting resistance. The parameter is directly obtainable from Superpave Gyratory Compacter (SGC) capable of measuring shear stress during compaction or by PDA (Guler et al. 2000 & Stackston et al. 2002). Bayomy et al. (2002) and Dessouky et al. (2004) developed another approach to estimate the shear stress developed in the asphalt mix due to compaction in an SGC equipped with force measuring cells. Using the response of the mix to the applied forces in the SGC and the mix deformation during compaction, the energy utilized to develop contacts between aggregates was quantified using the Contact Energy Index (CEI). The CEI reflects the stability of the mix, by relating to the frictional forces among its aggregate particles. Their studies showed that CEI is sensitive to variation of mix constituents such as aggregate characteristics, gradation, and binder content. Later, Bayomy & Abu Abdo (2007) introduced the Gyratory Stability (GS), which is based on CEI to facilitate the determination and implementation of such index. 2

OBJECTIVES AND SCOPE

The main objective of this study was to evaluate the potential of using the Gyratory Stability (GS) as a measure of aggregate structure stability in Superpave mixes. It has been achieved by addressing the following issues: • Investigating whether GS relates to the permanent deformation as measured in the asphalt pavement analyzer (APA), • Investigating whether GS relates to rutting tendencies determined by the Dynamic Modulus and Flow Number Tests, and • Determining whether GS may be used as screening tool at design stage and as a quality control criterion in the field.

3

THE GYRATORY STABILITY (GS)

Since this paper focuses on GS as a candidate indicator for mix stability, which can be augmented with the Superpave mix design, a brief discussion of GS development is presented. Based on studies by Bayomy et al. (2002) and Dessouky et al. (2004), the CEI equation and an algorithm to determine its value from compaction data were developed. CEI can be determined using Equation 1: GEI =

NG 2

∑ Si Δdi

(1)

NG 1

where Si is shear force in kN at half a sample height, di is the change in height (mm) at each number of gyrations, and NG1 and NG2 are two defined starting and ending number of gyrations on the compaction curve. The procedure for calculating Si can be found in Bayomy et al. (2002). In calculating the CEI, the compaction curve is divided into two parts as shown in Figure 1. The first one (part A) has a steep change in percent air voids with an increase in number of gyrations. In this part, most of the applied energy is used in inducing volumetric deformation (reduction in percent air voids), and aggregates do not experience significant amount of shearing forces. In the second part (part B), however, aggregates experience significant shear deformation and most of the energy is consumed in adjusting particle orientation and increasing aggregates contacts, which will result in an increase in mix shear strength. Therefore, the energy calculations for assessing the mix stability should focus on part B of the compaction curve. 296

Figure 1.

Typical compaction curve (after Bayomy et al. 2002).

The number of gyration NG1 that defines the beginning of part B of the compaction curve (Figure 1) is associated with a decrease in percent air void. Mathematically, this means that the third derivative of the compaction curve function should be zero. For practical purposes, it was considered that NG1 is where the difference in the change in the slope of the compaction curve was less than 0.001 (i.e., where the rate of the change of the slope is zero). NG2 is where the compaction curve flattens and no change in height is achieved, and therefore, it is selected at maximum possible for practical compaction. It was determined to be equal to 250 gyrations for the CEI to capture the differences among mixes prepared using aggregates with different properties such ource, shape and gradation. When the mix reaches its maximum stability any excess in induced compaction energy will be dissipated in particle sliding without increase in particles interlocks, and consequently no more strength is developed. This state will be manifested by no change in mix air voids, a state known as “refusal” in mix compaction, which means that the mix resists further compaction. Therefore, the energy calculations for assessing the mix stability should be focused only on part B of the compaction curve. For production samples where the compaction stops at N-design, NG2 is considered equal to N-design (Bayomy & Abu Abdo 2007). Since N-design is smaller than N-max, the calculated CEI to NG2 = N-design would be smaller than that calculated to N-max. Commonly, production samples are typically produced with number of gyrations equals N-design, the value of CEI for the energy product summed between NG1 and N-design is referred to as the Gyratory Stability (GS). GS is determined by Equation 2 as: GS =

Nde s ign

∑

Si Δdi

(2)

NG 1

4

ASPHALT MIXTURES

Idaho Transportation Department (ITD) recently started the full implementation of Superpave mix deign. With the help of ITD, raw materials for two different mixes were procured from two projects. These two mixes (L1 and L2) have different aggregate types and gradation. L1 and L2 were used as a base for the other nine different mixes by modifying the binder content and grade. In addition, four different hot plant-mixed mixes (F1, F2, F3 & F4) were obtained from different existing projects. Onsite compaction data for a fifth field mix (F5) were obtained and retrieved data was used for onsite quality control purposes. Details for these mixes are listed in Table 1. 297

Table 1.

Properties of tested mixes.

Mix label*

Binder grade

Binder content, %

L1-1 L1-2 L1-3 L1-4 L2-1 L2-2 L2-3 L2-4 L2-5 F1 F2 F3 F4 F5

PG 64-34 PG 64-34 PG 64-34 PG 64-34 PG 64-28 PG 6 4-28 PG 64-28 PG 64-22 PG 64-34 PG 70-28 PG 70-28 PG 70-28 PG 70-28 PG 70-28

5.0 5.5 6.0 6.5 4.9 5.9 6.9 5.9 5.9 4.9 5.4 5.9 6.2 5.9

*

L and F designations indicate Lab and Field mixes, respectively.

5

SAMPLE PREPARATION AND TEST SETUP

5.1 Gyratory Stability (GS) Six duplicate samples were used to determine the Gyratory Stability. Samples were compacted using the Servopac SGC to a number of gyrations to produce specimens with 4% air voids. The termination of compaction depended on specified height of 115 mm for the Optimum asphalt content for both mixes, the number of gyrations coincided, as expected, with around mix design set N-design. 5.2 Asphalt Pavement Analyzer (APA) Test The APA, which is the new generation of the Georgia Loaded-Wheel Tester, was developed to evaluate the HMA resistance to permanent deformation (Choubane et al. 2000 & Martin & Park 2003). Three samples were compacted to achieve 4% final air voids and to a fixed height of 150 mm. The test was conducted at the upper temperature range of the binder grade (i.e., 64°C for PG 64-28 and 70°C for PG 70-28). 5.3 Dynamic Modulus (E*) Test The Dynamic Modulus Test (AASHTO TP 62-03) consists of applying a uniaxial sinusoidal compressive stress to an unconfined HMA cylindrical test specimen and measure the corresponding strain using three LVDTs mounted on the middle of the specimen. The Dynamic Modulus Test was conducted under a series of temperatures (4.4, 21.1, 37.8 and 54.4°C) and loading frequencies (0.1, 1, 5, 10 and 25 Hz) at each temperature. Samples used in the Dynamic Modulus and Flow Number tests were compacted to achieve 175 mm high specimens with a total 9% air voids. Then samples were cored and sawed to obtain 100 mm diameter and 150 mm high samples with 7% air voids. (E*/sin ϕ) parameter at loading frequency of 5 Hz at temperatures of 54.4 and 37.8°C was used as a permanent deformation (rutting) indicator, where ϕ is the phase angle which represents the times lag between the application of load and the material respond. 5.4 Flow Number (FN ) Test The Flow Number Test is conducted using a loading cycle of 1.0 second in duration, which consists of 0.1 second haversine load followed by 0.9 second rest at a testing temperature of 54.4°C. This test utilizes the same samples used in the Dynamic Modulus Test. 298

The above mentioned tests were conducted on both lab and field mixes. Lab mixes were mixed and compacted in the laboratory. Field mixes were hot plant-mixed mixes obtained from behind the paver as per ITD specification. These mixes were compacted in the laboratory to achieve similar air voids as the lab mixes. 6

ANALYSIS OF RESULTS

Gyratory Stability (GS) values were determined for both mixes at different asphalt contents. As per Superpave Mix Design, these mixes should perform best at the optimum asphalt content, at which the air voids of the compacted specimen at N-design is four percent. As shown in Figure 2, both mixes yielded the highest GS at optimum asphalt content. In addition, when comparing the two mixes’ GS values, L2 mix yielded higher GS values, therefore it is expected that L2 mix will perform better than L1 mix under the same loading conditions. GS sensitivity to binder type (PG grade) was evaluated for L2 mix (see Figure 3). The results showed that GS is not very sensitive to the changes in binder grade. These findings matched the results from previous studies (Bayomy et al. 2002 & Dessouky et al. 2004). This can be explained by understanding that at compacting temperatures, all binder grades have the same viscosity, thus difference in grade does not influence the performance of the mix, which makes GS more of an indicator of aggregates structure stability. GS results were compared to the APA test results. Figure 4 shows that a very good correlation between GS and permanent deformation measured by APA existed (R-square of 0.58 for lab mixes and 0.84 for field mixes). Depending on the upper temperature of the PG grade (64 & 70°C) a correlation should exist between the two parameters. This relation shows that the higher GS is the lower is the permanent deformation predicted by APA.

25 L1

GS, kN.m

20

L2

15

10

5

0 4

4.5

5

5.5

6

6.5

7

AC%

Figure 2.

Superpave Mixes GS Results at different asphalt contents.

25

GS, kN.m

20 15 10 5 0 PG 64-22

PG 64-28 (Opt AC%) Binder

Figure 3.

Sensitivity of Gyratory Stability to different PGs (Mix 2).

299

PG 64-34

7.5

Lab Mixes

25

Field Mixes

GS, kN.m

20

15

R² = 0.58 R² = 0.84

10

5

0 0

2

4

6

8

10

Rut Depth, mm

Figure 4.

Relationship between Gyratory Stability and APA test results.

25

R² = 0.76

GS, kN.m

20

15

R² = 0.72 10

Lab Mixes

5

Field Mixes 0 0

100

200

300

400

500

600

700

800

900

a) E*/sin Φ @ 54.4°C, MPa

25

R² = 0.65

GS, kN.m

20

15

R² = 0.59 10 Lab Mixes

5

Field Mixes 0 0

1000

2000

3000

4000

5000

b) E*/sin Φ @ 37.8°C, MPa

Figure 5.

Relationship between Gyratory Stability and E*/sin ϕ.

Witczak et al. (2002) recommended the use of E*/sin ϕ at 54.4°C or at 37.8°C parameter as a rutting indicator for asphalt mixes. The higher the value of this parameter at a given temperature, the better resistance to rutting the mix exhibits. GS was compared to E*/sin ϕ at both temperatures. Figure 5 shows that a very good relation exists between GS and E*/sin ϕ at 54.4°C with an R-square of 0.76 and 0.72 for lab and field mixes, respectively and an R-square of 0.65 and 0.59 at 37.8°C. Then, GS was compared to the Flow Number (FN) Test results. Similar to E*/sin ϕ, it is believed that the higher FN is the better performance the asphalt mix will be. Although it has been observed that the results of this test vary much 300

25

R² = 0.64

GS, kN.m

20

15

R² = 0.96

10 Lab Mixes 5

Field Mixes

0 0

2000

4000

6000

8000

10000

12000

Flow Number, FN

19

6.1%

18

6.0%

17

5.9%

16

5.8%

15

5.7%

14

5.6%

AC%

Relationship between Gyratory Stability and Flow Number 54.4°C.

GS, kN.m

Figure 6.

5.5%

13 12

GS, kN.m

5.4%

11

AC%

5.3% 5.2%

10 624 625 626 627 628 629 630 631 632 633 634 635 636 Samples ID

a) Gyratory Stability versus Asphalt Content 19

7%

18

6% 5%

16

4%

15 14

AV%

GS, kN.m

17

3%

13

GS, kN.m

12

AV%

11

2% 1% 0%

10 624 625 626 627 628 629 630 631 632 633 634 635 636 Samples ID

b) Gyratory Stability versus Air Voids

Figure 7.

Gyratory Stability versus Air Voids and asphalt content for field mix 5.

within the same mix, results show (Figure 6) a relatively good correlation between GS and FN for lab mixes with an R-square of 0.64 but a higher correlation for field mixes (R-square of 0.96). Overall, results of Field mixes showed better GS correlations with other parameters than Lab mixes, it is not clear why, but it is speculated that results varied since Field mixes have different set of properties than Lab mixes. Commonly, air voids percentage is used to accept/reject filed mix batches, but it might not be enough. To determine if GS can be used also as an onsite quality control tool, compaction data for 26 samples (F5) from different mile-posts were retrieved from an existing project. These samples’ properties such as asphalt content and aggregates gradation varied from the 301

original mix design as measured by air voids. It is observed that GS captures these variations as shown in Figure 7-a & b. GS followed similar trend as the asphalt content and air voids changes to an extent, and since it measures the stability of the asphalt mix, it is preferable to use also GS as a quality control measurement. 7

SUMMARY AND CONCLUSIONS

Based on the results presented, the following observations and conclusions are made: 1. Gyratory Stability (GS) parameter is a simple, quick, and reproducible parameter to measure the mix stability from the Superpave Gyratory Compactor (SGC) data during mix compaction in the lab. GS was found to be sensitive to asphalt content changes but not to asphalt binder grade. The less sensitivity of GS to binder grade may be attributed to the unified binder viscosity of various binders at its designated mix and compaction temperatures. 2. GS determined at optimum asphalt content was the highest for L1 and L2 Mixes. Further, it was found that GS ranked L2 mix above L1 mix. Therefore, it expected that L2 mix will perform better than L1 mix under the same loading conditions. 3. GS correlated inversely with the APA test results, where for mixes with high GS, they showed small rut-depth results. Correlations between GS and rut depth measured by APA were developed, and showed R-square of 0.58 and 0.84 for lab and field mixes, respectively. 4. E*/sin ϕ at temperatures 54.4°C and 37.8°C correlated with GS with an R-Square of 0.76 and 0.65 respectively for lab mixes and with R-square of 0.72 and 0.59 for field mixes. 5. GS correlated with the Flow Number test results with R-square equal to 0.64 for lab mixes, but a higher correlation for field mixes (R-square of 0.96). 6. It is postulated that the GS has the potential to be used as a screening tool for HMA design, especially to decide upon the aggregate structure during the mix design stage. 7. Due to the simplicity and ease of the determination of GS, it can be used not only at the mix design level, before further extensive testing is made, but also during production for quality control purposes.

ACKNOWLEDGEMENT This research was funded by the Idaho Transportation Department under a contract with the National Institute of Advanced Transportation Technology (NIATT) at the University of Idaho (project number KLK482). Support of these organizations is greatly appreciated. The research team would like to thank Mr. Monte Tish of ITD, Mr. Josh Smith Poe Asphalt Paving Inc., Mr. Dave Zhai of Idaho Asphalt Supply and Debco Construction Co., for their help and providing necessary materials for the study. REFERENCES Anderson, R., Tuner, P., Peterson, R. & Mallick, R. 2002. Relationship of Superpave Gyratory Compaction Properties to HMA Rutting Behavior. NCHRP Report 478, Washington D.C.: TRB. Bahia, H., Friemel, T., Peterson, P., Russell, J. & Poehnelt, B. 2003a. Optimization of Contractibility and Resistance to Traffic: A New Design Approach for HMA Using the Superpave Compactor. Journal of Association of Asphalt Paving Technologists, Vol. 67: 189–225. Bahia, H., Masad, E., Stackston, A., Dessouky, S. & Bayomy, F. 2003b. Simplistic Mixture Design Using the SGC and the DSR. Proceedings of the Association of Asphalt Paving Technologists, Vol. 72: 196–225. Bayomy, F. & Abu Abdo, A. 2007. Performance Evaluation of Idaho HMA Mixes Using Gyratory Stability, NIATT Project No. KLK 482 Final Report, National Institute for Advanced Transportation Technology, University of Idaho, Moscow, Idaho.

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Bayomy, F., Masad, E. & Dessouky, S. 2002. Development and Performance Prediction of Idaho Superpave Mixes, Interim Report ITD-NIATT Project KLK464, National Institute for Advanced Transportation Technology, University of Idaho, Moscow, Idaho. Butcher, M. 1998. Determining Gyratory Compaction Characteristic Using Servopac Gyratory Compactor. Transportation Research Record 1630: 89–97. Choubane, B., Page, G. & Musselman, J. 2000. Suitability of Asphalt Pavement Analyzer for Predicting Pavement Rutting. Transportation Research Record 1723: 107–115. Cominsky, J., Huber, G., Kennedy, T. & Anderson, R. 1994. The Superpave Mix Design Manual for New Construction and Overlays. SHRP Report A-407, Strategic Highway Research Program, Washington, D.C. DeSombre, R., Chadbourn, B., Newcomb, D.E. & Voller V. 1998. Parameters to Define the Laboratory Compaction Temperature Range of Hot-Mix Asphalt. Journal of Association of Asphalt Paving Technologists, Vol. 67: 125–152. Dessouky, S., Masad, E. & Bayomy, F. 2004. Prediction of Hot Mix Asphalt Stability Using the Superpave Gyratory Compactor, Journal of Materials in Civil Engineering, Vol. 16, No. 6: 578–587. Guler, M., Bahia, H., Bosscher, P. & Plesha M. 2000. Device for Measuring Shear Resistance for Hot Mix Asphalt in Gyratory Compactor. Transportation Research Record 1723: 116–124. Kumar, A. & Goetz W. 1974. The Gyratory Testing Machine as a Design Tool and Instrument for Bituminous Mixture Evaluation. Journal of Association of Asphalt Paving Technologists, Vol. 43: 350–383. Mallick, R. 1999. Use of Superpave Gyratory Compactor to Characterize Hot Mix Asphalt. Transportation Research Record 1681, TRB: 86–96. Martin, A. & Park D. 2003. Use of the Asphalt Pavement Analyzer and Repeated Simple Shear Test at Constant Height to Augment Superpave Volumetric Mix Design. Journal of transportation Engineering, Vol. 129, No. 5: 522–530. McRea, J.L. 1962. Gyratory Compaction Method for Determining Density Requirements for Subgrade and Base of Flexible Pavements. Miscellaneous paper No. 4–494, U.S. Army Engineering Waterways Experiment Station, Corps of Engineering, Vicksburg, Mississippi. McRea, J.L. 1965. Gyratory Testing Machine Technical Manual. Engineering Developments Company Inc., Vicksburg, Mississippi. Rand, D. 1997. Comparative Analysis of Superpave Gyratory Compactors and TxDOT Gyratory Compactors. Master Thesis, University of Texas, Austin, Texas. Ruth, B., Shen, X. & Wang, L. 1991. Gyratory Evaluation of Aggregate Blends to Determine their Effects on Shear Resistance and Sensitivity to Asphalt Content. American Society for Testing and Materials, 1147: 252–264. Sigurjonsson, S. & Ruth, B. 1990. Use of Gyratory Testing Machine to Evaluate Shear Resistance of Asphalt Paving Mixture. Transportation Research Record 1259: 63–78. Witczak, M., Kaloush, K., Pellinen, T., Al-Basyouny, M. & Von Quintus H. 2002. Simple Performance Test for Superpave Mix Design, NCHRP Report 465.Washington D.C.: TRB.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Prediction of the dynamic modulus of Superpave mixes A. Abu Abdo, F. Bayomy, R. Nielsen, T. Weaver & S.J. Jung Department of Civil Engineering, University of Idaho, Moscow, Idaho, USA

M.J. Santi Idaho Transportation Department, Boise, Idaho, USA

ABSTRACT: Since the mid 1990’s Superpave researchers suggested using the dynamic modulus (E*) as a fundamental parameter to reflect the hot-mix asphalt (HMA) performance. Furthermore, E* is an essential input in the 2002 AASHTO Mechanistic Empirical Pavement Design Guide (MEPDG). Hence, the method(s) of evaluating and/or predicting this property for HMA are essential for mix design as well as for structural design of asphalt pavements. This paper focuses on verification of a proposed model to predict E* from the properties of the HMA constituents. Dimensional analysis was used to pre-determine the model parameters. The model includes a new mix design mechanistic parameter, the Gyratory Stability (GS). The model was verified using field mixes and was compared to an MEPDG E* prediction model. MEPDG distresses results showed that the E* proposed model yielded closer results to actual E* results than MEPDG level-3 inputs. 1

INTRODUCTION

One of the most important outcomes of SHRP (Strategic Highway Research Program) is Superpave mix design, a state-of-the-art method to design Hot-Mix Asphalt (HMA), which is based on performance criteria. However, for practical implementation of SHRP products, the main design criterion in the current Superpave system is based only on volumetric analysis. Therefore, a need to develop simple, practical and reliable methods and procedures to be incorporated in the design criteria of Superpave is essential for its full implementation. Research efforts, since the release of Superpave in 1992, have continued to address this issue. Under the NCHRP (National Cooperative Highway Research Program) Project number 9-19, the Superpave Performance Tester (SPT) setup was developed. SPT includes dynamic modulus (E*), flow number (FN), and flow time (FT) tests. Recent studies (e.g. NCHRP projects 9-19 and 9-29) have concluded that SPT could be used to evaluate the asphalt mix performance potentials. A permanent deformation (rutting) indicator was recommended, E*/sin ϕ at a loading frequency of 5 Hz at temperatures of 37.8 and 54.4 °C, where ϕ is the phase angle. The phase angle represents the time lag between the application of load and the material response. In addition, E* ⋅ sin ϕ at a loading frequency of 5 Hz at temperatures of 4.4 and 21.1 °C was used as a fracture resistance indicator for the tested mixes. The release of the 2002 AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) increased the importance of E*, using E* as one of the essential inputs in the MEPDG in levels 1 and 2. However, mix evaluation methods, such as SPT, were found to be highly sophisticated and time consuming for mix design and quality control stages. Recognizing the importance of the dynamic modulus of the asphalt mixes as a performance parameter, many studies and research projects have been initiated to determine the dynamic modulus for asphalt mixes using simple tests and/or prediction models. Two approaches have been adopted; the first approach predicts E* using numerical and analytical modeling. The second approach predicts E* using models developed based on correlation and regression of actual test results with the physical and mechanical properties of the asphalt mixes. Many models 305

Table 1.

Dynamic modulus prediction model.

Analytical/Numerical models

Empirical/Regression models

– – – – – – – –

– Asphalt Institute Method (Shook and Kallas 1969) – Witczak Models (Witczak 1978, Miller et al. 1983, Witczak and Fonesca 1996 & Bari and Witczak 2006) – Christensen et al. (2003)

Voigt Model (Aboudi 1991) Reuss Model (Reuss & Aarsenault 1929) Hashin Model (1965) Aboundi Model (1991) Uddin (1999) You (2003) Dai & You (2007) Abbas et al. (2007)

(Table 1) have been developed under both approaches, which led to very simple models that under/overestimate E* or very sophisticated but better models that require multiple inputs and are user dependent. 2

OBJECTIVE

The main objective of this study was to develop, validate and present a model that predicts the dynamic modulus (E*) of asphalt mixes using its constituents and their interactions. 2.1 Dynamic modulus (E*) proposed model Using dimensional analysis (Bridgman 1963, Buckingham 1914 & Curtis et al. 1982), E* was found to be a function of binder dynamic shear modulus (G*), compaction energy index (Gyratory Stability, GS), bulk specific gravity (Gmb), and binder content (Pb). The binder effects are measured by G*, Gmb, and Pb, aggregates effects are measured by GS, Gmb, and (1Pb), and finally air voids are measured by Gmb. Further, it was found that the model consists of two sets of parameters; (G*/Pb) and (GS . Gmb/(1−Pb)). Full details of model development can be found in Abu Abdo 2008. 2.2 Asphalt mixtures With the help of the Idaho Transportation Department (ITD), raw materials for several mixes were procured from existing projects. These mixes were used to create 17 different mixes; four different aggregate structures and gradations (Coarse Mix (25 mm), Mix 1 (25 mm), Mix 2 (19 mm), and Fine Mix (19 mm)); three binder contents per two aggregate structures (Optimum asphalt content and ± 0.5% from Optimum) and eight binder grades (PG 70-22, PG 70-28, PG 70-34, PG 64-22, PG 64-28, PG 64-34, PG 58-28 and PG 58-34). Further, an additional seven field mixes were obtained for model verification. 2.3 Lab samples preparations and tests setup For the purpose of developing a predictive model of E*, three tests were performed on lab and field mixes to investigate the sensitivity of E* to mix parameters. These tests included: 2.3.1 Dynamic modulus (E*) test As per AASHTO TP 62-03, the dynamic modulus test consists of applying a uniaxial sinusoidal compressive stress to an unconfined test specimen and measuring the corresponding strain using 3 LVDTs mounted on the middle of the sample. The E* test was conducted under a series of temperatures (4.4, 21.1, 37.8 and 54.4 °C) and loading frequencies (0.1, 1, 5, 10 and 25 Hz) at each temperature. Two samples per mix were tested in the dynamic modulus test. Samples were compacted to achieve a height of 175 mm with 9% air voids. These samples were cored and sawed, to obtain 100 mm diameter by 150 mm high samples with 7% air voids. 306

2.3.2 Binder dynamic shear modulus (G*) test Eight binder grades were tested, two were neat binders (PG 58-28 and PG 64-22), and the rest were modified binders (PG 70-22, PG 70-28, PG 70-34, PG 64-28, PG 64-34, and PG 58-34). These binders were aged using Rolling Thin Film Oven (RTFO) to simulate the mix aging during mixing and compaction. G* was determined using the Dynamic Shear Rheometer (AASHTO T315-06). The test was conducted under the same series of temperatures and loading frequencies of the E* test. A constant stress of 220 Pa was used at temperatures of 37.8 and 54.4 °C and 5000 Pa at temperatures of 4.4 and 21.1 °C. 2.3.3 Gyratory stability (GS ) The GS is calculated from the accumulated incremental shear energy that is dissipated in a mix during compaction. GS is a mechanistic parameter (not volumetric) that reflects the complex contribution of the aggregate structure (aggregate shape, texture, and gradation) in the mix; hence is expected to affect its dynamic modulus. GS can be measured easily using only the compaction data retrieved from any Superpave Gyratory Compactor (SGC) equipped to report stress generated in HMA samples during compaction and mix properties. No other parameters are needed. (Details of GS development can be found in Bayomy & Abu Abdo 2007). Eight samples per mix were used to determine the GS. These specimens were compacted using the Servopac SGC to a number of gyrations equal to each mix set Ndesign, at which sample air voids are equal to 4%. All tests were conducted on both lab and field mixes. Lab mixes were mixed and compacted in the laboratory. Field mixes were loose plant-mixed mixes obtained from behind the paver as per ITD specification. These mixes were compacted in the laboratory to achieve similar air voids as the lab mixes. 2.4 Data analysis and results 2.4.1 Aggregates structure effects Four different aggregate structures were evaluated; Mix 1 (25 mm mix), Mix 2 (19 mm mix), very Coarse Mix (25 mm mix), and Fine mix (19 mm mix). These mixes were mixed using the same asphalt binder content (4.9%) and binder grade (PG 70-28). E* master curves for these mixes (Figure 1) show that at high temperature (represented by low frequencies), when binder effects lessen, E* increases for coarser mixes, thus increasing the mix stability, until a point is reached where the lack of fine materials causes the mix to become less stable, due to the decrease of friction between aggregate particles which is necessary for aggregate interlocking. GS results presented in Figure 2, followed the same trend, where Mix 1 yielded higher values than Mix 2. 2.4.2 Binder content effects E* and GS values were determined for Mix 1 and Mix 2 at different asphalt contents; optimum and ± 0.5% asphalt content from optimum. As shown in Figure 3, E* values for –0.5% 100000

E*, MPa

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Figure 1.

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E* master curves for four different aggregates structures.

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16 15 GS, kN . m

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Figure 2.

Gyratory stability for four different aggregates structures.

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Figure 4.

Gyratory stability for three binder contents.

asphalt content is higher than optimum asphalt content and ±0.5% asphalt. Therefore, it is expected that Mix 1 and Mix 2 with a –0.5% asphalt content will perform better than mixes with optimum asphalt content. In addition, both mixes yielded the highest GS at −0.5% AC instead of at optimum asphalt content (see Figure 4). It is believed that the decrease of binder content led to higher GS values due to the increase of interlocking between aggregate particles. Both E* and GS followed the same pattern. 308

2.4.3 Binder grade effects To evaluate changes of binder grades on E*, the upper and lower grades of the binders were changed. The upper grade represents the highest temperature the binder can operate, and it is mainly considered for rutting. On the other hand, the lower grade represents the lowest temperature, and is mainly considered for thermal cracking. Therefore, it was expected that the stiffness of an upper grade binder should be higher than a lower grade. E* results for Mix 1 and 2, as presented in Figure 5-a, show that at high temperatures (low frequencies) the higher binder grad (70, 64, and 58) yielded higher E* values and nearly the same values at low temperatures. Figure 5-b presents E* results for mixes with low temperature binder grades of (–34, –28 and –22). It was speculated that at higher temperatures, E* values would be similar since the upper grade is the same. E* values at low temperatures (presented by high frequencies on the master curve) were anticipated to vary due to differing low temperature binder grades. Results showed E* values varied at high temperature with the same upper binder grade and were similar at low temperature with varying lower binder grade. Earlier studies (Bayomy et al. 2002, Dessouky et al. 2004 and Bayomy & Abu Abdo 2007) showed that GS was not sensitive to the changes in binder grades, since GS is determined during compaction in the SGC, when all binders are heated to achieve the same viscosity; therefore the difference in grade does not influence the performance of the mix at these temperatures. GS sensitivity to binder grade was evaluated for Mix 1 and 2. Results showed, as expected, that overall GS did not capture the variations in binder grade. Thus, GS could be used to present the aggregate properties in the E* model. 2.5 E* proposed model development and validation To determine the relation between parameters predetermined by the dimensional analysis and E*, the sensitivity of E* versus (G*/Pb) and (ρw ⋅ GS ⋅ Gmb/(1 − Pb)) were investigated and a model was developed as shown in Equation 1 below.

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a) Changes in Upper Binder Grade

Figure 5.

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E* master curves for mix 1 and mix 2 with different binder grades.

309

⎛ G * ⋅ GS ⋅ %Gmm ⎞ E* = 1.08 ⎜ ⎟ Pb (1 − Pb ) ⎠ ⎝

0.5583

(1)

where, E*: Dynamic Modulus for Asphalt Mix, MPa, G*: Dynamic Shear Modulus for RTFO Aged Binder, MPa, Pb: Percent Binder Content, GS: Gyratory Stability, kN ⋅ m, Gmb: Bulk Specific gravity of Mix, Gmb = Gmm (1-AV%), Gmm: Maximum Specific gravity of Mix, and AV%: Air Voids. Using the two-tail statistical t-Test with α equal to 0.01 (99% reliability), it was found that there was no significant difference between the actual and predicted E* mean values. As shown in Figure 6-a, it was found that the developed model had a correlation of R2 equal to 0.962 and that the predicted E* values are all within of 12% of the measured E* values. To verify the ability of the model to predict E* for mixes other than the ones used in the model development, the predicted E* values were compared with actual E* data for other tested

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Figure 6.

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d) Witczak’s Revised Model (2006)

Results of predicted E* using proposed and Witczak’s models.

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Figure 7.

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Lab mixes permanent deformation results of MEPDG trial runs.

mixes (field mixes). It was found as shown in Figure 6-b that the proposed model could predict E* for these different mixes with a correlation of R2 equal to 0.9469. When using the two tail statistical t-Test with α equal to 0.01 (99% reliability), it was found that there was also no significant difference between the actual and predicted E* mean values. The next step in the model validation process compared the proposed model prediction for all mixes with other models. Actual E* values from laboratory measurements were compared to predicted values using the model proposed by Witczak and Fonesca (1996), hereafter referred to as the 1996 Witczak model, which is incorporated in the MEPDG for Level-3 analysis. Further, E* values were compared to the newly revised model by Bari and Witczak (2006), hereafter referred to as the revised Witczak model. It has been suggested that the revised Witczak model better predicts E* values when compared to the earlier models. Results from both models proposed by Witczak and colleagues did not predict actual E* values as well as the proposed model as indicated in Figure 6-c & Figure 6-d. It was observed that results of the revised Witczak model were less scattered than results of the 1996 Witczak model and unlike the proposed model, the revised Witczak model seemed to over-predict E* values. To verify if E* predicted by the proposed model can be used in the MEPDG instead of actual E* test data, MEPDG trial runs were conducted for Mix 1 and Mix 2 at optimum condition. In addition to actual and proposed model E* values, MEPDG Level-3 inputs (Witczak’s 1996 model) and Witczak’s revised model (2006) were used for comparison. MEPDG permanent deformation results (Figure 7) showed that the proposed model E* values yielded closer results to actual E* values. Level-3 inputs (Witczak’s 1996 model) yielded very high rutting results in contrast to Witczak’s 2006 revised model, which yielded very low rutting values. The average percent error was determined to be 12.6%, 86.6%, and 60.3% when proposed, Witczak’s 1996 model (Level-3), and Witczak’s 2006 revised model were compared respectively to results from actual E* values. In addition, MEPDG trial runs were conducted for 6 field mixes. As shown in Figure 8, pavement distresses (e.g. permanent deformation, alligator cracking, and longitudinal cracks) predicted with 50% reliability by the proposed model were closer to those based on the actual E* than distresses based on E* from the MEPDG Level-3 analysis (Witczak’s 1996 Model). 3

SUMMARY AND CONCLUSIONS

Based on the test results and data analysis presented in this study, the following conclusions and observations are made: 1. E* was found to be a function of binder grade and content, and aggregates properties and structures. 311

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Field mixes results of MEPDG trial runs.

2. Dimensional analysis was used effectively in determining the dynamic modulus (E*) model parameters. It was found that E* is a function of binder dynamic shear modulus (G*), Gyratory Stability (GS), bulk specific gravity of the mix (Gmb) and binder content (Pb). 3. Based on dimensional analysis and a regression analysis, an E* prediction model has been developed, with an R2 equal to 0.962. A two-tail t-Test found there is no significant difference between the means of the actual and predicted E* values with a reliability of 99%. 4. The model was further validated for seven field mixes. Using a two-tail t-Test, it was found there is also no significant difference between the means of the actual and predicted E* values with a reliability of 99% and an R2 equal to 0.9469. 5. The proposed model results were compared to the two Witczak models (1996 and 2006); it was found that the proposed model better predicts the dynamic modulus E*. 6. MEPDG trial runs were conducted for Mix 1 and Mix 2 at optimum condition. Actual E*, proposed model E*, and MEPDG Level-3 E* values from Witczak’s 1996 model, and Witczak’s 2006 revised model were used for comparison. MEPDG permanent deformation results showed that the proposed model E* values yielded closer results to actual E* values. The percent error was determined to be 12.6%, 86.6%, and 60.3% when proposed E*, Witczak’s 1996 model (Level-3 E*), and E* from Witczak’s model 2006 were utilized respectively.

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7. MEPDG trial runs were conducted for 6 field mixes. It was found that when the proposed E* model is used, pavement distresses results were closer to those from actual E* values than those based on E* values from MEPDG Level-3. ACKNOWLEDGEMENT This research is funded by the Idaho Transportation Department and the US Department of Transportation under contracts with the National Institute of Advanced Transportation Technology (NIATT) at the University of Idaho (projects number KLK483 and KLK479). The authors also would like to thank Mr. Frank Eckwright, an undergraduate student in civil engineering at the University of Idaho, for his help preparing specimens. REFERENCES AASHTO 2004. Standard Method of Test For Determining Dynamic Modulus of Hot-Mix Asphalt Concrete Mixtures. American Association of State Highway and Transportation Officials. AASHTO TP 62-03. AASHTO 2006. Standard Method of Test for Determining the Rheological Properties of Asphalt Binder Using a Dynamic Shear Rheometer (DSR). American Association of State Highway and Transportation Officials. AASHTO T315-06. ASTM 2003. Standard Test Method for Dynamic Modulus of Asphalt Mixtures. American Society for Testing and Materials, ASTM D3497-79. Abbas, A., Masad, E., Papagiannakis, T. & Harman, T. 2007. Micromechanical Modeling of the Viscoelastic Behavior of Asphalt Mixtures Using the Discrete-Element Method. International Journal of Geomechanics, 7 (2), 131–139. Aboudi, J. 1991. Mechanics of Composite Materials, a Unified Micromechanical Approach. Amsterdam: Elsevier. Abu Abdo, A. 2008. Development of Predictive Model to Determine the Dynamic Modulus for Hot Mix Asphalt. Thesis (PhD), University of Idaho, Moscow. ARA, Inc., ERES Consultants Division 2004. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. NCHRP Final Report 1-37A, Illinois. Bari, J. & Witczak, M.W. 2006. Development of a New Revised Version of the Witczak E* Predictive Model of Hot Mix Asphalt Mixtures. Journal of the Association of Asphalt Paving Technologist, 75, 381–424. Bayomy, F., Masad, E. & Dessouky, S. 2002. Development and Performance Prediction of Idaho Superpave Mixes, Interim Report ITD-NIATT Project KLK464, Idaho. Bayomy, F. & Abu Abdo, A. 2007. Performance Evaluation of Idaho HMA Mixes Using Gyratory Stability”, NIATT Project No. KLK 482 Final Report, Idaho. Bridgman, P.W. 1963. Dimensional Analysis. Cambridge: Yale University Press. Buckingham, E. 1914. On Physically Similar Systems; Illustrations of the Use of Dimensional Equations. Physical Review, 4 (4), 345–376. Christensen, D.W., Pellinen, T. & Bonaquist R.F. 2003. Hirsch Model for Estimating the Modulus of Asphalt Concrete. Journal of the Association of Asphalt Paving Technologist, 72, 97–121. Curtis, W.D., Logan, J.D. & Parker, W.A. 1982. Dimensional Analysis and Pi Theorem. Linear Algebra and its Applications, 47, 117–126. Dai, Q. & You, Z. 2007. Prediction of Creep Stiffness of Asphalt Mixture and Micromechanical FiniteElement and Discrete Models. Journal of Engineering Mechanics, ASCE, 133 (2), 163–173. Dessouky, S., Masad, E. & Bayomy, F. 2004. Prediction of Hot Mix Asphalt Stability Using the Superpave Gyratory Compactor, Journal of Materials in Civil Engineering, 16 (6), 578–587. Hashin, Z. 1965. Viscoelastic Behavior of Heterogeneous Media. Journal of Applied Mechanics, 32, 630–636. Hirsch, T.J. 1962. Modulus of Elasticity of Concrete Affected by Elastic Moduli of Cement Paste Matrix and Aggregates. Journal of the American Concrete Institute, 59 (3), 427–451. Huang, Y.H. 2004. Pavement Analysis and Design. Second addition. New Jersey: Pearson Prentice Hall. Miller, J.S. Uzan, J. & Witczak, M.W. 1983. Modification of the Asphalt Institute Bituminous Mix Modulus Predictive Equation. Transportation Research Record 911, 27–36.

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Nowak, A.S. & Collins, K.R. 2000. Reliability of Structures. Boston: Mc Graw Hill Higher Education. Reuss, A. & Aarsenault, Z. 1929. In Metal Matrix Composites, Oxford: Pergamon Press. Shook, J.F. & Kallas, B.F. 1969. Factors Influencing the Dynamic Modulus of Asphalt Concrete. Proceeding of The Association of Asphalt Paving Technologists, 38, 140–178. Uddin, W. 1999. A Micromechanical Model for Prediction of Creep Compliance and Viscoelastic Analysis of Asphalt Pavement. Presented at the 78th Annual Transportation Research Board Meeting. Witczak, M.W. 1978. Development of Regression Model for Asphalt Concrete Modulus for Use in MS1 Study. Research Report, University of Maryland, Collage Park. Witczak, M.W. & Fonseca, O.A. 1996. Revised Predictive Model for Dynamic (Complex) Modulus of Asphalt Mixtures, Transportation Research Record 1540, 15–23. You, Z. 2003. Development of a Micromechanical Modeling Approach to Predict Asphalt Mixture Stiffness Using the Discrete Element Method. Thesis (PhD), University of Illinois at Urbana-Champaign.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Laboratory evaluation of warm mix asphalt using Sasobit® S.W. Goh & Yu Liu Michigan Technological University, Houghton, Michigan, USA

Z. You Transportation Material Research Center, Michigan Technological University, USA

ABSTRACT: In comparison with other civil or general engineering construction, hot mix asphalt (HMA) design and construction can be said to consume significantly larger amounts of the United States energy resources. Thus, strategies to increase HMA sustainability are needed. The potential of using Warm Mix Asphalt (WMA) in reducing the energy consumption and emissions of HMA is part of the solution to resolve this issue. In this study, WMA binders made with Sasobit® at the rate of 2%, 3% and 4% based on total weight of asphalt were prepared and examined using the dynamic shear rheometer (DSR). Field produced samples were also collected and compared using the Superpave compactor. It was found that the additional Sasobit® increased the dynamic shear modulus (G*) of the asphalt binder significantly. The G* values increased when the rate of Sasobit® increased. Additionally, there was no significant difference in volumetric properties between WMA and HMA, even though the compaction temperature for WMA was about 25°C lower than the HMA compaction temperature.

1

BACKGROUND AND INTRODUCTION

Asphalt mixing is an energy intensive process compared with other industrial activities. The energy consumed during the mixing process was as much as 60 percent of the total energy required for the construction and maintenance of a given road over a typical service life of 30 years (Ventura et al. 2007). Hence, research studies on sustainable materials that deal with different environmental issues such as global warming are needed. The use of Warm Mix Asphalt (WMA) techniques allow for the reduction in required mixing energy and subsequently allow for substantial savings in energy costs (Romier et al. 2006). The use of additives in these WMA processes allowed the production temperatures to be 50°F to 100°F lower than the typical HMA production temperatures (Brown 2008). According to reports on the subject, this correlates to burner fuel savings with WMA processes ranging from 20 to 35 percent (D’Angelo et al. 2008). These energy savings and emission reductions could be greater if burner tuning was adjusted to allow the burners used in the WMA process to run at lower settings. In addition, a lower temperature used during the production also accounted for the reduction in electrical usage to mix the material, as well as to transport the material through the plant (D’Angelo et al. 2008). Figure 1 shows the compaction temperature for HMA, WMA, half-warm asphalt and cold mix asphalt (D’Angelo et al. 2008). In Europe, the benefits of WMA in terms of environmental aspects were consistently identified (FHWA 2008). A few countries in Europe (e.g. Norway, Italy, Netherland and France) indicated that emissions were reduced significantly when WMA was used. Based on research done in Europe and North America, there are usually several technologies that have been used to produce WMA such as synthetic zeolite (often referred to as Aspha-min®), Sasobit®, Evotherm®, WAM-FOAM®, etc (FHWA 2007; Von Devivere et al. 2003). All these technologies reduce the mixing temperature and allow the aggregate to be fully coated at a lower temperature (Goh and You 2008; Kristjansdottir et al. 2007). 315

Hot mix asphalt 280°F (138°C) to 320° F (160°C)

Warm mix asphalt 250°F (121°C) to 275°F (135°C)

Half warm asphalt 150°F (66°C) to 200°F (93°C) Cold mix asphalt around 60°F (16°C) Figure 1.

Typical mixing temperature range for asphalt mixtures.

It was known that hot bitumen fumes generated during the asphalt mixing processes contained polycyclic aromatic hydrocarbon (PAH) compounds (Ventura et al. 2007). PAH compounds are of concern regarding exposure to workers, because some of these compounds have been identified as carcinogenic, mutagenic and teratogenic. The current asphalt mixing process emitted huge amounts of PAH during the required warming and drying of aggregate steps (Ventura et al. 2007). The use of recycled HMA in these processes could also lead to additional asphalt related emissions. Additionally, studies focused on this topic have indicated that a distinct relationship exists between production temperatures and asphalt fume generation (D’Angelo et al. 2008). The use of WMA technology can effectively reduce the production of these fumes, consequently reducing worker’s exposure. Monitoring of worker exposure to aerosol/fumes and PAHs within asphalt mixing plants showed a viable decrease in exposure as compared to the HMA processes. Research studied by the German Bitumen Forum indicated that WMA could result in a reduction of up to 50 percent in PAHs (Anderson 2007). Aside from reducing exposure to these aerosols/fumes and PAHs, the lower mix temperatures utilizing WMA technology seem to foster a more desirable work environment, potentially aiding in worker retention (D’Angelo et al. 2008). Warm Mix Asphalt is a relatively new technology. Although it shows significant promise in energy saving and emission (CO2) reduction, currently many state agencies and contractors are not confident with the application of WMA. This paper presented a preliminary laboratory study on the rheological properties of WMA binder made with Sasobit® using Dynamic Shear Rheometer (DSR). In addition, field samples were collected and the volumetric properties of WMA were evaluated using Superpave mix design guide. 2

RHEOLOGICAL PROPERTIES OF WMA USING DYNAMIC SHEAR RHEOMETER

In this study, a Dynamic Shear Rheometer (DSR) was used to evaluate the rheological properties of WMA. DSR is a device that allows users to characterize the viscous and elastic behavior of asphalt binders at high and intermediate service temperatures. The asphalt binder with the grade of PG52-34 (control binder) was used in this study and a WMA additive, Sasobit® was added to the binder PG52-34 at the amount of 2%, 3% and 4% based on the total binder weight. In this study, only neat (unaged) binder was tested, and a total of six frequencies (ranging from 0.01 hz to 25 hz) and three temperatures (46°C, 55°C and 58°C) were used. The results from the DSR for WMA and control binders were compared and shown in figures 2 and 3. Note φM and φC are phase angles of WMA and control binders, respectively; GM and GC are dynamic shear moduli for WMA and control binders, respectively. It was found that most of the ratios of phase angles between WMA and control binders were smaller than one, which indicates that the WMA binder has a smaller phase angle. It is observed that when the amount of Sasobit® increased from 2% to 4%, the average ratios of phase angles 316

(a) 46°C

(b) 55°C

(c) 58°C Figure 2. Ratio of phase angles for WMA and control binders over different percentages of Sasobit® additive at (a) 46°C, (b) 55°C and (c) 58°C.

decreased from 0.961 to 0.323. Additionally, it was found that the ratio of phase angles at a testing frequency of 25 hz was significantly higher compared to others in most cases. In figure 3, the initial trend shows that the ratio of dynamic shear modulus slightly decreased when the rate of Sasobit® added increased (i.e. from 2% to 3% Sasobit®). However, the ratio of dynamic shear modulus increased dramatically when 4% of Sasobit® is used (rate 317

(a) 46°C

(b) 55°C

(c) 58°C Figure 3. Ratio of dynamic shear modulus between modified and control binders over different percentages of Sasobit® additive at (a) 46°C, (b) 55°C and (c) 58°C.

ranged from 5.06 to 235 over all the frequencies tested). This indicates that the additional Sasobit® might bump up the binder grade and would potentially improve asphalt rutting resistant. However, the increment of dynamic shear modulus may indicate that the asphalt has less resistance to fatigue cracking. In general, the results indicated that when frequencies increase, dynamic shear modules increase while phase angles decrease. It was also observed that temperature affects the value of both the phase angle and dynamic shear modulus ratios. 318

3

VOLUMETRIC PROPERTIES OF WARM MIX ASPHALT

It is important to evaluate and compare the volumetric properties of WMA with conventional HMA. The mixture design used in this study was based on a 5E3 mix in Michigan (i.e. nominal maximum aggregate size up to 9.5 mm and a designed traffic level less than 3 million ESALs). A total of nine HMA and nine WMA samples were collected from the field (HMA and WMA made with 1.5% Sasobit®). The mixing and compacting temperatures used for HMA were 165°C and 152°C, respectively. The WMA was mixed and compacted at the same temperature of 127°C. Table 1 shows the measured volumetric properties (average value) for WMA and HMA after compaction. The maximum specific gravity for WMA was found to be slightly lower than HMA. The initial investigation indicated that the Gmm of Sasobit® is lower than asphalt and hence, the maximum specific gravity of the mixture might drop when Sasobit® was added. The bulk specific gravity (Gmb) for WMA and HMA were back-calculated at each gyration number using the Superpave mix design guide. Figure 4 shows the average measured Gmb of WMA and HMA at each gyration number. It was observed that even though WMA compacted at a lower temperature, the Gmb of both HMA and WMA does not show any significant difference. The largest difference between HMA and WMA was found to be 0.34%, which was insignificant. Thus, this showed that WMA made with 1.5% Sasobit® could be compacted at least 25°C lower than the HMA and at the same time it would not affect the volumetric property. Additionally, advantages such as energy/fuel saving and emission reduction could be achieved based on the results conducted. Further research is ongoing to find out the performance of WMA and HMA using Superpave Simple Performance Test. Table 1.

Volumetric properties of WMA and HMA.

Maximum Specific Gravity, Gmm Gyration number use in Superpave Gyratory Compactor Bulk Specific Gravity (Gmb) at the end of Compaction Air Void Level Asphalt Binder Content

WMA

HMA

2.569

2.573

69

59

2.455 4.45% 5.52%

2.441 5.13% 5.52%

Figure 4. Bulk specific gravity of WMA compacted at 127°C and HMA compacted at 152°C versus gyration number.

319

4

SUMMARY AND CONCLUSIONS

This paper presents a preliminary laboratory study of WMA made with Sasobit®. Rheological and volumetric properties of WMA compared with HMA were discussed. Based on the results, it was found that when frequencies increased, dynamic shear modules increase while phase angles decrease. A significant increase in dynamic shear modulus of asphalt was found when 4% Sasobit® (based on the total binder weight) was used. For the WMA volumetric properties, it was found that WMA has a lower maximum specific gravity. In addition, it was found that the Gmb of both HMA and WMA did not show any significant difference even though WMA used a lower temperature (25°C lower). This indicated that WMA could be compacted at least 25°C lower than the HMA compaction temperature and would not affect the volumetric design. Thus, advantages such as energy/fuel saving and emission reduction could be achieved. ACKNOWLEDGEMENT The research work was partially sponsored by the Federal Highway Administration through Michigan Department of Transportation (MDOT). The authors also appreciate the guidance and involvement of John Barak of MDOT as the Project Manager. The authors also acknowledge the funding support from the United States Department of Transportation through the University Transportation Center for Materials in Sustainable Transportation Infrastructure at Michigan Technological University. The authors also wish to acknowledge the discussions with Curtis Bleech of MDOT and many helpful engineers in Payne and Dolan. The authors also acknowledge undergraduate student Viviana Torres Ortiz’s preliminary testing on warm mix asphalt. The contents of this short paper do not necessarily reflect the official views and policies of any institution or agency. REFERENCES Anderson, E.O. 2007. “WAM-Foam—An Environmentally Friendly Alternative to Hot-Mix Asphalt.” W. S. Team, ed., Norwegian Public Roads Administration, Oslo, Norway. Brown, D.C. 2008. “Warm Mix: The Lights Are Green.” HMAT, Vol. 13 (No. 1), 20–22, 25, 27, 30 & 32. D’Angelo, J., Harm, E., Bartoszek, J., Baumgardner, G., Corrigan, M., Cowsert, J., Harman, T., Jamshidi, M., Jones, W., Newcomb, D., Prowell, B., Sines, R. & Yeaton, B. (2008). “Warm Mix Asphalt: European Practice.” Office of International Programs, Office of Policy, Federal Highway Administration, US Department of Transportation, American Association of State Highway and Transportation Officials, National Cooperative Highway Research Program. FHWA. 2007. “Warm Mix Asphalt Technologies and Research.” US Department of Transportation Federal Highway Administration. FHWA. 2008. “Warm Mix Asphalt: European Practice. Chapter 2: Benefits of WMA.” US Department of Transportation Federal Highway Administration. FHWA. 2001. “Highway Statistics 2000.” Office of Highway Policy Information, Federal Highway Administration, Washington, DC. Goh, S.W. & You, Z. 2008. “Mechanical Properties of Warm Mix Asphalt Using Aspha-min®.” Transportation Research Board 87th Annual Meeting, Transportation Research Board, Washington, DC. [CD-ROM] Kristjansdottir, O., Muench, S.T., Michael, L. & Burke, G. 2007. “Assessing potential for warm-mix asphalt technology adoption.” Transportation Research Record, 91–99. Romier, A., Audeen, M., David, J., Martineau, Y. & Olard, F. 2006. “Low-energy asphalt with performance of hot-mix asphalt.” Transportation Research Record (1962), 101–112. Ventura, A., Jullien, A. & Moneron, P. 2007. “Polycyclic aromatic hydrocarbons emitted from a hot-mix drum, asphalt plant: Study of the influence from use of recycled bitumen.” Journal of Environmental Engineering and Science, 6(6), 727–734. Von Devivere, M., Barthel, W. & Marchand, J.P. 2003. Warm Asphalt Mixers by adding a synthetic zeolite, World Road Association—PIARC.

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Dynamic modulus prediction of asphalt concrete using three tensile tests S. Adhikari & Z. You Department of Civil and Environmental Engineering, Michigan Technological University, Houghton, MI, USA

ABSTRACT: A micromechanical based Discrete Element Model (DEM) was used to simulate dynamic modulus of the asphalt concrete using Uni-axial Tensile (UT) model, Hollow Cylindrical Tensile (HCT) model and Indirect Tensile (IDT) model. The dynamic moduli of the sand mastic and stiffness of aggregate were used as input parameters in the DEM to predict the dynamic moduli of the asphalt concrete. The three-dimensional (3D) internal microstructure of the asphalt concretes (i.e., orientation and distribution of aggregate, mastic and air voids) was obtained through the X-ray CT. The laboratory measured dynamic moduli of asphalt concrete were used to compare predicted dynamic moduli of three different tensile models. UT model was able to predict the asphalt concrete modulus across a range of loading frequencies and test temperatures. HCT model was under-predicted all the given temperatures and frequencies and IDT model slightly over-predicted at −18°C and slightly under-predicted at 4°C. 1

INTRODUCTION

The discrete element method is a good technique for micromechanical modeling of the asphalt concrete microstructure. The discrete element method was initially developed by Cundall (1971; 1987; 1990; 2000). The mechanical properties of asphalt concrete specimen was predicted by Buttlar & You (2001) using the micromechanical based Discrete Element Model (DEM). Buttlar & You (2001) used PFC2D code to predict creep strains and modulus of an asphalt concrete in the indirect tension test. Collop et al. (2004) applied a discrete element method to investigate the mechanical behavior of idealized asphalt concrete. You & Buttlar (2006) used a two-dimensional linear elastic DEM to simulate complex moduli of asphalt concrete. The comparison of two dimensional (2D) and three dimensional (3D) micromechanical discrete element simulation was developed by You et al. (2008). Adhikari & You (2008) predicted the asphalt concrete dynamic modulus using 2D and 3D DEM. The model was generated from the X-ray computed tomography (X-ray CT) images. It was found that the 3D discrete element models were able to predict the asphalt concrete moduli considering air void distribution. In this study, DEM was used to simulate dynamic modulus of the asphalt concrete using Uni-axial Tensile (UT), Hollow Cylindrical Tensile (HCT) and Indirect Tensile (IDT) test. The DEM simulation of the UT, HCT and IDT test was also compared in this paper. 3D DEM were developed to predict the dynamic modulus of an asphalt concrete from its constituent properties (i.e., the properties of aggregate, mastic and air voids). Sand mastic dynamic modulus was used as an input parameter in the 3D DEM. The Particle Flow Code (PFC) was used in the discrete element modeling prediction. The modulus from the prediction was compared with the laboratory measured asphalt concrete dynamic modulus. 2

MECHANICAL RESPONSE OF THREE TENSILE TESTS

This section briefly discusses mechanical response in the UT, HCT and IDT specimen of an asphalt concrete. UT specimen and HCT specimen were developed from coring the asphalt 321

concrete. IDT specimen was developed from horizontal cutting of the asphalt concrete. The dimensions of the asphalt concrete were 150 mm in diameter and 150 mm in height. The asphalt concrete was cored into a diameter of 100 mm and a height of 150 mm to get the UT specimen and HCT specimen. The dimensions of the IDT specimen were 150 mm in diameter and 50 mm in height. The principle behind the HCT test is to apply internal pressure to the inner cavity of the hollow cylinder specimen. The circumference pressure and longitudinal stress is developed on the hollow cylinder specimen due to the internal pressure. Haven & Swett (1915) described the modulus of the hollow cylinder can be calculated as E=

σ r p ⋅ Δ R1 ⎛ R22 + R12 ⎞ = ⎜ ⎟ εr R1 ⎜⎝ R22 − R12 ⎟⎠

(1)

Alavi & Monismith (1994) used the HCT test to determine the shear and compressive properties of asphalt concrete. Buttlar et al. (1999) & Al-Khateeb (2001) developed a HCT test device to determine the mechanical properties of the asphalt concrete. Dynamic modulus was measure by applying the different loading frequencies in the inner surface of the cylinder by Buttlar et al. (1999) and Al-Khateeb (2001). The principle behind the indirect tensile test is subjected to a uniform diametral pressure, p, acting over parallel plates. The tensile stress and compressive stress are developed on the specimen due to the diametral pressure. The tensile and compressive stresses produce a corresponding strain on the indirect tensile specimen. Kaklis et al. (2005) described the tensile stress at the center of the specimen, and is given by the equation:

σt =

2P π Dt

(2)

The corresponding strain εt, εc at the center of the specimen calculated from the change in displacement due to loading and used to determine modulus by the equation: E=

σt εt

(3)

The principle behind the UT test is to apply tensile pressure to the top and bottom of the cylindrical specimen along loading direction. The tensile stress and tensile strains are calculated on the cylinder specimen due to the external pressure and deflection. The modulus was calculated by dividing tensile stress by tensile strain. 3

LABORATORY TESTS

Asphalt concretes were prepared using 5.57% asphalt content of Performance Grade (PG) 64-28. Asphalt concrete was compacted to 4.36% air voids using a Superpave gyratory compactor. The aggregate gradation was a 12.5 mm nominal maximum aggregate size in the mix. The nominal maximum aggregate size of sand mastic was 1.18 mm. The asphalt content in the sand mastic was around 10.33%. The dynamic modulus of the sand mastic was measured through uniaxial compressive tests. The dynamic modulus of the sand mastic and asphalt concretes were tested across a range of loading frequencies (0.1 Hz, 0.5 Hz, 1 Hz, 5 Hz, 10 Hz and 25 Hz) and test temperatures (–18°C, −6°C and 4°C). An aggregate modulus of 55.5 GPa was used in the models. 4

IMAGE PROCESSING OF X-RAY CT IMAGES

The X-ray Computed Tomography (CT) technique was used to get the asphalt concrete microstructure for the DEM simulations. X-ray CT was used to acquire the internal microstructure 322

X-ray CT image Figure 1.

Aggregate > 1.18 mm

Air Void in black

Illustration of gray images from the X-ray CT with air void and aggregate.

with high accuracy (Lee and Dass 1993). Shashindhar (1999) & Masad et al. (1999) used X-ray CT image to study the compaction of asphalt concretes. An image processing technique was used to transfer X-ray gray image into aggregate, mastic and air voids images according to a threshold segmenting of each element. Figure 1 shows the segmentation to separate air voids, aggregate and mastic domain. Aggregate size larger than 1.18 mm is shown in Figure 1. The separation of the mastic threshold index was determined by volumetric analysis. The air void level index was chosen as 0–124. The threshold index of an aggregate size larger than 1.18 mm was selected as 202–255. 5

DISCRETE ELEMENT MODELING

The gray images of X-ray CT images were transferred into aggregate, mastic and air void images according to a threshold segmenting of each element. Aggregate, mastic and air void images were input into DEM by using discrete balls. Three types of DEM were generated in this study. Cylindrical-shaped model were prepared for UT tests and IDT tests. Hollow cylindrical-shape was prepared for HCT test. Figure 2 illustrates the extraction of HCT, UT and IDT models developed from the cylindrical asphalt specimen, where the aggregates, mastics and air voids are easily seen. The radius of each sphere was 0.5 mm for all models. The 3D hollow cylinder was used with an outer diameter of 150 mm, inner diameter of 100 mm and depth of 150 mm in the DEM simulation. There were a total of 487,200 spheres in the 3D asphalt concrete model. The aggregate volume was calculated by dividing the number of aggregate elements by the number of total elements, which was around 31.27%. The air voids were around 6.76%. The dimensions of the uniaxial cylindrical DEM were 100 mm in diameter and 150 mm in height. There were a total of 404,460 spheres in this 3D asphalt concrete DEM. There was a total of 49.73% aggregate phase of DEM. The air voids were around 1.65%. The 3D IDT cylinder specimen was used with diameter of 150 mm depth of 50 mm in the DEM simulation. There were a total of 296,240 spheres in this 3D asphalt concrete model. The aggregate volume was around 38.79%. The air voids were around 4.72%. A 3D discrete element model was constructed using closed-packing cubic arrays of spheres. The closed-packing arrays are based upon the face-centered packing spheres (Thornton 1979). The 3D DEMs were used to predict the dynamic modulus of the asphalt concrete. The sand mastic dynamic modulus and aggregate modulus were used into the DEM to predict the asphalt concrete modulus. The modulus of the hollow cylindrical asphalt model was simulated with 3D DEM by applying tensile stress on the inner surface of the hollow cylinder. The strains in the radial directions were computed using the change in displacement on the inner surface. The modulus was computed from the plots of radial stress versus radial strain. The modulus of the uniaxial tensile model was simulated by applying tensile stress at the top and bottom surfaces of the cylindrical model. The tensile strains in the axial direction were computed using the 323

3D cylindrical specimen

(a)

HCT Model

(b) Figure 2a,b.

UT Model

IDT Model

Corresponding air void distribution Demonstration of 3D DEM.

change in displacement on the top surface of the cylinder. The modulus was computed from the plots of tensile stress versus tensile strain. The modulus of the IDT model was simulated by applying compressive stress at the diametric section of the cylindrical model. The tensile stresses and strains at the center of the cylindrical specimen were calculated. The modulus was computed from the tensile stress divided by tensile strain. The contact stiffness model was used in the contact of discrete balls. Contact stiffness model provides an elastic relationship between the contact force and relative displacement between particles. The interaction of aggregates and mastics, mastics and mastics, and aggregate and aggregate were prepared with a linear contact stiffness model. 6

RESULTS OF DEM

The dynamic modulus of the asphalt concrete was predicted using UT, HCT and IDT discrete element models in this section. The 3D DEM simulations’ modulus results were compared 324

Figure 3.

Three different discrete element model comparisons with lab measurement.

with the experimental measurements to evaluate the accuracy of the different simulation methods. The dynamic modulus of the asphalt mastic across a range of loading frequencies (0.1 Hz, 0.5 Hz, 1 Hz, 5 Hz, 10 Hz and 25 Hz) and test temperatures (4°C, −6°C and −18°C) were measured. The moduli of sand mastic 1.18 mm were used as input parameters in the asphalt concrete models. A comparison of dynamic modulus prediction using the UT model, the HCT model and the IDT model with the experimental measurements (from three temperatures and six loading frequencies) is shown in Figure 3. The 3D DEM prediction using the UT model and the IDT model was very close to the asphalt concrete’s modulus measurements. The modulus of 3D DEM using HCT was under-predicted. HCT model was under-predicted at all test temperature and the IDT model over-predicted at the temperature of –18°C and under-predicted at the temperature of 4oC. The air voids of HCT, UT and IDT specimen were 6.76%, 1.65 and 4.72%. The predicted modulus was increased as decreased of air void. 7

CONCLUSIONS

The asphalt concrete was modeled using the UT model, HCT model and IDT model with 3D discrete element models. The 3D morphology of the asphalt concrete mixture was captured with an X-ray tomography image and reconstructed into the assembly of discrete element models. The aggregate, the sand mastic and the air void phases were analyzed in the DEM. The sand mastic used was a combination of asphalt and aggregate finer than 2.36 mm. The dynamic moduli of the sand mastic and modulus of aggregate were used in the discrete element models. The dynamic moduli of the asphalt concrete were used to assess the discrete element models. The moduli of the 3D models were compared with the experimental data. The predicted dynamic modulus from a DEM at frequencies of 0.1, 0.5, 1, 5, 10, and 25 Hz and test temperatures 4, −6, and −18°C was used to determine the dynamic modulus. It was found that the UT model was able to predict the asphalt concrete modulus across a range of temperatures and loading frequencies. The modulus HCT model was under-predicted and IDT model slightly over-predicted at −18°C and slightly under-predicted at 4°C. The results indicate that the different simulation models play a significant role during modeling of asphalt concrete. The results also indicate that modulus was increased with decreasing air void percentage. In this study, the elastic model was used to calculate the dynamic modulus. The DEM model with elastic constitutive elements matched well with measurements at low temperatures (4°C, –6°C and –18°C). Since the asphalt concrete behaves like elastic at low temperature (i.e. lower than 4°C). The future objective is moving toward viscoelastic models to predict at higher temperatures (i.e. more than 4°C) in subsequent work. 325

ACKNOWLEDGEMENTS This material is based in part upon work supported by the National Science Foundation under grant 0701264. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author’s and do not necessarily reflect the views of the National Science Foundation. The authors appreciate Dr. M. Emin Kutay for providing the X-ray tomography images. The experimental work was completed in the Transportation Materials Research Center at Michigan Technological University, which maintains the AASHTO Materials Reference Laboratory (AMRL) accreditation on asphalt and asphalt mixtures, aggregates, and Portland cement concrete. REFERENCES Adhikari, S., & You, Z. 2008. 3D Microstructural Models for Asphalt Mixtures Using X-Ray Computed Tomography Images. International Journal of Pavement Research and Technology 1(3): 94–99. Al-Khateeb, G.G. 2001. Development of a Hollow Cylinder Tensile Tester to Obtain Fundamental Mechanical Properties of Asphalt Paving Mixtures. University of Illinois at Urbana-Champaign. Alavi, S.H., & Monismith, C.L. 1994. Time and Temperature Dependent Properties of Asphalt Concrete Mixes Tested as Hollow Cylinders and Subjected to Dynamic Axial and Shear Loads. Journal of the Association of Asphalt Paving Technologists 63: 152–181. Buttlar, W.G., Al-Khateeb, G.G., & Bozkurt, D. 1999. Development of a Hollow Cylinder Tensile Tester to Obtain Mechanical Properties of Bituminous Paving Mixtures. Journal of the Association of Asphalt Paving Technologists 68: 369–403. Buttlar, W.G., & You, Z. 2001. Discrete element modeling of asphalt concrete: Microfabric approach. Transportation Research Record 1757: 111–118. Collop, A.C., McDowell, G.R., & Lee, Y. 2004. Use of the distinct element method to model the deformation behavior of an idealized asphalt mixture. Taylor & Francis Limited. 1–7. Cundall, P.A. 1971. A Computer Model for Simulating Progressive Large Scale Movements in Blocky Rock Systems. Proceedings of the Symposium of the International Society of Rock Mechanics. Nancy, France. II-8. Cundall, P.A.1987. Distinct Element Models of Rock and Soil Structure. Analytical and Computational Methods in Engineering Rock Mechanics. (Brown, E.T. Ed.), London, George Allen and Unwin. 129–163. Cundall, P.A. 1990. Numerical modelling of jointed and faulted rock. Proceedings of the International Conference on Mechanics of Jointed and Faulted Rock: 11. Cundall, P.A. 2000. A Discontinuous Future for Numerical Modelling in Geomechanics. Geotech. Eng 149(1): 41–47. Haven, G.B., & Swett, G.W. 1915. The design of steam boilers and pressure vessels. John wiley and dons. Inc., New york. Kaklis, K.N., Agioutantis, Z., Sarris, E., & Pateli, A. 2005. A theoretical and numerical study of discs with flat edges under diametral compression (flat brazilian test). 5th GRACM International Congress on Computational Mechanics. Limassol, Cyprus. Lee, X., & Dass, W.C. 1993. Experimental study of granular packing structure changes under load. Publ by Elsevier Science Publishers B.V., Amsterdam, Neth, Birmingham, UK. 17. Masad, E., Muhunthan, B., Shashidhar, N., & Harman, T. 1999. Quantifying laboratory compaction effects on the internal structure of asphalt concrete. Transportation Research Record. 1681: 179–185. Shashidhar, N. 1999. X-ray tomography of asphalt concrete. Transportation Research Record. 1681: 186–192. Thornton, C. 1979. Conditions for failure of a face-centered cubic array of uniform rigid spheres. Geotechnique. 29(4): 441–459. You, Z., Adhikari, S., & Dai, Q. 2008. Two Dimensional and Three Dimensional Discrete Element Models for HMA. ASCE Geotechnical Special Publication: Innovations in the Characterization, Modeling and Simulation of Pavements and Materials: 118–127. You, Z., & Buttlar, W.G. 2006. Micromechanical Modeling Approach to Predict Compressive Dynamic Moduli of Asphalt Mixture Using the Distinct Element Method. Transportation Research Record: Journal of the Transportation Research Board, National Research Council, Washington, D.C. 1970: 73–83.

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Assessing low temperature properties of asphalt materials by means of static testing techniques M. Wistuba, K. Mollenhauer & K. Metzker Braunschweig Pavement Engineering Centre (ISBS), Technische Universität Braunschweig, Germany

ABSTRACT: Asphalt pavements that are exposed to decreasing temperatures are loaded by cryogenic stresses arising from prohibited thermal shrinkage. Since decades, a common technique to assess the low temperature behaviour of asphalt materials is the combination of two laboratory tests, i.e. the thermal strain restrained specimen test (TSRST) and the uniaxial tensile stress test at low temperature conditions (UTST). In this study, these two test procedures are reviewed, based on laboratory data for different asphalt mixtures gained in numerous research studies within the last 15 years. In particular, the influences of the test conditions on the test results are discussed, and the effects of the variation of material properties on the low temperature performance are evaluated. Finally, the interrelation between the test results of the considered asphalt mixtures and the low temperature properties of bitumen is presented. 1

INTRODUCTION

Apart from traffic loading, the performance of a pavement in terms of strength and durability is mainly influenced by environmental factors, such as impacts from hot and cold temperature spells, precipitation as well as frost and water fluctuations in the unbound foundation. As the stiffness of bituminous materials varies widely depending on the temperature conditions, stresses and strains in asphalt pavements are always resulting from the actual temperature situation. Especially the effects of heavy traffic loading at extreme temperatures may be critical for pavement damage. Therefore, the temperature conditions are taken into account particularly in numerical stress-strain-analyses, as asphalt is a thermo-rheologically complex material, and its material characteristics vary widely depending on the magnitude of the thermal loading. Because of its viscous properties, asphalt exhibits low viscosity at high temperatures and high viscosity at low temperatures. When temperature decreases, elasticity and stiffness increase. At the same time, the asphalt material is subject to thermal shrinkage. At medium and high temperatures, the resulting thermal stress (cryogenic stress) can be reduced through internal flow processes without causing any changes in its external shape. This stress relaxation property of asphalt materials, where any shrinkage stress that may occur dissipates through viscous flow, is an advantage used in flexible road pavement construction without the necessity of pre-cast construction joints or reinforcement (as e.g. needed for cement concrete pavements). With decreasing temperature, movements in the grain structure are increasingly prevented due to the increasing viscosity of the bitumen. At the same time, the binder will contract at low temperatures, causing the binder film around the aggregate to become thinner. The difference of the thermal dilation between bitumen and aggregate weakens the bitumen-aggregate interaction, causing a decrease of the tensile strength of the composite. Therefore, in consequence of debonding effects of bitumen and aggregate, strength will decrease again with ongoing decrease in temperature. Moreover, the lower the temperature falls, the more the bituminous material stiffens and the less it is able to heal by stress relaxation. Eventually, at some temperature, the cryogenic stress (potentially super-imposed by traffic-induced stress) 327

may exceed the local tensile strength of the purely brittle asphalt material, and cracking may be initiated. In-field observations of low temperature cracks are manifold. Depending on the respective mechanism of crack initiation, surface cracks are observed in situ to be mainly orientated in two directions, i.e. transversally and longitudinally with respect to the road axis. Intermittent transverse cracks perpendicular to the road axis often appear in surprisingly consistent spacing of typically 6 to 9 m. Even though traffic induced stresses may likely play a role, transverse cracks are supposed to occur in consequence of thermal stresses due to extreme cooling, and therefore are usually called ‘low temperature cracks’. Low temperature cracks typically occur in consequence of a sudden change in the asphalt layer temperature gradient, especially at very low temperatures and fast cooling rates at the same time. Because of the complete geometrical confinement of the pavement, the temperature stresses in the longitudinal direction are more significant than those in the transversal direction, and hence transversal cracks are formed primarily. However, transverse cracks can act as stress focal points from which longitudinal cracks may initiate, and moreover, the presence of a transverse crack in the asphalt layer significantly increases the vertical stresses in the base and it also has a noticeable effect on the horizontal stresses (e.g. see Holewinski et al., 2003). In-field longitudinal cracks are found to run inside as well as outside the wheel-path. In literature, various mechanisms have been identified as contributing factors (cp. Myers et al., 1998; Holewinski et al., 2003; and Collop et al., 2004). It is claimed inter alia, that critical stresses to provoke longitudinal cracking may result from traffic-loading at low temperatures, when traffic-induced stresses arising from the negative bending curvature effect of the asphalt layer are superimposed by thermal (cryogenic) stresses, and thus, combined stresses lead to a complex stress situation in the pavement, which is influenced by the material strength and toughness, the material fatigue properties and the changing stiffness properties in consequence of temperature cycles and varying seasonal sub-grade bearing support. Premature material fatigue arises in the form of longitudinal cracks outside the wheel path in a distance between 400 to 900 mm from the load axis, with increasing distance if temperature decreases (Arand et al., 1995). Asphalt mix specification requires predictive techniques for characterization of in-field material performance. The overall objective of such simulative testing is to reproduce as closely as possible and practical the in-field pavement loading conditions. At the very best, this will include most realistic consideration of the three dimensional stress state due to traffic and thermal loading, and changing structural and material conditions, especially in consequence of asphalt ageing and of moisture effects. By January 2007 new harmonized European Standards (EN) for asphalts and asphalt testing were introduced in all CEN member countries within the European Union. These EN standards contain test conditions for different performance criteria, i.e. stiffness and fatigue properties, and resistance to permanent deformation. However, this first generation Standards do not consider techniques to assess low temperature properties, even though a number of national Standards cover these techniques already (see, e.g. FGSV (1994) for Germany, ÖNORM B3590 for Austria, or AASHTO (1993) for the USA). For this reason, a new European Standard is drafted to date, i.e. preEN 12697-46, which includes a set of static and dynamic testing techniques. This paper presents two static testing techniques covered by the draft Standard, i.e. the thermal stress restrained specimen test (TSRST) and the uniaxial tensile stress test (UTST), and it summarizes important findings based on numerous laboratory investigations. 2

STATIC TESTING TECHNIQUES

While the thermal stress restrained specimen test (TSRST) is intended to derive shrinkage properties of a compacted asphalt mixture, the uniaxial tensile stress test (UTST) is useful to derive creep compliance and tensile strength at low temperatures. The test equipment and the test principles for conducting these tests are given in this chapter. 328

4 1 5

2

6 3

7

2 6 5

8

1 2 3 4 Figure 1. ISBS.

2.1

load cell displacement transducer thermal indifferent measurement base crossbeam

5 6 7 8

gimbal suspension adapter specimen gear box with stepping motor

Layout of a test device used for conducting static low temperature tests as developed by

Test equipment

A layout of the test equipment, as typically used for static laboratory testing in uni-axial direction is shown in Figure 1 representing the apparatus developed at the Braunschweig Pavement Engineering Centre (ISBS, Germany) (see e.g. Eulitz, 1987). This uniaxial test device used for carrying out low temperature tests represents a bending-resistant load frame. The frame consists of a base plate of high bending resistance and two columns supporting a stiff crossbeam. A gearbox with stepping motor is fixed to the base plate and can generate movements with an accuracy of 0.05 μm. At the crossbeam the control unit is fixed for controlling the force or displacement applied. To avoid radial and/or transversal forces as well as moments in the test specimen, it is placed between the gearbox and the pressure measurement equipment with two gimbal suspensions. The system is placed in a thermostatic cabinet with temperature control. The temperature range extends from −40°C to +40°C with an accuracy of ±0.3°C. The air temperature in the thermostatic cabinet is recorded continuously by means of a temperature sensor of the type PT 100 with an accuracy of 0.1°C. The temperature of the test specimen is measured indirectly, with an accuracy of 0.1°C, by means of a temperature sensor positioned in the middle of the cross-section of a dummy of the same cross-section as the specimen. As the steel frame is exposed to the same thermal changes as the examined specimens, it reacts with thermal shrinkage and expansion. Thus, the correct measuring of the actual strain of the specimen requires a basis with constant length at various temperatures. Therefore, two measurement bases with thermal indifference made of carbon fibres, help to measure the real deformation of the test specimen and to counterbalance the thermal strain of the test equipment. Figure 1 shows a principle sketch and a photo of the test device. During the test the force is recorded by a load cell fixed to the cross beam (1) whereas the specimen length of the specimen is measured by 4 displacement transducers (2). The specimen is fixed centrally within two adapters with a two-component epoxy resin adhesive. After curing of the adhesive, the specimen is put between the gimbal suspensions of the test device. At ISBS, prismatic specimens are used with the dimensions 40 × 40 × 160 mm3 for asphalt mixes with a maximum grain size of 11 mm, and with the dimensions 55 × 55 × 329

160 mm3 for grain sizes between 11 and 32 mm. The specimens are sawn from asphalt plates compacted in the laboratory by means of the segment roller compaction technique, or from asphalt cores taken in situ in a diameter of about 300 mm. In this way, the longitudinal axes of the specimens are always orthogonal to the direction of compaction. Hence, the direction of loading within the laboratory test basically corresponds to the direction of loading in-situ. 2.2 Tensile stress restrained specimen test The tensile stress restrained specimen test (TSRST), as developed by Monismith et al. (1965), Fabb (1974), Arand (1987, 1996; Arand et al., 1984, 1989, 1995), and Jung et al. (1994), is a cooling test in which temperature is reduced at a constant rate. It simulates the weatherinduced cooling of an asphalt pavement in the laboratory and aims in recovering the cryogenic tensile stresses in an asphalt mix specimen arising from temperature cooling as well as stress and temperature at fracture. The TSRST is intended to investigate the influence of mix parameters on the low temperature failure behaviour, like grading, aggregate type, filler content, and binder type and content. After the installation of the test specimen it is brought to an initial temperature without inducing any stress. During the test the temperature is reduced by a pre-specified constant cooling rate, while the deformation of the specimen is restrained. The step motor responds to changes in the electric signals emitted by the displacement transducers. Comparisons between the target and the actual length of the test specimen are conducted continuously. As soon as a change in length occurs, the step motor pulls the specimen back to its original length. This process continues until the tensile force reaches the material’s tensile strength and, hence, the specimen fractures. An illustration of the test principle is given in Figure 2 (a), and a typical test result is depicted in Figure 2 (b) for asphalt concrete AC 11 for two different cooling rates, i.e. 5°C/h and 10°C/h. The test is stopped as soon as the specimen fractures (complete specimen transsection). From the tensile force (F) and from the specimen’s cross-section (A), the cryogenic tensile stress σkry is calculated from σkry = F/A. As a result, the change in cryogenic tensile stress versus temperature is shown in a diagram (see Figure 4). The parameters resulting from the test are given in terms of the fracture stress σcrack in MPa and the corresponding fracture temperature Tcrack in °C, also referred to as TTSRST. A number of studies are focused in particular on the influence of the test temperature and/or the cooling rate selected as well as of test specimen dimensions on temperatures at fracture and tensile strength reserves (Arand, 1984; Wistuba et al., 2006, 2007; Spiegl et al.,

(a)

(b)

Figure 2. Test principle for TSRST (a), and (b) TSRST results for AC 11 for two different cooling rates, i.e. 5°C/h and 10°C/h (Spiegl et al., 2005).

330

2005). Also during the Strategic Highway Research Program (SHRP), the test conditions of the TSRST test were analysed thoroughly. The influence of binder ageing behaviour and methods of improving low temperature performance through modified binders are also being investigated (Metha et al., 2000). In summary, only a marginal influence of the start temperature on the test results was stated, if only the start temperature is chosen considerably higher than the failure temperature. Therefore, a standard start temperature of +20°C is prescribed in the draft European Standard preEN 12697-46. As to the cooling rate, it may influence both the failure stress and the failure temperature. Vinson et al. (1989) stated that a cooling rate of below 5°C/h influences the test results significantly resulting in lower cracking temperatures. Jung et al. (1994) stated that an increase of the cooling rate from 1°C/h to 10°C/h results in an increase of the fracture temperature of about 5°C, and an increase of the failure stress of about 20%. The lower the cooling rate the lower is the fracture temperature, as the stress relaxation capacity is more distinct. For practical reasons, a standard cooling rate of +10°C ± 0.1°C is prescribed in the European Standard, even though such severe cooling conditions may hardly ever occur in situ. However, it may be difficult to evaluate the low temperature performance of asphalt mixtures by using TSRST data only, as in some cases little variation is found in the failure stress of different materials, especially if the effect of different polymer modifiers is investigated (e.g., see Fabb, 1974; Kluttz et al., 1997; Hesp et al., 2000, 2004 and references therein). It was also observed, that for some materials the specimen did not fail in the fashion of a sudden fracture, but in a sliding failure, which makes the determination of a fracture criterion delicate. 2.3 Uniaxial tensile stress test The tensile strength of asphalt mixtures is a critical factor in cracking resistance. During the uniaxial tensile stress test (UTST), the asphalt specimen is loaded by a tensile displacement until fracture occurs, and strength is determined from the maximum load and the specimen dimensions. The UTST is an isothermal process at a specified test temperature. After stress-free cooling of the specimen to the test temperature, a constant deformation rate is applied. The test is stopped as soon as the applied load has reached a maximum and fracture occurs. An illustration of the test principle is given in Figure 3. Usually, the test temperatures are specified in a range of –20 to –25°C in intervals of 5 to 15°C, with a minimum of four test temperatures. For a deformation rate of 1 mm/min and a temperature range of –25°C to –10°C the stress increase is almost linear and the specimen fails spontaneously. At higher temperatures, ductile behaviour becomes more distinct. 6,00

deformation

-25 °C

-10 °C

SMA 11 @ 1 mm/min

time temperature

time force

Tensile stress σt [MPa]

5,00 4,00

+5 °C

3,00 2,00 +20 °C

1,00 0,00

time

(a) Figure 3.

0

0,1

0,2

0,3

0,4

0,5

Strain ε [%]

(b) Test principle for UTST (a), and (b) UTST results for SMA 11 at different temperatures.

331

Figure 4. UTST results for AC 11: influence of displacement rate and temperature on stress-strain relation and tensile strength (Spiegl et al., 2005).

During the test, the force is recorded. The test is stopped as soon as the specimen fractures (complete specimen trans-section) or the course of tensile stress reached a maximum value and decreases again. As a result of the test, the strength is calculated from the maximum load and is shown over the test temperature in a diagram. A cubic spline function is found considering all test temperatures, giving the strength curve (see Figure 5). The maximum tensile strength fmax for temperatures beyond this range can be approximately extrapolated from: fmax (T = –40°C) = 0,9 ⋅ fmax (T = –25°C);

and fmax (T = +30°C) = 0,5 ⋅ fmax (T = +20°C).

For UTST, the maximum tensile strength fmax is determined, as well as the related temperature Tf,max. The temperature Tf,max in function of the applied deformation rate can be defined as the maximum temperature in the plot tensile strength over temperature and referred to as the brittle to ductile transition temperature Tbdm. The standard deformation rate during UTST is 1 mm/min corresponding to a strain rate of approximately dε/dt = 375 mm/m/h if an original specimen length of 160 mm is considered. This strain rate, however, exceeds the strain rate during in-service situations (cp. Spiegl et al., 2005). The influence of the displacement rate on stress-strain relation and tensile strength is given in Figure 4 for AC 11 for two different temperatures, i.e. –10°C (left), and –25°C (right). Results are depicted for strain rates of 1 mm/min and 0.1 mm/min. Whereas the strain rate hardly influences the stress-strain relation and, thus, the tensile strength at a test temperature of –25°C, the material response is significantly different at –10°C. 2.4 Superposition of TSRST and UTST results By combining the test results from the TSRST and from the UTST, the tensile strength reserve is found, a target parameter commonly used to rank the low temperature cracking resistance of asphalt mixtures. According to Arand et al. (1984), the tensile strength reserve is a measure of the capacity of traffic stress that an asphalt material can support additionally to cryogenic stress without any failure. For determination of the tensile strength reserve, the stress curve induced by thermal shrinkage— as derived from TSRST—is compared to the respective tensile strength curve—as derived from UTST—for the tested material. The tensile strength reserve Δβt is referred to as the difference between the cryogenic stress obtained from the TSRST at a certain temperature and the respective material strength given by the UTST. Consequently, the curve of the tensile strength reserve is derived for the whole temperature range (see Figure 5). The tensile strength reserve is used to assess the additional traffic-induced tensile stresses that the asphalt is still able to absorb. The superposition of TSRST and UTST results raises the question of the different loading speeds, applied on the specimen by long-standing TSRST on the one hand, and by the 332

Tension stress σ [MPa]

6,0 5,0

Tensile Strength βt(T)

Δβ t,max 4,0 σF

Tensile Strength Reserve Δβt(T)

3,0 2,0

Cryogenic Stress σcry (T)

1,0

-30

-10

0

Example of a strength test result: UTST (left), and UCST (right).

Influence of compositional asphalt properties on the results of low-temperature tests.

UTST: βt(T ) +20°C +5°C –10°C –25°C +5°C –10°C –25°C

↓

↑ ↑ ↓ ↓ ↑ ↓ ↓

↓ ↓ ↓

↓ ↑

–

–

↑ ↑ ↑ ↑

↑ ↑ ↓ ↓

↑ ↑ ↑ ↑

↑ ↑ ↑

–

↑ ↑ ↑

–

↓ ↑

↓

↓ ↓ ↓ ↓

↑ ↑ ↑

↑ ↑

↓ ↓ ↓

↑ ↑ ↑

–

Increasing compaction degree

Increasing content of fines

Increasing penetration index

↓ ↑

PA Increasing binder viscosity

↓

↓ ↑

MA Increasing binder content

Coarser grading

↑

Increasing compaction degree

Increasing binder viscosity

σF TF

Property

Δβt(T)

SMA

Increasing binder content

AC

TSRST

10 20 Temperature T [°C]

Increasing compaction degree

Table 1.

-20

Increasing binder content

Figure 5.

TF

T(Δβt,Max )

0,0

– –

↓ ↓

↑ ↑ ↑ ↑ ↑ ↑ ↑

Changes of test results: : decrease; : increase; ↓: significant decrease; ↑: significant increase (based on data from Eulitz, 1987; Arand et al., 1990, 1998; and Leutner et al., 2000).

comparably fast application of stress by UTST on the other hand. It is unfavourable, that the tensile-strength-reserve concept is based on a comparison of data obtained from tests characterized by different mechanical conditions (in general, the strain rate of the UTST is by the factor 1000 higher than the thermal strain rate associated with cooling during the TSRST) and by different thermal conditions (isothermal for UTST and non-isothermal for TSRST). In future, a more reliable interpretation of results from TSRST and UTST is needed. As concerns distress models for the prediction of low temperature cracking using data obtained from UTST and TSRST the reader is referred to Metha et al. (2000) and Little et al. (2001). 2.5 Impact of compositional asphalt properties on TSRST and UTST results The impact of various compositional asphalt characteristics on the test results stated in TSRST and UTST was investigated in a number of research projects at ISBS (see Eulitz, 1987; Arand et al., 1990, 1998; Leutner et al., 2000; Mollenhauer et al., 2008). From systematic variation 333

of influencing factors the interrelations represented in Table 1 were found for various types of asphalt mixtures (AC, SMA, MA and PA). It can be concluded, on the one hand, that the failure temperature and the temperatures, where the maxima of tensile strength and tensile strength reserve occur are mostly influenced by the binder viscosity. On the other hand, the values of failure stress, tensile strength and the tensile stress reserve are depending on the void content of the tested material, controlled by the asphalt composition and its compaction degree. 3

INTER-RELATIONS TO LOW TEMPERATURE BEHAVIOUR OF BITUMEN

Correlations between binder test results and TSRST and UTST results were investigated for a stone mastic asphalt SMA 11 (for details see Büchler et al., 2008). The results are summarized in Table 2, where the coefficients of correlation are given for the characteristic test parameters. The table indicates that especially the BBR results are correlated to the TSRST results, i.e. the failure temperature TF, the cryogenic stress σcry(–20°C), and the temperature of maximum tensile strength reserve T(Δβt,Max). Further the tensile strength βt at high test temperatures correlates reasonably well with some binder properties (e.g. G* (DSR) or maximum force in the force ductility test). UTST results at lower test temperatures (see results for –10°C and –25°C) are not correlated to binder properties, except the DSR result δ with βt(–10°C). In literature, only poor correlation of results from the Fraass breaking point test and TSRST is reported (see, e.g. Guericke et al., 2001; Lu et al., 2003; Des Croix, 2004; Olard et al., 2004). Correlation coefficients, r2, usually range from 0.42 to 0.72. Comparisons of test results from BBR and TSRST are reported from various authors (e.g. Jung et al., 1994; Lu et al., 2003; Des Croix, 2004; Guericke et al., 2001; Lecomte et al., 2000; and Hesp et al., 2000). Correlation of TSRST fracture temperature and BBR stiffness, S, and m-value determined at –24°C was found to be poor (Lecomte et al., 2000). In contrast, BBR

Table 2. Coefficients of correlation between binder tests and asphalt mix tests for stone mastic asphalt. Tensile strength reserve

UTST TSRST σkry (–20°C)

βt(+20°C)

βt(+5°C)

βt(–10°C)

βt(–25°C)

εF(+20°C)

εF(+5°C)

εF(–10°C)

εF(–25°C)

Δβt,Max

T(Δβt,Max)

Tensile strain

σF

Tensile strength

TF

BBR

DSR

Force ductility

Standard tests

Coefficient of correlation between bitumen characteristics (RTFOT) and asphalt characteristics (unaged) SP R&B Pen Fraass BP El. Rec. Total Energy Energy (20–40 cm) FMax

4 60 71 16 8 0 30

51 6 16 74 50 40 0

13 97 91 0 7 25 75

52 81 76 11 41 61 97

12 79 94 0 8 15 80

54 6 15 50 50 44 0

27 18 30 23 36 18 4

6 58 67 17 8 1 25

7 55 65 22 8 2 23

17 37 40 23 24 7 7

17 29 34 23 22 5 7

35 19 21 38 34 18 0

1 61 86 1 0 1 60

G*(60°C; 1,59 Hz) δ(60°C; 1,59 Hz) S (–16°C) m (–16°C) T (S = 300 MPa) m (S = 300 MPa)

30 33 68 59 49 65

0 81 22 12 6 13

80 0 77 83 78 82

95 11 49 61 67 52

70 0 66 69 73 69

1 87 25 13 8 16

3 54 31 25 12 26

23 39 73 62 51 67

20 44 75 60 53 65

9 49 52 42 31 54

9 47 40 32 19 31

0 71 40 27 18 33

44 7 62 61 57 57

334

0 temperature at maximum tensile strength reserve T( Δβt,max ) [°C]

4

RTFOT - unaged PAV - aged

-5

-15 y = 2E-06x - 30.374 R2 = 0.5564

-20

-25

-30

-35

-40

0 -2 y = 2E-06x - 11.421 R2 = 0.8459

-4 -6 -8 -10 -12

G*/sinδ at T = 30°C [Pa]

8,000,000

7,000,000

6,000,000

5,000,000

4,000,000

3,000,000

2,000,000

1,000,000

8,000,000

7,000,000

6,000,000

5,000,000

4,000,000

3,000,000

2,000,000

1,000,000

0

-14 0

failure temperature TF [°C]

-10

RTFOT - unaged PAV - aged

2

G*/sinδ at T = 30°C [Pa]

Figure 6. Correlation according Hagner (2003) between the binder characteristic G*/sin δ at T = +30°C and the results of TSRST & UTST (fracture temperature TF, and the temperature of maximum tensile strength reserve T(Δβt,max)). Data obtained from Renken et al. (2007).

limiting temperatures are correlated to TSRST failure temperatures by factors ranging from 0.53 to 0.99. BBR limiting temperatures are (i) the temperature TLS where creep stiffness S reaches 300 MPa, (ii) the temperature TLm where the m-value reaches 0.3, and (iii) the temperature TLeps where the fracture strain is 1.3. Correlation was found to be better for notched TSRST specimen. Olard et al. (2004) compared for a set of five different binders (two paving grade binders and three pmB) failure temperature Tε=1% and transition temperature Tbdb from DTT, and fracture toughness KIc and fracture energy GIc resulting from three point bending fracture tests on notched bitumen samples (deformation rate of 1 mm/s, 6 specimen tested per temperature) to two parameters from asphalt mix testing, namely the transition temperature Tbdm (at two different strain rates) from UTST and the failure temperature Tf from TSRST. Olard et al. (2004) emphasized that, in general, repeatability of the tests is poor. As regards correlation of binder testing to asphalt mix testing, they concluded, that the binder parameters Tbdb and Tε = 1% are well correlated with Tf and Tbdm (for the two considered strain rates) from asphalt mix testing, as correlation coefficients range from 0.90 to 0.99. Hence, DTT parameters correlate reasonably well with low temperature mix properties. Contrary, Olard et al. (2004) stated only poor correlation of binder fracture properties, KIc and GIc, to low temperature asphalt properties, Tbdm and Tf. This is in best agreement with similar results known from Hesp et al. (2000), who evaluated eleven RTFOT-aged binders (four paving grade binders and seven pmB). They investigated correlations of DTT temperature Tε=1.3% (at which failure strain reaches 1.3%) to mixture failure temperature of TSRST measurements, Tf, on both regular and notched samples. Correlation coefficients for the un-notched samples account for 0.53, in contrast to 0.83 for the notched samples. Hagner (2003) found a correlation between the quotient G*/sin δ measured in the DSR at a temperature of 20°C and the TSRST fracture temperature TF, as well as the temperature of maximum tensile strength reserve T(Δβt,max). He concluded, that low values of G*/sin δ will improve the resistance against low-temperature-cracking. Figure 6 shows the application of this theory on the data presented by Renken et al. (2007). 4

SUMMARY

This paper represents a review on two static test procedures to assess low temperature behaviour of asphalt materials, i.e. the thermal strain restrained specimen test (TSRST) and the uniaxial tensile stress test at low temperature conditions (UTST). In detail, the test device and the test procedures 335

are presented, and the test conditions as proposed by the draft European Standard prEN 12697-46 are discussed. Moreover, results from various research projects are compared with respect to the inter-relations from asphalt mix testing to binder testing, where a strong correlation to BBR tests were found for TSRST results. REFERENCES Arand, W. 1987. Influence of bitumen hardness on the fatigue behavior of asphalt pavements of different thickness due to bearing capacity of subbase, traffic loading, and temperature. Proc., 6th Int. Conf. on Structural Behavior of Asphalt Pavements, Univ. of Michigan, Ann Arbor, Michigan, pp. 65–71. Arand, W. 1993. Low Temperature Cracking in Polymer Modified Binders. Journal of the Association of Asphalt Paving Technologists, Volume 62. Arand, W. 1996. Funktionelle Anforderungen an Bitumen und Asphalt—Prüftechnische Ansprache des Verformungswiderstandes, der Rissresistenz und der Ermüdungsbeständigkeit von Asphalten. Bitumen, Jahrgang 58/4. Arand, W. und Lorenzl, H. 1995. Einfluß der Bitumenhärte auf das Ermüdungsverhalten von Asphaltbefestigungen unterschiedlicher Dicke in Abhängigkeit von der Tragfähigkeit der Unterlage, der Verkehrsbelastung und der Temperatur, Teil 2. Schriftenreihe Forschung Straßenbau und Straßenverkehrstechnik des Bundesministers für Verkehr, Abteilung Straßenbau, 696, Bonn-Bad Godesberg, Deutschland. Arand, W., Dörschlag, S. und Pohlmann, P. 1989. Einfluß der Bitumenhärte auf das Ermüdungsverhalten von Asphaltbefestigungen unterschiedlicher Dicke in Abhängigkeit von der Tragfähigkeit der Unterlage, der Verkehrsbelastung und der Temperatur. Schriftenreihe Forschung Straßenbau und Straßenverkehrstechnik des Bundesministers für Verkehr, Abteilung Straßenbau, 558, Bonn-Bad Godesberg, Deutschland. Arand, W., and Hase, M. 1990. Verhalten von Gussasphalten bei tiefen Temperaturen; Teil A: Bewertungshintergrund zur Beurteilung von Gußasphalten, Teil B: Einfluß kompositioneller Merkmale. AiF-Forschungsvorhaben Nr. 7191; Braunschweig, Germany. Arand, W., Steinhoff, G., Eulitz, J., und Milbradt, H. 1984. Verhalten von Asphalten bei tiefen Temperaturen, Entwicklung und Erprobung eines Prüfverfahrens. Schriftenreihe Forschung Straßenbau und Straßenverkehrstechnik des Bundesministers für Verkehr, Abteilung Straßenbau, Heft 407, BonnBad Godesberg, Deutschland. Arand, W., Zander, U., Renken, P., and Büchler, S. 1998. Einfluss des Bindemittelgehaltes auf das mechanische Verhalten von Splittmastixasphalten mit unterschiedlichen stabilisierenden Zusätzen. BMV-Forschungsvorhaben Nr. 7.167 G 95 F, Braunschweig, Germany. Büchler, S., Renken, P., and Mollenhauer, K. 2008. Relation between rheological bitumen characteristics and the resistance of asphalt against fatigue and cold temperatures. Proc., 4th Eurasphalt & Eurobitume Congress, 21–23 May 2008, Copenhagen, paper 402–077. Collop, A.C., Choi, Y., Airey, G.D., and Elliott, R.C. 2004. Development of a combined ageing/moisture sensitivity laboratory test. European Asphalt Pavement Association EAPA, Proc., Eurasphalt & Eurobitume Congress, 12–14 May 2004, Vienna. Des Croix, P. 2004. Mechanical fatigue and thermal cracking tests to evaluate pavement performance and comparison with binder properties. European Asphalt Pavement Association EAPA, Proc., Eurasphalt & Eurobitume Congress, 12–14 May 2004, Vienna. Eulitz, H. 1987. Kälteverhalten von Walzasphalten. Prüftechnische Ansprache und Einfluss kompositioneller Merkmale. Schriftenreihe des Instituts für Straßenwesen, Technische Universität Braunschweig, Heft 7. Fabb, T.R.J. 1974. The influence of mix composition, binder properties and cooling rate on asphalt cracking at low-temperature. Journal of the Association of the Asphalt Paving Technologists, AAPT, 43, pp. 285–331. Guericke, R., and Höppel, H.-E. 2001. ARBIT-Untersuchungsprogramm 1998/99 an 36 Bindemitteln. Bitumen 1/2001.Hagner, T. 2003. Untersuchung und Bewertung von bitumenhaltigen Bindemitteln für Asphalt mittels Dynamischem Scher-Rheometer. Schriftenreihe des Instituts für Straßenwesen, Technische Universität Braunschweig, Heft 19. Hesp, S.A.M., Terlouw, T., and Vonk, W.C. 2000. Low Temperature Performance of SBS-Modified Asphalt Mixes. Association of Asphalt Paving Technologists. Holewinski, J.M., Soon, S.-C., Drescher, A., and Stolarski, H. 2003. Investigation of factors related to surface-initiated cracks in flexible pavements. Minnesota Department of Transportation, St. Paul, Minnesota.

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Jung, D.H., Vinson, T.S. 1994. Low-Temperature Cracking: Test Selection. Strategic Highway Research Program, SHRP-A-400, Washington D.C. Kanereva, H.K., Vinson, T.S., and Zeng, H. 1994. Low-Temperature Cracking: Field Validation of the Thermal Stress Restrained Specimen Test. Strategic Highway Research Program; SHRP-A-401; Washington D.C. Kluttz, R.Q., and Dongre, R. 1997. Effect of SBS polymer Modification on the Low-Temperature Cracking of Asphalt Pavements. In Asphalt Science and Technology, Arthur M. Usmani (ed.), Marcel Dekker Inc., New York, pp. 217–233. Leutner, R., Renken, P., and Lüthje, U. 2000. Nutzungsdauer von Asphaltbefestigungen in Abhängigkeit vom Verdichtungsgrad. AiF-Forschungsvorhaben Nr. 11239, Braunschweig, Germany. Little, D.N., Lytton, R.L., Williams, D., and Chen, C.W. 2001. Microdamage healing in asphalt and asphalt concrete, Volume I: Microdamage and microdamage healing, Project Summary Report, FHWA-RD-98-141, Washington, D.C. Lu, X., Isacsson, U., and Ekblad, J. 2003. Influenxce of Polymer Modification on Low Temperature Behaviour of Bituminous Binders and Mixtures. 6th RILEM Symposium Performance Testing and Evaluation of Bituminous Materials, pp. 435–449, Zürich. Metha, Y.A., and Christensen, D.W. 2000. Determination of the Linear Viscoelastic Limits of Asphalt Concrete at Low and Intermediate Temperature. In Journal of the American Association of Asphalt Paving Technologists AAPT, Vol. 69. Mollenhauer, K., Büchler, S., and Renken, P. 2008. Testing of cold characteristics of asphalt. Proc., 4th Eurasphalt & Eurobitume Congress, 21–23 May 2008, Copenhagen, paper 402–071. Monismith, C.L., Secor, G.A., and Secor, K.E. 1965. Temperature induced stresses and deformations in asphalt concrete. Journal of the Association of Asphalt Paving Technologists, AAPT, 34, Ann Arbor, Mich., pp. 248–285. Myers, L., Roque, R., and Ruth, B.E. 1998. Mechanisms of surface-initiated longitudinal wheel path cracks in high-type bituminous pavements. Asphalt Paving Technology, Vol. 67, p. 401–432. Olard, F., Di Benedetto, H., Dony, A., Vaniscote, J.C. 2003. Properties of Bituminous Mixtures at Low Temperatures and Relations with Binder Charateristics. 6th RILEM Symposium Performance Testing and Evaluation of Bituminous Materials, pp. 450–457, Zürich. Renken, P., Büchler S., and Mollenhauer, K. 2007. Einfluss von modifizierten Bitumen auf die Kälteund Er-müdungseigenschaften von Asphalt und deren Veränderung während der Nutzungsdauer. Forschung Straßenbau und Straßenverkehrstechnik, 991, Bonn, Germany. Spiegl, M., Wistuba, M., Lackner, R., and Blab, R. 2005. Evaluation of temperature associated cracking in asphalt concrete by means of performance based laboratory testing. Proc., 7th Int. Conf. on Bearing Capacity of Roads and Airfields, 27–29 June 2005, Trondheim, Norway. Vinson, T.S., Janoo, V.C., and sHaas, R.C.G. 1989. Summary Report on Low Temperature and Thermal Fatigue Cracking. Strategic Highway Research Program, SHRP-A-/IR-90-001, Washington D.C. Wistuba, M., Lackner, R., Blab, R. & Spiegl, M. 2006. Low-temperature performance prediction of asphalt mixtures used for Long-Life Pavements—new approach based on fundamental test methods and numerical modelling. International Journal of Pavement Engineering, Vol. 7, No. 2, pp. 121–132, Taylor & Francis. Wistuba, M., and Spiegl, M. 2007. Asphalt pavements in cold climates—A systematic approach for the assessment of cracking resistance. Proc., Int. Conf. on Advanced Characterization of Pavement and Soil Engineering Materials, Athens, 20–22 June 2007, Taylor & Francis Group, Loizos, Scarpas & Al-Qadi (eds), London, ISBN 978-0-415-44882-6.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Ageing of stone mastic asphalt and evaluation of cracking resistance S. Büchler, K. Mollenhauer, M. Wistuba & P. Renken Braunschweig Pavement Engineering Centre (ISBS), Technische Universität Braunschweig, Germany

ABSTRACT: The influence of binder characteristics on the cracking resistance of stone mastic asphalt (SMA) wearing courses was recently investigated at the Braunschweig Pavement Engineering Centre (ISBS), Germany. Variations of SMA mixtures were produced using 7 different binder products. From the virgin and by a special procedure aged mixtures prismatic specimens were produced. Then the specimens were subjected to thermal stress restrained specimen tests, uniaxial tensile stress tests and cyclic tensile stress tests. The lowtemperature-test results are shifted up to 5 K, caused by the ageing procedure. The effect of ageing on fatigue-properties depends on the temperature conditions. At low temperatures, it leads to a reduction in the endured number of load cycles to fatigue failure, whereas at the higher test temperatures they are improved. It is emphasized, that the application of suitable test conditions is of utmost importance when performing laboratory tests to characterize the mechanical properties of asphalt mixtures.

1

INTRODUCTION

The long-term performance and durability of asphalt pavements is highly controlled by their resistance to cracking. An important factor influencing the susceptibility to cracking of asphalt surface courses is the long-term-ageing due to UV radiation and oxidative hardening of the bituminous binder. Various test methods are known for simulating the ageing behaviour of bituminous materials in the laboratory. Generally, ageing simulation methods for asphalt binders use increased test temperature and/or pressure to speed up the ageing process in the laboratory, by providing a flow of air or oxygen, and/or by stimulating the diffusion of oxygen in the binder (Verhasselt, 2002). Accelerated tests are used to simulate the short-term and the long-term ageing of asphalt materials assuming that the degree of laboratory conditioning resulting from accelerated ageing simulation techniques approximate the degree of long-term ageing as observed from in-field environmental conditions. Typically, binder ageing simulation tests as adopted within the Strategic Highway Research Program (SHRP) are used, like Thin-Film Oven Test, Rolling Thin-Film Oven Test, and the Pressure Ageing Vessel. Because there is no direct measure for asphalt ageing, physical tests are performed on the conditioned bitumen successively to ageing simulation, and changes in the rheological properties due to ageing simulation are quantified in terms of rheological material parameters. Unfortunately, laboratory test methods for the conditioning of asphalt mix samples are hardly known. Such accelerated ageing techniques are often based on the exposure of compacted asphalt mix specimens to hot air for a period of several days (see, e.g., Bell, 1989). Disadvantageously such techniques provoke inhomogeneous conditioning of the sample as the oxidative ageing is limited to the superficial zone of the specimen’s cross-section. This paper presents a new technique for the conditioning of asphalt mixtures where a homogeneous ageing of the mix is achieved.

339

2

EXPERIMENTAL WORK

2.1 Material The presented test results are based on laboratory investigations performed on stone mastic asphalt (SMA) in order to examine the influence of polymer modification and long-term ageing on the low-temperature and fatigue properties. SMA 8 (maximum grain size of 8 mm) were produced in the laboratory using one specific aggregate grading, but seven different bitumen. The produced asphalt mixtures and the most important mix properties are summarized in Table 1. For the conduction of performance-based laboratory tests the asphalt mixtures were compacted in the laboratory to slabs by means of the German steel roller compactor (see Renken 2000). To avoid bias effects due to differing void contents, all mixtures were compacted until the slabs reached nearly the same void content (±0,3 vol-%). Finally, prismatic-shaped specimens of the size 40 × 40 × 160 mm3 were sawn from the asphalt slabs. 2.2 Ageing procedure Long-term ageing in the laboratory was simulated such, that homogenous ageing of the asphalt mix components was achieved. For this purpose, the ageing procedure developed within SHRP (Bell, 1989) was modified: The loose non-compacted bitumen-covered Properties of the SMA 8—mixtures.

SMA Binder characteristics: Binder category* Polymer type Softening point R&B [°C] Penetration [1/10 mm] Fraass breaking point [°C] Elastic recovery [%] Force ductility: deformation energy [J] Force ductility: peak force [N] Bending Beam Rheometer: S [MPa], m [–] @ T = −16°C Dynamic Shear Rheometer: G* [Pa]/ϕ [°] @ T = 60°C, f = 1,59 Hz Mix properties: Binder content [mass-%] Bulk density [g/cm3] Grading

1–2

2–1

2–3

2–5

3–1

4–2

5–1

10/40– 65 SB

20/60– 55 SBS

20/60– 55 SBS

20/60– 55 SB

45/80– 50 SBS

40/100– 65 H SB

50/70 −

64.2 30

57.2 35

62.2 43

58.5 57

50.0 57

71.0 62

48.9 66

−11.5 74.5

−11.8 63.0

−16.0 78.0

−20.9 75.5

−17.0 71.0

−20.7 90.5

−16.5 15.3

2.0691

0.5839

1.0625

0.6618

0.6618

2.7387

0.0488

5.3

3.7

2.5

1.5

1.2

1.4

0.8

223.4/ 0.32

254.4/ 0.33

202.3/ 0.35

116.2/ 0.40

111.1/ 0.43

85.1/ 0.44

172.1/ 0.36

25,439/ 66.4

12,242/ 76.7

10,828/ 71.7

9,793/ 68.3

6,377/ 79.0

11,285/ 56.1

2,846/ 86.6

6.6 2.469

maximum density [g/cm3] void content [vol-%]

2.546 3.02

100

passing [%]

Table 1.

80 60 40 20 0 0.09

0.25

0.71

2

5

8 11.2 16 Sieve [mm]

* The binder categories were transferred from the former German classification system.

340

Figure 1. Effects of a change in temperature conditions and in the duration of exposure on the softening point Ring & Ball.

aggregate particles of the asphalt mix are spread on a grid and exposed to hot air for several days. In order to find the most suitable ageing conditions, the temperature conditions and the time duration of hot air exposure was varied and the results of this variation on the ageing degree was investigated (see Figure 1). It was the aim to reach an increase of the softening point Ring & Ball by 12°C of the virgin binder. This could be reached by a temperature of T = 80°C for a duration of 4 days. The aged binder was further tested by conventional and performance based methods and compared with standard-aged (RTFOT, PAV) binder test results (for a more detailed description the reader is referred to (Renken et al., 2007)). 2.3 Low temperature tests As concerns the low temperature testing of the compacted asphalt mixtures, thermal strain restrained specimen tests (TSRST), uniaxial tensile stress tests (UTST), and uniaxial cyclic tensile stress tests (UCTST) were conducted on prismatic specimens (for specimen preparation see Chapter 2.1) according to the German specifications (FGSV, 1994) and the draft European pre-Standard preEN 12697-46. 2.4 Thermal strain restrained specimen test As to the thermal strain restrained specimen test (TSRST), the specimen is held at a constant length, while its temperature is decreased with a constant cooling rate. Because of the prohibited thermal shrinkage, the specimen is object to a (cryogenic) tensile stress. At the Braunschweig Pavement Engineering Centre, the standard starting temperature is always T0 = +20°C, and a temperature rate of dT = −10 K/h is applied. During the test, the core temperature of the specimen shows a time lag to the air temperature in the test chamber. For this reason, a specimen dummy is placed in the temperature chamber which gives the correct specimen temperature. As a result from the TSRST, the temperature-dependent cryogenic stress σcry(T) [MPa], the failure stress σcry,F [MPa], and the failure temperature TF [°C] are recorded. The increase of cryogenic stress is exemplarily shown in Figure 2. 2.5 Uniaxial tensile stress test As concerns the uniaxial tensile stress test (UTST), the specimen is subjected to a timedependent strain by pulling the specimen with a prescribed deformation rate, which is normally defined as 1 mm per minute. For the specimen length of 160 mm, the strain rate results to 104.2 ⋅ 10–6 1/s. UTST are conducted at various test temperatures, at the Braunschweig 341

Tension stress σ [MPa]

6,0 5,0

Tensile Strength βt (T)

Δβ 4,0 t,max σF

Tensile Strength Reserve Δβt (T)

3,0 2,0

Cryogenic Stress σcry (T)

1,0

-30

TF

-20

-10

T(Δβt,Max )

0,0

0

10 20 Temperature T [°C]

Figure 2. Principle of evaluating the tensile strength reserve from the test graphs of the UTST and the TSRST in the temperature-stress diagram.

Pavement Engineering Centre usually at test temperatures of +20°C, +5°C, −10°C and −25°C. During the test the deformation of the specimen and the applied load is measured. At low temperatures between –25°C and –10°C the stress increase is almost linear and the specimen fails spontaneously by brittle fracturing. During the UTST, the tensile force and the resulting displacement are measured. As a result of the UTST, the tensile strength βt and the failure strain εF are calculated from the force and the displacement at failure. The tensile strength βt [MPa] is calculated by dividing the measured tensile force at failure by the initial area of the specimen cross-section. The failure strain εF [‰] is calculated by the measured deformation at failure divided by the initial length of the specimen. The higher the test temperature, the slope of the stress increase is less distinct, but higher total strains are endured. As the asphalt behaviour becomes increasingly ductile, the specimen does not fail spontaneously. In this case, the tensile strength βt is defined as the maximum tensile stress, and the failure strain εF is the strain corresponding to the tensile strength. The impact of the test temperature on the tensile strength is finally visualized by plotting the obtained tensile strengths against the test temperature. A cubic spline function is used to interpolate (or extrapolate) the tensile strength of the material over the full temperature range (Figure 2). Empirically derived functions for the extrapolation beyond temperatures below −25°C and above +20°C, respectively, are given by (Renken et al., 2007): βt (T = −40°C ) = 0.9 ⋅ βt (T = −25°C),

and

βt (T = + 34°C ) = 0,5 ⋅ βt (T = + 25°C)

(1) (2)

2.6 Calculation of the tensile strength reserve by combining test results from TSRST and UTST By combining the test results from the TSRST and from the UTST, the tensile strength reserve is found, a parameter commonly used to rank the low temperature cracking resistance of asphalt mixtures. According to (Arand et al., 1984), the tensile strength reserve is a measure of the capacity of traffic stress that an asphalt material can support additionally to cryogenic stress without any failure. For determination of the tensile strength reserve, the stress curve induced by thermal shrinkage—as derived from TSRST—is compared to the respective tensile strength curve— as derived from UTST—for the tested material. The tensile strength reserve Δβt is referred to as the difference between the cryogenic stress σcry obtained from the TSRST at a certain temperature and the respective material strength βt(T) given by the UTST, reading 342

Figure 3. Change in the low temperature properties stated by TSRST and UTST for SMA in consequence of the laboratory long-term-ageing process.

343

Δβt (T) = βt (T ) − σ cry (T ).

(3)

Consequently, the curve of the tensile strength reserve is derived for the whole temperature range (see Figure 2). The tensile strength reserve is used to assess the additional trafficinduced tensile stresses that the asphalt is still able to absorb. The resulting maximum tensile strength reserve Δβt,Max [MPa] and the corresponding temperature T(Δβt,Max) are key material parameters to predict the capacity to low-temperature cracking. 2.7 Uniaxial cyclic tensile stress test The uniaxial cyclic tensile stress test as performed in this study is a homogeneous forcecontrolled fatigue test at low temperatures. The prismatic asphalt specimen is loaded by a sinusoidal cyclic tensile stress at a constant temperature. For this purpose, the specimen is glued to steel adapters. After joining it with the load device at +20°C, it is cooled down to test temperature, while the test machine balances the thermal strains. After reaching the test temperature, the cyclic force is generated by a hydraulic valve and measured in a load cell and a cyclic load is applied. The deformation of the specimen is detected by two LVDT, which enables the analysis of the strain signal to calculate the visco-elastic response of the specimen and the initial stiffness modulus |E|, which is registered at the beginning of the loading. The test ends with specimen fracture and the number of endured load cycles NF is recorded. Because the test as performed in this study is intended to simulate the fatigue behaviour of asphalt surface materials at low temperature conditions (Arand, 1987), the test was conducted at temperatures +5, −10 and −20°C. The cyclic loading is prescribed by a constant bottom tensile stress to simulate the loading by cryogenic stress due to prohibited thermal strain, as well as the superimposed sinusoidal load simulating the traffic, defined in this study by a frequency of f = 10 Hz and a stress difference of Δσ = 1.6 MPa. The applied value of cryogenic stress is determined by conducting a TSRST with a constant temperature decrease (ΔT = −10 K/h). The applied values can be derived from Figure 3. 3

TEST RESULTS

3.1 Results from static tests The diagrams summarized in Figure 3 illustrate the influence of ageing on the low temperature behaviour for all seven SMA 8 mixtures investigated. A temperature shift is observed due to ageing, as the curves of the cryogenic stress, the tensile strength as well as the tensile strength reserve are shifted to a higher temperature range. Hence, in consequence of ageing, a decrease in the material’s resistance to cracking is realized. The asphalt type SMA 4-2, which contains a highly polymer-modified bitumen of the type 40/100-65 is characterized by a high tensile strength, a moderate stress development with respect to cryogenic stresses and thus a high tensile strength reserve at low temperatures. From the comparison of the polymer-modified binders used, i.e. 10/40-65, 25/55-55 and 40/80-50, it can be concluded that low-viscous binders generally show a better low-temperature behaviour than binders with high viscosity. Note the wide range of test results for the three SMA with different binders of the cathegory 20/60-55. Obviously, the low-temperature performance properties of a defined asphalt mix may vary significantly. In Figure 4 the change in low-temperature test results in consequence of the laboratory ageing process are given (the shift is represented by arrows), i.e. failure stress and failure temperature from TSRST, and the maximum tensile strength reserves. It can be seen, that the failure temperature increases due to ageing in the range of 0.7°C (SMA 1-2) to 3.1°C (SMA 5-1). The shift of the failure stress stated in TSRST shows various directions. The failure stress decreases for SMA 1-2, SMA 2-1 and SMA 2-3, which contain binders of higher viscosity as characterised by low penetration values and high BBR-stiffness. Contrary, the other SMA variations show an increase in failure stress. Similar results are obtained for the tensile strength reserve. The temperatures that correspond to the maximum tensile strength reserve 344

max. tensile strength reserve ΔβT,max [MPa]

5.5

failure stress σF [MPa]

5.0

4.5

4.0

3.5

6.5 SMA 1-2 SMA 2-3 SMA 3-1 SMA 5-1

6.0 5.5

SMA 2-1 SMA 2-5 SMA 4-2

5.0 4.5 4.0 3.5 3.0

3.0 -40

-35

-30

-25

-20

-15

-15

-10

failure temperature TF [°C]

-5

0

5

temperature T(Δβ T,max ) [°C]

stiffness modulus |E*| (T = +5°C) [MPa]

Figure 4. Shift of TSRS T results and the maximum tensile strength reserves in consequence of the laboratory ageing process.

18000 initial aged

16000 14000 12000 10000 8000 6000 4000 2000 0 1-2

2-1

2-3

2-5

3-1

4-2

5-1

SMA mixture

Figure 5.

Stiffness modulus |E*| at test temperature T = 5°C for initial and aged SMA mixtures.

show higher values up to 5 K for the aged SMA than for the initial ones. For most SMA a decrease of the maximum tensile strength reserve is observed due to ageing. The decrease in tensile strength is explained by dominant brittle performance properties. 3.2 Results from cyclic fatigue testing Figure 5 shows the stiffness modulus measured at a temperature of T = +5°C for both the initial and aged SMA mixtures. While the stiffness increases due to ageing between 5 and 13% for most SMA, the stiffness decreases of about 3% for the mixtures SMA 2-1 and SMA 2-5. A statistical analysis shows no difference in initial and aged SMA mixtures 2-1 and 2-5, so that this decrease is explained by data scatter. In Figure 6 the numbers of endured load cycles to failure NF are given, as resulting from fatigue tests on virgin and aged SMA mixtures at three different temperature levels. All SMA mixtures but one (SMA 2-1) showed at T = +5°C an increased number of endured 345

200.000 150.000 100.000

0 -10 °C

+5 °C

-20 °C

-10 °C

0

150.000

181.791

SMA 2-5

100.000 50.000 0

-20 °C

-10 °C

+5 °C

-20 °C

-10 °C

3.256

40.000

4.730

60.000 20.000

800.000 700.000 600.000 500.000

aged initial

400.000 300.000 200.000 100.000

0

0 -20 °C

-10 °C

+5 °C

-20 °C

485.701

SMA 5-1 500.000

10.147

32.593

200.000 100.000

aged initial

17.293

300.000

+5 °C

139.128

400.000

-10 °C

temperature T [°C]

254.015

number of endured load cycles N

temperature T [°C] 600.000

SMA 4-2

5.286

80.000

SMA 3-1

864.863

900.000

489.171

100.000

110.401

120.000

71.041

140.000

1.000.000

567.478

aged initial

573.425

177.405

160.000

+5 °C temperature T [°C]

number of endured load cycles N

180.000

81.302

number of endured load cycles N

temperature T [°C] 200.000

aged initial

12.849

25.095

12.115

50.000

221.649 200.000 135.694

SMA 2-3

250.000

108.550

aged initial

150.000 100.000

+5 °C temperature T [°C]

number of endured load cycles N

172.426

160.675

200.000

200.507

250.000

64.108

number of endured load cycles N

temperature T [°C]

18.456

-20 °C

44.424

50.000

0

14.136

20.000

9.384

40.000

aged initial

37.646

32.658

60.000

SMA 2-1 250.000

39

80.000

59.926

69.115

100.000

253.921

120.000

300.000

106.512

aged initial

45.054

number of endured load cycles N

123.170

SMA 1-2

8.543

number of endured load cycles N

140.000

0 -20 °C

-10 °C

+5 °C temperature T [°C]

Figure 6. Fatigue test results on all SMA mixtures investigated: number of endured load cycles until failure NF at 3 test temperatures.

load cycles after ageing. At the lowest test temperature of –20°C, NF decreased due to ageing (except of SMA 2-1). At T = −10°C the asphalt mixtures SMA 1-2, SMA 2-3 & SMA 2-5 show an increase of NF whereas the mixtures SMA 2-1, SMA 3-1, SMA 4-2 & SMA 5-1 endure lower numbers of load cycles. It can be observed that these numbers highly depend of the specific test temperature. Four SMA of the unaged mixtures indicate an increase in NF with decreasing temperature. However, the mixtures with the highest stiffness moduli, i.e. SMA 1-2, SMA 2-1, and SMA 5-1, show a maximum value of NF at –10°C, while it is significantly reduced for a temperature of –20°C. 346

As to the aged mixtures, a similar behavior is stated for the two SMA with lowest stiffness moduli, i.e. SMA 3-1 and SMA 4-2, showing an increasing fatigue resistance with decreasing temperature. All other aged SMA inhibit a maximum fatigue resistance at –10°C. 3.3 Discussion on the fatigue life increase after ageing By comparing the number of endured load cycles NF for specimens made of virgin material and for specimens made out of material that has been exposed to the ageing before an interesting result was achieved: As presented above, in some cases the fatigue life increases. For interpretation of the effects on the ageing procedure on the fatigue life determination, the mode of loading has to be taken into account carefully. The uniaxial cyclic tensile stress test is a force-controlled fatigue test. In this study, a predefined stress amplitude was applied on all tested asphalts at all temperatures, independently from material properties. The use of one single stress amplitude for all materials leads to varying load conditions: The higher the stiffness modulus of the asphalt material (due to binder viscosity, temperature and/or ageing properties), the lower is the cyclic strain response of this material, and thus, the less energy is dissipated during one load cycle. For this reason, the ranking of the SMA according to the stiffness modulus is similar to the observed ranking of the number of load cycles NF at a temperature of T = +5°C. In detail, the mixtures with highest stiffness moduli, i.e. SMA 1-2, and SMA 2-1 also show the highest numbers of load cycles NF at +5°C whereas the mixtures with lowest stiffness moduli, i.e. SMA 4-2 and SMA 3-1, show shortest fatigue life. However, with decreasing temperature another factor influences the test results importantly, i.e. the constant bottom stress level of the stress amplitude as derived from TSRST. The development of cryogenic stress in TSRST is dominated by the stiffness properties of the tested material. For this reason, the SMA mixtures which inhibit a high stiffness modulus show highest cryogenic stresses in TSRST. If the temperature and material dependent cryogenic stress from TSRST is used as a stress determining test condition in the fatigue test, the asphalt mixtures with high stiffness modulus are loaded with a higher stress level. Especially the test results obtained at –20°C again indicate a ranking similar to the ranking of the stiffness modulus. At this temperature, the mixture with the lowest stiffness, i.e. SMA 4-2, endures the highest number of load cycles, whereas the mixture with the highest stiffness modulus, i.e. SMA 2-1, fails after a few load cycles already. 4

CONCLUSIONS

The low temperature behavior of 7 SMA mixtures was tested by means of a set of experiments, uniaxial tensile stress test (UTST), tensile strain restrained specimen test (TSRST), and uniaxial cyclic tensile stress test (UCTST). The SMA mixtures investigated differ in the used binder products, whereas other componential properties were kept constant. The asphalt materials were tested in virgin condition as well as in an aged condition. For the purpose of ageing a new laboratory ageing procedure was introduced based on accelerated ageing of the loose asphalt mixture by exposure to hot air. From the test results obtained the following conclusions can be drawn for characterization of the impact of ageing on the cracking resistance: • The ageing procedure causes a shift of the test results of UTST and TSRST to higher temperatures: The failure temperature in the TSRST increases by a temperature of up to 5 K. • The tensile strength increases at high test temperatures and decreases at low test temperatures. The binder aging results in a higher asphalt viscosity. At high temperatures (+5°C, +20°C) the applied strain rate results in a faster stress increase and a higher failure strength is recorded. At low test temperatures, the material failure results from its brittleness which increases with increasing viscosity. The asphalt material’s resistance to cyclic loading significantly depends on the test temperature: At high temperature, the endured number of number of load cycles is increased by ageing, 347

whereas at low temperatures, the aged asphalts show a decreased fatigue resistance. This can be explained by the loading condition applied in the UCTST: The same applied cyclic stress value causes a higher strain response in asphalt mixtures with low stiffness modulus and thus a higher consumption of energy which leads to a shorter fatigue life. At low test temperatures, the effect of the bottom value of cyclic loading comes into account. As mixtures with low stiffness modulus showed comparably small cryogenic stress levels in this study, they are less loaded and show a higher fatigue resistance than the mixtures with high stiffness modulus. Further conclusions can be drawn from the results on the SMA with varied binder products: • The results of the low-temperature tests depend highly on the used binder type but still vary considerably if binder products of the same type are considered. • The results on SMA with polymer modificated binders were less influenced by ageing than the results of SMA with unmodified binders. All results showed the importance of the consideration of the test temperature for the interpretation of performance-tests as the UCTST. Ageing seems to have a positive influence on the cracking resistance when a temperature of +5°C is applied for testing. This observation can be explained by the varying levels of energy dissipation for materials with varied stiffness moduli as the loading mode used in UCTST is force-controlled. This effect is superposed at low temperatures by the impact of the cryogenic stress used as bottom stress value, which is higher at asphalt mixtures with high stiffness modulus. Thus, the SMA mixtures with low stiffness moduli showed better crack resistance at the test temperature of –20°C. ACKNOWLEDGEMENT The authors want to thank the German Federal Ministry of Transport, Building and Urban Affairs, supported by the Research Society for Highway and Traffic Engineering for funding the research project (Renken et al., 2007). The colleagues of the scientific and technical staff of the Braunschweig Pavement Engineering Centre (ISBS) are gratefully acknowledged for their scientific input and accurate laboratory work. REFERENCES Arand, W., Steinhoff, G., Eulitz, J., und Milbradt, H. 1984. Verhalten von Asphalten bei tiefen Temperaturen, Entwicklung und Erprobung eines Prüfverfahrens. Schriftenreihe Forschung Straßenbau und Straßenverkehrstechnik des Bundesministers für Verkehr, Abteilung Straßenbau, Heft 407, BonnBad Godesberg, Germany. Arand, W. 2004. Technical test specification: Resistance of asphalt to fatigue at medium and low temperatures—swelling tensile test, 3rd Eurasphalt & Eurobitumen Congress, Vienna. Arand, W., Rubach, K., and von der Decken, S. 1996. Grundlegende Untersuchungen über den Einfluss der Zusammensetzung auf die Ermüdungsbeständigkeit von Walzasphalten mittels systematischer Variation kompositioneller Merkmale zur Schaffung eines quantitativen Bewertungshintergrundes, Forschung Straßenbau und Straßenverkehrstechnik, No. 717, Bonn, Germany. Bell, C. 1989. “Summary Report on Ageing of Asphalt-Aggregate Systems”. SHRP-A/IR-89-004. 1989 FGSV, 1994, Technische Prüfvorschrift—Verhalten von Asphalten bei tiefen Temperaturen, FGSV-Verlag, Köln, Germany. Hopman, P., Kunst, P., and Pronk, A. 1989. A Renewed Interpretation Model for Fatigue Measurement. Verification of Miner’s Rule, 4th Eurobitume Symposium, Vol. 1, Madrid. 4–6 October 1989, pp. 557–561. Renken. P. 2000: Influence of specimen preparation onto the mechanical behaviour of asphalt aggergate mixtures; 2nd Eurasphalt & Eurobitume Congress. Barcelona 2000. Renken, P., Büchler, S., and Mollenhauer, K. 2007. Einfluss von modifizierten Bitumen auf die Kälteund Ermüdungseigenschaften von Asphalt und deren Veränderung während der Nutzungsdauer, Forschung Straßenbau und Straßenverkehrstechnik, No. 991, Bonn, Germany. Verhasselt, A. 2002. Long-term ageing—Simulation by RCAT ageing tests. Proc. of the 9th Int. Conf. on Asphalt Pavements, Copenhagen, Denmark, Aug. 17–22, 2002.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Fatigue resistance of hot mix asphalt at low temperatures— Is there a way to reduce the test efforts? K. Mollenhauer & M. Wistuba Braunschweig Pavement Engineering Centre (ISBS), Technische Universität Braunschweig, Germany

ABSTRACT: The fatigue resistance of hot-mix asphalt is usually assessed by means of cyclic laboratory tests. According to the European standard EN 13108-20 the fatigue properties for one single asphalt concrete mixture are derived at one temperature and one frequency. Based on the test results gained by applying three load amplitudes, a fatigue function is developed and used as an indicator for the pavement’s durability. In reality, the asphalt pavement life depends on further conditions as vehicle speeds and pavement temperatures. Hence, the laboratory test program is usually extended to more test temperatures and frequencies. Consequently the assessment of fatigue properties becomes a time consuming and cost intensive issue. This paper analyses possible ways to reduce the effort in fatigue testing without downgrading the quality of the derived fatigue function by means of Uniaxial Cyclic Tensile Stress Tests at varied frequencies and temperatures on six different asphalt mixtures. 1

INTRODUCTION

1.1 General overview on the assessment of stiffness and fatigue properties The stiffness and fatigue characteristics of the individual pavement layers and the sub-grade are important properties in order to estimate the appropriate lifetime of the bound and unbound layers. For assessing the asphalt material properties in the laboratory, specimen of compacted hot mix asphalt are usually subjected to oscillatory loading in a cyclic test. Basically, the test conditions are selected to reach similar loading conditions as estimated for the point in the pavement where the maximum tensile stress is assumed to occur (either on top of the pavement outside the load axis, as assumed in this study, or respectively, at the bottom of the asphalt pavement in the load axis, as presumed conventionally). The loading conditions represented by the load amplitude, the frequency and the ambient temperature are kept constant during the test. Generally, the load amplitude during the test is intended to correspond to the horizontal bending stress in the pavement due to axle loading. The test frequency is correlated with vehicle speed, and the ambient test temperature corresponds to the pavement temperature. Because of the vast varieties of vehicle types, axle loads, and vehicle speeds and ever changing pavement temperatures, various loading scenarios are examined during laboratory fatigue testing, and the interrelation of loading conditions and material fatigue life is determined. This makes the assessment of fatigue properties a rather time consuming and cost intensive issue. The mechanisms of crack initiation and propagation in the laboratory test may be different from observations in real pavement structures. However, material fatigue usually results in an important degradation of the pavement structure, and hence, the assessment of material characteristics by means of fatigue testing is of crucial importance to ensure adequate structural pavement design. Various test methods are applied for stiffness and fatigue testing of asphalt materials, including both homogeneous and non-homogeneous tests (see, e.g., Di Benedetto et al., 2001). For the determination of the asphalt material fatigue properties the cyclic loading test to assess the stiffness modulus is prolonged in the sense of a fatigue test by applying a high number of load cycles. The sinusoidal load is usually applied by maintaining either a constant force amplitude (controlled-force mode), or a constant displacement amplitude (controlled-displacement mode). 349

In consequence of repeated loading, strength and stiffness modulus of asphalt materials change progressively. For the controlled-force mode, the strain response increases with the number of load cycles. This phenomenon is generally called fatigue. The stiffness modulus decreases and the phase lag increases during testing and the energy dissipated per stressstrain cycle increases. As a result of the fatigue test, one obtains the long-term evolution of the complex modulus and the dissipated energy. These parameters are obtained from the measured sinusoidal forces and displacements. Usually, the test results are analysed in terms of fatigue life duration and of fatigue damage characteristics in the crack initiation phase. In a macroscopic sense, failure is usually defined in terms of load carrying capacity or energy storage capacity, and is considered in empirical failure criteria, stress or strain failure criteria, energy type failure criteria, or damage failure criteria (cpr. Li, 2001). By fatigue life the number of load applications to failure is understood. The classical fatigue criterion is defined in a controlled-displacement/strain test as the number of cycles (N) when the force/stress has decreased to half of its initial value, and respectively in a controlled-force/stress test, when the displacement/strain has increased to double of its initial value (van Dijk, 1975). In best accordance but independently from the mode of loading (controlled-displacement/strain or controlled-force/stress), the fatigue criterion can also be defined as the number of cycles (Nf/50) when the stiffness modulus has decreased to half of its initial value, as specified in the European standard for fatigue testing (EN 12697-24). Amongst these criteria, the concept of Rowe (1993) is common (see also Hopman et al., 1989): The number of load cycles to failure (NMakro) is determined as soon as macro-cracking is supposed to be initiated, represented by a distinct change in dissipated energy (Wdis,n), either determined in a N-Wdis,n-diagram, or in a diagram where the energy ratio (ER) is calculated from the product N ⋅ |E*| of the number of load cycles and the stiffness modulus, and is plotted against the number of load cycles (Figure 1). The results of several fatigue tests at various load amplitudes, constant temperature and constant frequency are then plotted in a diagram on logarithmic scales, where the values of N are shown in function of the initial load amplitudes (half of the stress difference Δσ in a uni-axial force-controlled tensile swelling test as examples shown in Figure 2). Finally, a regression line (called Wöhler line) is plotted, indicating the fatigue life duration in function of the applied load amplitude. The slope of the fatigue line and the load amplitude corresponding with a fatigue life of 106 load cycles are determined (as required for CE-declaration of conformity by the European Standards EN 13108). Based on these characteristic material parameters, fatigue behaviour can be evaluated, as a small slope and a high load amplitude are related to a promising fatigue resistance. Based on the Wöhler line, the number of load cycles to fatigue can be estimated from Equation 1, where the regression factor K1 and the exponent K2 are experimentally derived material constants. This fatigue function is used as an indicator for the pavement’s durabil-

stiffness modulus

20.000 AC 11 T = -5°C f = 5 Hz

15.000 10.000

energy ratio 5.000

NMakro

energy ratio ER [-]

siffness modulus |E| [MPa]

25.000

0 0

10.000 20.000 30.000 40.000 50.000 60.000 70.000 80.000 90.000 100.000 number of load cycles N [-]

Figure 1. Example of a fatigue test result conducted in the controlled-force mode: decrease in stiffness modulus |E*|, increase in dissipated energy ratio ER, and NMakro estimated from the energy ratio used as a failure criterion.

350

endured number of load cycles NMakro [-]

1,000,000 AC 11 T = -10°C frequency 10 Hz 5 Hz 3 Hz

f = 10 Hz y = 583,350x-3.4921 R2 = 98.9 % f = 5 Hz y = 267,526x-3.0994 R2 = 97.4 %

100,000

f = 3 Hz y = 138,611x-2.8294 R2 = 90.3 % 10,000 0.0

0.5

1.0

1.5

2.0

2.5

stress difference Δσ [MPa]

Figure 2.

Example of Wöhler lines derived from controlled-force fatigue tests.

ity. However the test results as well as the derived fatigue function highly depend on the test conditions temperature and frequency. N Makro = K1 ⋅ Δσ K 2

(1)

1.2 Scope and outline of this study The mode of loading has a crucial influence on the fatigue test result. Consequently, the fatigue behaviour is very sensitive to the loading and boundary conditions applied during the test. Results from different fatigue tests usually show an important scatter. For this reason, careful selection of testing conditions and accurate interpretation of test data are needed. According to the European Standard for fatigue testing (EN 12697-24) a minimum number of six repetitions per load level is required to determine the fatigue properties of one single asphalt mixture because of the material inherent in-homogeneities. This results in a number of 18 single tests for a single temperature and one frequency. Even if 18 single fatigue tests are rather time-consuming and cost-extensive already, the temperature and frequency dependency of asphalt fatigue properties still remains unconsidered. Against this background, the scope of this study is to analyse possible ways to reduce the effort in fatigue testing with regard to the derivation of parameters to assess pavement performance Special attention is paid to the loss of prognosis quality with reduction of test effort as it is common practice to consider only one temperature condition in laboratory fatigue testing, special emphasis is also put on the consideration of the temperature dependency of material fatigue behaviour. For this purpose fatigue functions are derived for six different asphalt mixtures by conducting fatigue tests at various temperatures and loading frequencies. The experimental part of this study is represented in Chapter 2. The obtained fatigue test results are the basis of a study on possible correlations between the coefficients of the derived fatigue functions and the applied temperatures and frequencies. Based on these correlations, a possible reduction of the test effort is discussed in Chapter 3 aiming in a reduction of the time needed for fatigue testing and in the incorporation of the dependency of material fatigue properties on temperature and frequency conditions. The conclusions are summarized in Chapter 4. 2

LABORATORY FATIGUE TESTS

2.1 Materials investigated This study is based on fatigue test results obtained for 9 different hot mix asphalts. Main compositional characteristics of these asphalt materials are summarised in Table 1. 351

2.2 Test procedure The test procedure operated for this study is the uni-axial cyclic tensile stress test (UCTST) which is a homogeneous controlled-force fatigue test at low temperatures and was recently introduced as test method in the European Pre-Standard prEN 12697-46. The prismatic asphalt specimen is loaded with a sinusoidal cyclic tensile stress at a constant temperature. For this purpose, the specimen is glued to steel adapters. After joining it with the load device at +20°C, it is cooled down to the test temperature, while the test machine balances the thermal stress. After reaching the test temperature, the cyclic force is generated by a hydraulic valve and measured in a load cell. The deformation of the specimen is detected by two LVDTs, which enable the analysis of the strain signal. The test ends with specimen fracture. Because the test as performed in this study is intended to simulate the fatigue behaviour of asphalt materials at low temperature conditions (see Arand, 1987), the test is conducted at temperatures in the range of –15°C to +10°C. The stress amplitude moves between prescribed constant tensile stress limits, where the bottom stress limit is correlated to the material loading due to cryogenic stress, and the upper stress limit corresponds to the superimposed mechanical traffic loading (Figure 3). The cryogenic stress is derived from Thermal Stress Restrained Specimen Test (TSRST) as described in prEN 12697-46. This procedure results

Characteristics of aggregates maximum aggregate density [kg/m3] 2860 [%] <0.09 mm 9.2 <2.0 mm 15.3 >2.0 mm 73.5 content of crushed aggregate C100/0 Binder characteristics binder type

softening point R&B [°C]

AC 22

AC 16 (II)

SMA 11 (III)

AC 32

AC 16 (I)

PA 8

AC 11

SMA 11 (II)

Composition of asphalt mixtures investigated. SMA 11 (I)

Table 1.

2701 11.0 13.0 76.0

2698 9.5 37.5 53.0

2645 4.6 0.6 94.8

2700 7.0 21.0 72.0

2700 8.2 24.2 67.6

2708 10.5 14.5 75.0

2682 6.1 21.5 72.4

2730 6.9 24.9 68.2

C90/1

C90/1

C90/1

C90/1

C90/1

C100/0

C100/0

C90/1

25/ 55– 55 A

50/70

50/70

25/ 55– 55 A

50/70

60

52

54

63

54

25/ 55– 55 A

25/ 55– 55 A

50/70

40/ 100– 65 H

59

62

52

87

Characteristics of the asphalt mixture binder content [mass-%] 6.2 6.7 maximum density [kg/m3] 2608 2432 mean void content of specimens [vol-%] 3.1 2.8

6.0

6.2

4.5

4.2

6.5

4.3

4.4

2476

2414

2514

2545

2438

2507

2552

2.8

24.3

4.3

6.6

3.2

5.2

4.0

Preparation of specimen preparation of industrial production in asphalt plants asphalt mixtures preparation of from asphalt slabs, compacted in laboratory by specimen segmented roller compactor

352

from asphalt cores, taken from a test road

in material- and temperature-dependent test conditions. The applied bottom stress values are summarised in Table 2. More details concerning the test procedure can be found in Arand (1987) and Arand et al. (1996), Wistuba et al. (2006), Mollenhauer (2008) and Mollenhauer et al. (2008). 2.3 Test results: Fatigue functions and low-temperature performance curves Based on the fatigue tests conducted for various stress amplitudes σa and based on the measured load cycles to failure NMakro, the coefficients K1 and K2 of the fatigue function (cp. Equation 1) can be determined in function of test temperature and test frequency. The test results of all fatigue tests performed on the materials presented above are published in Mollenhauer (2008). Contrary, Equation (1) can also be employed for predicting the number of load cycles to fatigue NMakro,cal for other load amplitudes than tested. Using interpolation and extrapolation techniques so-called ‘low-temperature-performance-(LTP-)curves’ can be derived, as exemplarily depicted in Figure 4 for AC 11. Note that below the test temperature of –15°C, the curves can be extended towards a theoretical fracture temperature Tf,TSRST, where failure is expected to occur for a single load impulse and which can be stated in a thermal strain restrained specimen test (comp. Table 2). A comparison of the measured number NMakro and the predicted number NMakro,cal is presented in Figure 4 (right) for all materials investigated. The coefficient of correlation becomes 97.4%, indicating a promising quality of prognosis.

Figure 3.

Test equipment and principle of the uniaxial cyclic tensile stress test.

bottom stress value σu [MPa] at test temperature T

SMA 11 (I)

SMA 11 (II)

AC 11

PA 8

AC 16 (I)

AC 32

SMA 11 (III)

AC 16 (II)

AC 22

Table 2. Bottom stress values derived from TSRST and applied during uniaxial cyclic tensile stress tests.

σu(T = +10°C) σu(T = +5°C) σu(T = 0°C) σu(T = −2.5°C) σu(T = −5°C) σu(T = −10°C) σu(T = −15°C)

− 0.106 0.215 − 0.444 0.845 1.486

− 0.099 0.288 − 0.626 1.153 1.906

− 0.056 – − 0.515 1.171 2.246

− 0.030 0.050 − 0.094 0.173 0.307

− 0.078 0.187 − 0.416 0.831 1.498

− 0.058 0.094 − 0.222 0.568 1.134

0.030 − − 0.220 − − 1.370

0.030 − − 0.290 − − 1,280

0.030 − − 0.320 − − 1.680

failure temperature Tf,TSRST

−25.5

−25.6

−25.5

−33.7

−23.2

−25.9

−24.7

−26.8

−26.2

353

1,000,000

AC 11 f = 10 Hz

with test results supported area 0.6

1,000,000

0.8 1.0

100,000

1.2 Δσ [MPa] 1.4 1.6 1.8 2.0 2.2 2.4 2.6

10,000

1,000 -20

-15

-10 -5 0 Temperature T [°C]

5

10

calculated number of load cycles NMakro,cal (Δσ,T,f) (eq. 1)

number of load cycles NMakro(Δσ)

10,000,000

100,000

correlation of all values: 0.991 y = 1.0465x 2 R = 97.4 % SMA 11 S (I) SMA 11 S (II) SMA 11 S (III) AC 11 PA 8 AC16 (I) AC16 (II) AC 22 AC 32 bisector

10,000

1,000 1,000

10,000 100,000 1,000,000 measured number of load cycles N Makro (Δσ,T,f)

Figure 4. Low-temperature-performance-curves (LTP-curves) for the prediction of the number of endurable load cycles NMakro at a given temperature and load difference and for the frequency f = 10 Hz (left); comparison of calculated and measured data for NMakro (right).

3

REDUCING THE TEST EFFORT

3.1 Temperature-dependency of fatigue properties To obtain a single LTP-curve as shown in Figure 4, one fatigue function per test temperature is evaluated from at least 9 single tests at constant frequency. In case of four test temperatures, the number of needed fatigue tests becomes 36, indicating a total testing time of about 18 work days (without considering the time needed for specimen preparation). If further the influence of the traffic speed is analysed by means of test frequency variations, the total number of tests has to be tripled at least. For this reason, a procedure has been developed to reduce the test effort in order to describe the temperature-dependent fatigue properties. This procedure is discussed in the following, focusing on the parameters K1 and K2, and their dependency on the test temperature 3.1.1 Factor K1 Based on the obtained fatigue test results it can be shown, that the factor K1 increases with decreasing temperature until a maximum is reached. Then the factor K1 decreases with decreasing temperature, as exemplarily depicted in Figure 5 for the asphalt materials AC 11 (filled squares) and SMA 11 (I) (filled rhombi). The shape of the curve is thus similar to the shape of the LTP-curve (cp. Figure 4). Note that the factor K1 equals the number of endured load cycles at a load amplitude of Ds = 1,0 MPa (cp. Equation 1): K1(T ) = N Makro ( Δσ = 1,0 Μ pa, T).

(2)

For this reason, in Figure 5 the means of the measured number of load cycles at a load amplitude of Δσ = 1,0 MPa are located just next to the factors obtained for K1 (dotted lines, squares representing AC 11, and rhombi representing SMA 11 (I)). It can finally be concluded, that in order to obtain the fatigue function parameter K1 for a prescribed frequency it is sufficient to conduct fatigue tests at 4 different temperatures, but only one load amplitude of Δσ = 1,0 MPa. In total, considering a triple test replication, 12 single tests are thus sufficient to derive the factor K1 3.1.2 Exponent K2 Figure 6 shows the exponents K2 (representing the slope of the fatigue function) in function of the test temperature T, as derived for all materials investigated in this study. The data scatter is in the range of approximately –3 to –7. The lower the exponent the more important is the influence of the applied load on the resulting number of load cycles. However, the asphalt materials investigated show inconsistent behaviour, and a temperature dependency is hardly 354

factor of fatigue functions K 1(f=10 Hz) [-]

1,000,000

100,000

K1: AC11

N(1.0 MPa): AC 11

K1: SMA 11 (I)

N (1.0 MPa): SMA 11 (I)

10,000 -20

-15

-10

-5

0

5

10

temperature T [°C]

Figure 5. Factors K1 and numbers endured load cycles at a stress difference of Δσ = −1,0 MPa versus the temperature T (exemplarily for AC 11 and SMA (I)).

temperature T [°C] -20

-15

-10

-5

0

5

10

15

0 SMA 11 (I)

exponent of fatigue functions K2 (f=10 Hz) [-]

-1

SMA 11 (II)

-2

SMA 11 (III)

-3

AC 11

-4

PA 8

-5

AC 16 (I) AC 16 (II)

-6

AC 32

-7

AC 22

-8 Figure 6.

Exponents K2 versus test temperature T.

observed. For this reason, the fatigue function parameter K2 is considered to be independent of the temperature conditions. Thus, it is sufficient to estimate the impact of the stress difference on the number of load cycles at only one test temperature. The resulting fatigue function can be represented by Equation 3. N Makro ( Δσ , T) = Κ1(T) ⋅ Δσ Κ 2 = N Makro (1, 0 MPa, T) ⋅ Δσ K 2

(3)

In order to examine at which temperature the exponent K2 should be estimated to reach fatigue functions which represent the measured data best. In Figure 7, the measured numbers of load cycles are compared to the calculated values using (eq. 3) with the exponents, derived at 4 temperatures. The best agreement for the AC 11 was found for the exponent, derived at a temperature of –5°C. If all nine asphalts are taken into account, it can be stated, that best agreement is obtained for a temperature of 0°C (Figure 7). It is concluded, that the factor K2 can be derived best at a test temperature of 0°C. Based on these conclusions presented above, the temperature-dependent fatigue properties is estimated for a given frequency from Equation 4, reading N Makro ( Δσ , T) = N Makro (1, 0 MPa, T) ⋅ Δσ K 2 ( T=0°C) . 355

(4)

1.4 1.2

AC 11 f = 10 Hz

exponent

1

100,000

0.8 0.6 0.4 0.2 0 100

10,000

K2(-15°C)

coefficient of determination

calculated number of load cycles s NMakro,cal (Δσ,K2(T))

1,000,000

K2(-10°C) 1.0035

y = 0.8488x 2 R = 0.905

K2(-5°C) K2(+5°C)

1,000 1,000

10,000

100,000

80 60 40 20

1,000,000

0 -20

-15

measured number of load cycles N Makro(Δσ,T)

-10 -5 0 temperature T [°C]

5

10

15

Figure 7. Comparison of the number of load cycles NMakro measured with the number NMakro,cal calculated by use of eq. 3 by using exponents estimated at various temperatures (left); analyses of the temperature which results in the best prognosis quality (right).

Hence, only one fatigue test at a constant load amplitude of Δσ = 1.0 MPa has to be carried out per temperature to determine K1. Assuming a choice of 4 temperatures and a threefold test replication 12 tests are needed in total for the assessment of the factor K1. In addition, two more load amplitudes with three tests each are to be applied at a temperature of 0°C to derive the exponent K2 and the entire fatigue function. In total, 18 single fatigue tests are needed instead of 36 (see above) for the description of the temperature-dependency of fatigue properties. This procedure may reduce the test effort significantly. 3.2 Frequency-dependency of fatigue properties If in Figure 2 (see Section 1) the load amplitudes are depicted in function of the test duration until cracking instead of the number of load cycles, it is noticed, that the duration until the specimen fails is independent of the frequency applied and all data can be represented by a single time-fatigue function (see Figure 8), reading t(N Makro ) = L1 ⋅ Δσ L2 .

(5)

Similar Figures for all materials investigated can be found in Mollenhauer (2008). The number of load cycles until failure is linked to the test duration according to Equation 6, and the numbers of endured load cycles derived at two different frequencies f1 and f2 are linked to another in accordance with Equation 7, reading N Makro (f ) = t(N Makro ) ⋅ f

or t(N Makro ) =

N Makro , and f

N Makro (f1 ) = t(N Makro ) ⋅ f1 = N Makro (f2 ) ⋅

f1 . f2

(6)

(7)

Hence, it is sufficient to derive the fatigue function for a single frequency. Equation 7 can than be used to calculate the endured number of load cycles for any other frequency. In this way, the fatigue function derived at one single frequency can be used for the prognosis of the fatigue life for various traffic speeds. 3.3 Quality of prognosis with reduced test effort If fatigue life determination is based on the “(short-time)” technique developed a reduction of prognosis quality has to be taken into account. The extent of this reduction can be estimated 356

100,000

test duration until cracking t(NMakro) [s]

AC 11 T = -10°C frequency 10 Hz 5 Hz 3 Hz 10,000

all frequencies -3.1642 y = 52.401x 2 R = 95.0 %

1,000 0.0

0.5

1.0

1.5

2.0

2.5

stress difference Δσ [MPa]

Figure 8.

Test duration versus the applied stress difference to derive a time-fatigue function. 1,000,000 correlation of all values: 1.0311 y = 0.6864x 2 R = 92.1 %

calculated number of load cycles NMakro,cal (Δσ,T,f) (eq. 7)

calculated number of load cycles NMakro,cal (Δσ,T,f) (eq. 4)

1,000,000

100,000 SMA 11 S (I) SMA 11 S (II) SMA 11 S (III) AC 11 PA 8 AC16 (I) AC16 (II) AC 22 AC 32 bisector

10,000

1,000 10,000

1,000

100,000

1,000,000

measured number of load cycles N Makro (Δσ,T,f)

correlation of all values: 0.9846 y = 1.1273x 2 R = 0.96.3 100,000 SMA 11 S (I) SMA 11 S (II) SMA 11 S (III) AC 11 PA 8 AC16 (I) AC16 (II) AC 22 AC 32 bisector

10,000

1,000 1,000

10,000

100,000

1,000,000

measured number of load cycles N Makro (Δσ,T,f)

Figure 9. Comparison of the measured numbers of load cycles NMakro to the numbers calculated by using the fatigue functions derived with reduced test effort NMakro,cal.

for a selection of test parameters by comparing the calculated numbers of load cycles NMakro,cal (derived from the reduced test program and based on the fatigue functions) with the measured number NMakro. This comparison is depicted in Figure 9, where only a marginal influence of the reduction of test effort on the prognosis quality is found: Even though the procedure leads to an increased scatter of the corresponding pairs of values, still a satisfying coefficient of correlation is observed. The prognosis quality decreases even less if Equation 7 is used to calculate the number NMakro,cal by applying the fatigue function parameters derived at a frequency of f1 = 10 Hz to other frequencies and multiply the result by the quotient of f2/f1 (in comparison to Figure 4). 4 CONCLUSIONS This study discusses possible ways to reduce the effort in fatigue testing, but without downgrading the quality of the derived fatigue function. “Short-time” techniques are developed based on fatigue functions derived for nine different asphalt mixtures by means of UCTST at various temperatures and loading frequencies. First an important reduction of test effort is achieved by deriving the parameter K1 of the fatigue function from cyclic tests where a load difference Δσ = 1 MPa per temperature is applied. The exponent K2 of the fatigue function is considered as temperature indifferent and thus has to be determined at a single test temperature only. The results obtained at varied frequencies show, that the testing time controls the number of endured load cycles primarily. Hence, the fatigue test result for a prescribed test frequency f1 can be used to calculate the endured number of load cycles at a varied frequency f2. In this way, varying frequencies can be considered without any enlarging of the test effort. 357

In the future, further application of this “short-time” technique will prove its practicability. These considerations will pave the way for the incorporation of the dependency of material fatigue properties on temperature and frequency conditions in future pavement analysis practice. ACKNOWLEDGEMENT The results of fatigue tests on nine asphalt materials as used in this study were obtained in two research projects (Leutner et al. 2007, Wellner et al. 2008). The authors want to thank the Federal Ministry of Transport, Building and Urban Affairs and the Federal Ministry of Education and Research for the funding of these two research projects. Further, the laboratory and scientific staff of the Braunschweig Pavement Engineering Centre (ISBS) is thanked for the accurate laboratory work. REFERENCES Arand, W. 1987. Influence of bitumen hardness on the fatigue behaviour of asphalt pavement of different thickness due to bearing capacity of subbase, traffic loading and temperature. Proceedings of the VI. International Conference on the Structural Design of Asphalt pavements An Arbor/USA 1987. Volume I, 65–71. Arand, W., Rubach, C., v.d.Decken, S. 1996. Grundlegende Untersuchungen über den Einfluss der Zusammensetzung auf die Ermüdungsbeständigkeit von Walzasphalten mittels systematischer Variation kompositioneller Merkmale zur Schaffung quantitativer Bewertungsmaßstäbe. Forschung Straßenbau und Straßenverkehrstechnik; Heft 717. Bundesministerium für Verkehr, Bau und Wohnungswesen, Bonn. Di Benedetto, H., Partl, M.N., Francken, L., De La Roche Saint André, C. 2001. Stiffness testing for bituminous mixtures. RILEM TC 182-PEB Performance testing and evaluation of bituminous materials, Materials and Structures, Vol. 34. EN 12697-24 2003: Bituminous Mixtures—Test methods for hot mix asphalt—Part 24: Resistance to fatigue, European Committee for Standardization CEN, Brussels. EN 12697-26 2003: Bituminous Mixtures—Test methods for hot mix asphalt—Part 26: Stiffness, European Committee for Standardization CEN, Brussels. EN 13108-1 2006: Bituminous mixtures—material specifications—Part 1: Asphalt concrete. European Standard, European Committee for Standardization CEN, Brussels. Hopman, P., Kunst, P., Pronk, A. 1989. A Renewed Interpretation Model for Fatigue Measurement. Verification of Miner’s Rule; 4th Eurobitume Symposium; Madrid. 4–6 October; 1989; Vol. 1; pp. 557–561. Leutner, R., Lorenzl, H., Schmoeckel, K., Donath, J., Bald, S., Grätz, B., Riedl, S., Möller, B., Oeser, M., Wellner, F., Werkmeister, S., Leykauf, G., Simon, C. 2007. Stoffmodelle zur Voraussage des Verformungswiderstandes und Ermüdungsverhaltens von Asphaltbefestigungen; Berichte der Bundesanstalt für Straßenwesen Heft S 45, Bergisch Gladbach. Li, Q.M. 2001. Strain energy density failure criterion. International Journal of Solids and Structures, 38, pp. 6997–7013. Mollenhauer, K. 2008. Dimensionierungsrelevante Prognose des Ermüdungsverhaltens von Asphalt mittels einaxialer Zug-Schwellversuche. PhD-Thesis. Technische Universität Braunschweig, Institut für Straßenwesen. Mollenhauer, K. Lorenzl, H. 2008. Testing of fatigue and deformation properties in uniaxial tension tests; 4th Eurasphalt & Eurobitume Congress; 21–23 May 2008. Copenhague. Rowe, G. 1993. Performance of Asphalt Mixtures in the trapezoidal Fatigue Test. Proceedings of the Association of Asphalt Paving Technologists, Volume 62, S. 344–384, 1993. van Dijk, W. 1975. Practical Fatigue Characterization of Bituminous Mixes. Proc., Association of Asphalt Paving Technologists, Vol. 44. Wellner, F., Weise, C., Leutner, R., Oeser, M., Jähnig, J., Lorenzl, H., Schindler, K., Mollenhauer, K., Zander, U., Rabe, R. 2007. Nachhaltiger Straßenbau: Bemessungsmodell zur Förderung der Innovations- und Wettbewerbsfähigkeit kleiner und mittelständischer Straßenbauunternehmen; Schlussbericht; Dresden; 2007. Wistuba, M., Lackner, R., Blab, R. Spiegl, M. 2006. Low-temperature performance prediction of asphalt mixtures used for Long-Life Pavements—new approach based on fundamental test methods and numerical modelling. International Journal of Pavement Engineering, Vol. 7, No. 2, pp. 121–132, Taylor & Francis.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Hot mix asphalt produced from marble waste C. Gurer & H. Akbulut Technical Education Faculty, Afyon Kocatepe University, Afyonkarahisar, Turkey

A. Yildiz Engineering Faculty, Afyon Kocatepe University, Afyonkarahisar, Turkey

ABSTRACT: The vast quantity of waste materials accumulating throughout the world has been creating a costly disposal problem. More than 95% of asphalt pavement materials (by weight) consist of aggregates. The highway and construction industries consume a huge amount of aggregates annually causing considerable energy and environmental losses. As a result of the increasing demands for new aggregate quarries, the general texture of earth’s surface has been steadily deteriorating, causing environmental concerns. The use of marble wastes from marble quarries as aggregates might help meet the increasing demands and slow down any detrimental effects on the environment. In this study, marble aggregates (M) produced from homogeneous marble quarry wastes in Afyonkarahisar Iscehisar region were compared to control aggregate specimen (C) currently used in Afyonkarahisar city asphalt pavements. Various physical and mechanical aggregate tests, Marshall stability-flow and indirect tensile tests were carried out on the aggregates and hot mix specimens and the test results were compared with control specimen (C). The results indicate that the physical properties of the marble aggregates are within specified limits and these waste materials can potentially be used as aggregates in light trafficked asphalt pavement’s binder layers. 1

INTRODUCTION

The vast quantity of waste materials accumulating throughout the world has been creating a costly disposal problem. One of the major waste generating industries is the construction and marble production industry. Nearly 70% of this precious mineral resource gets wasted in the mining, processing and polishing procedures. The processing waste, which comprises about 30% by weight of the marble blocks, are converted into powder and dumped onto riverbeds thereby threatening the porosity of aquifer zones. Almost 40% (amounting to 86000 m3 per year) of the waste generated during quarrying operations is mainly in the form of rock fragments which are dumped into nearby empty pits, or on roads, riverbeds, pasturelands and agricultural fields leading to wide-spread environmental pollution (Gürer & Akbulut 2006; Okagbue & Onyeobi 2003). The rock fragments generated is a source of aggregates that can be used in the highway pavement design procedure. Afyonkarahisar has been a major marble producer since the Roman Empire producing 200,000 m3 annually, which comprises 12% of the entire marble production in Turkey (Kus¸cu & Bagˇcı 2003). The waste generated in the region has the potential to meet the aggregate demands for bituminous pavement construction in the area. Marble waste in a quarry and open Land’s Afyonkarahisar shown in Figure 1. In most cases, over 90% of asphalt concrete (AC) mix is aggregate (coarse aggregate, sand and filler) and flexible road construction even the foundations beneath the bituminous layers are made up aggregate in some form (White 1996). In the construction of pavements, as much as 32,200 t of virgin aggregates are consumed per kilometer (Zoorop & Suparma 2000). In order to meet the demands from the road construction industry, aggregate quarries have been

359

Figure 1.

Marble waste in a quarry and open land (Afyonkarahisar, Turkey).

causing rapid environmental deterioration and unrecoverable damages (Drew et al. 2002). In order to minimize these effects as well as construction costs, a number of researchers have been working to find a source of aggregates that is environment friendly and cost effective (Gürer 2005; De Rezende 2002; Karasahin & Terzi 2007). A number of researchers indicate that quarry aggregates produced from waste marble during mining and processing wastes could be used as construction material in low traffic asphalt pavement base courses (Çetin 1997, Akbulut & Gürer 2006). The waste marbles mostly consist of calcium with a low polishing stone value, so their use on the top of the layers (wearing courses) requiring a high skid resistance may not be possible. However, Akbulut & Gürer reported that the potential to use the waste in low to medium traffic urban roads and binder courses not requiring a high skid resistance exists (Akbulut & Gürer 2006). Aggregates from waste marble may meet the huge demand for aggregates by the pavement construction industry. The work aims at studying the use of waste marble fragments, generated during the production of marble blocks and cutting processes, as aggregates in the asphaltic mix design procedure. The use of waste marble aggregates has the potential to reduce road construction budgets as well as encourage environmental protection. 2

MATERIALS AND METHODS

2.1 Aggregate and asphalt cement Two kind of aggregates were used in this study, a waste marble (M) and limestone (C). C sample was chosen as a control specimen because the specimen has been used as pavement aggregates (in seal coats, binder and wearing course of hot mix asphalt pavements) in Afyonkarahisar City municipality. Aggregate specimen’s chemical properties are shown in Table 1. The asphalt cement used is 60/70 penetration grade (ASTM D 946). The engineering properties of the asphalt cement are given in Table 2. The asphalt cement used in the tests is commonly used by the Turkish Highway Authority. It was produced in the Izmir Aliaga refinery and meets ASTM standards. The asphalt cements properties given in Table 2. 2.2 Experimental program The plan of this study included the following steps: 1. Determine aggregate physical properties: This section includes sieve analysis (ASTM C136); specific gravity of coarse, fine and filler aggregates (ASTM C127, C128, D854); Los Angeles abrasion test (CEN EN 1097-2), Aggregate impact value test (CEN EN 1097-2), freezing and thawing test (CEN EN 1367-1), particle shape-flakiness index test (CEN EN 933-3). 2. Determine the asphalt cement properties: This section includes specific gravity test (ASTM D70), penetration test (at 25°C) (ASTM D5), softening point test (ASTM D36), loss on heating test (ASTM D6) ductility test (ASTM D113) and viscosity test (at 135 and 165°C) (ASTM 4402). 360

Table 1. Chemical compositions indicating aggregate specimen’s component percentage.

Table 2.

Component

M (%)

C (%)

CaO SiO2 MgO Na2O Al2O3 O2

32,01 1,06 0,18 0,22 0,18 66,35

19,94 0,51 0,42 – – –

Properties of asphalt cement.

Properties

Results

Properties

Results

Source Penetration grade Penetration at 25°C Specific gravity Softening point (°C)

Aliaga 60/70 63 1,060 49

Loss on heating (%) Flash point (°C) Ductility (5 cm/dk) Viscosity at 135°C Viscosity at 165°C

2 296 >100 cm 0,420 Pa s 0,114 Pa s

3. Perform Marshall method and determine optimum asphalt concrete cements (ACC): In determining the optimum ACC for a particular gradation of aggregates by Marshall method of mix design (ASTM D 1559), a series of test specimens are prepared for a range of different ACC so that the test data curves show a well defined optimum value. Optimal asphalt cement content was determined with Marshall Method after mechanical properties of aggregates were determined. Test should be scheduled on the basis of 0,5% increment of asphalt content. Three test specimens are prepared for each ACC used in order to provide adequate data. Thus, a hot-mix design study using six different ACC will normally require 18 test specimens. 4. Determine permanent deformation of hot mix asphalt briquette specimens: in order to determine permanent deformation, 5 specimens produced with the optimum asphalt cement ratio for each specimen (M and C) and indirect tensile test were carried out. In the indirect tensile strength test, cylindrical specimen is subjected to repeated compressive loads, which act parallel to and along the vertical diameter plane using the Marshall loading equipment. This creates uniform tensile stresses perpendicular to the direction of applied load and along the vertical diameter plane, which ultimately causes the specimen to fail splitting along the vertical diameter. Resistance of mix to permanent deformation is assess with the using the test.

3

TEST RESULTS AND DISCUSSION

3.1 Aggregate test results In this part, standard aggregate test methods were applied to the aggregates. Specific gravities of aggregates specimens are presented in Table 3. Aggregate specimens design gradation limits (ASTM C136 1992) and mechanical properties of aggregates are shown in Table 4 and Table 5 respectively. Sample M and C was supplied from different aggregate resources. The both specimens were taken from production line for sieve analyses. The sieve analyses result were based on the Marshal mix design procedure. LAV, particle shape-flakiness index, loss of freezing and thawing of aggregate specimens within the specification limits. Merely, AIV values of M specimens higher than specification limits. However, it is thought that this situation would not be an obstacle because the sample 361

Table 3.

Specific gravities of aggregates. Specific gravities (kg/m3)

Fraction

Apparent

Specimens

M

C

M

C

Standard

Coarse aggregate Fine aggregate Filler aggregate Efective specific grade of blended aggregate Bulk specific grade of blended aggregate Apparent specific grade of blended aggregate

2705 2724 2742 2703

2693 2685 2705 2671

2695 2684 – –

2674 2612 – –

ASTM C127 ASTM C128 ASTM C128 ASTM D 2041

2692

2650

–

–

–

2714

2691

–

–

–

Table 4.

Bulk

Design gradation limits of aggregate specimens.

Sieve

Sieve (mm)

Passing (M)%

Passing (C)%

3/411 1/211 3/811 No. 4 No. 10 No. 40 No. 80 No. 200

19,0 12,5 9,5 4,75 2,00 0,42 0,180 0,074

82,6 67,8 60,8 47,9 28,0 15,5 9,5 4,0

100 73 63 49 30 14 10 7

Table 5.

Lower-upper limits 77–100 59–77 49–66 34–52 23–39 12–22 7–14 2–7

Mechanical properties of aggregates.

Aggregate properties

Standard

Specimens

Test results

Limit values

LA Abrasion Value (LAV) (%)

CEN EN 1097-2

M C

27,44 25,60

≤35 ≤35

Aggregate Impact Value (AIV) (%)

CEN EN 1097-2

M C

18,66 16,83

≤18 ≤18

Particle shape-flakiness index (%)

CEN EN 933-3

M C

9,41 3,54

≤35 ≤35

Loss of freezing and thawing (%)

CEN EN 1367-1

M C

2,85 2,75

≤12 ≤12

LAV test after freezing and thawing test

CEN EN 1367-1

M C

34,74 11,80

Polishing stone value (PSV)

BS 812 part 114

M C

0,44 0,45

– – ≥0,5 ≥0,5

M will not be used on a wearing and seal coat layers. LAV value after freezing and thawing of M specimen is higher than C specimens but it is being thought that this fact don’t cause any problem because it was used in binder course. PSV values of specimens are in same levels approximately both of the specimens. 362

3.2 Marshall stability and flow test results

1400,0

2,47 2,46 2,45 2,44 2,43

M

2,42

R2

2,41

C

= 0,990

R 2 = 0,921

2,4 2,39

Marshall Stability (kg)

Bulk Specific Gravity (gr/cm3)

Despite all specimens, used on a binder layer of medium trafficked roads ensuring 600 kg min. stability value, provided more than the minimum stability specified and the maximum stability values (1345 kg) were gained with the sample M provided by marble specimens. The sample M having the maximum stability value may be effectively used within a binder layers in which this is not cause a distress which will not lead any deformation during medium trafficked road condition. Maximum stability of both specimens are almost the same and within

1300,0 1200,0 1100,0

M 1000,0

2,38

R2 = 0,863

800,0 700,0

3,0

4,0

5,0

6,0

7,0

3,0

Asphalt Content %

5,0

6,0

7,0

110,0

6,00

R2

5,00

2

= 0,998

R = 0,984

4,00

M 3,00

C

2,00 1,00 0,00 3,0

4,0

5,0

6,0

Void Filled with Asphalt %

Void (Vh) %

4,0

Asphalt Content %

7,00

100,0 90,0 80,0

M

70,0

C

60,0

R 2 = 0,989

50,0

R 2 = 0,999

40,0

7,0

3,0

Asphalt Content %

4,0

5,0

6,0

7,0

Asphalt Content %

3,80

Void in Mineral Aggregate %

15

3,60

Marshall Flow (mm)

C

R 2 = 0,979

900,0

3,40 3,20

M

3,00

C

2,80 2,60

R 2 = 0,928

2,40

R 2 = 0,876

2,20

14,5 14 13,5 13

M

12,5

C 12 11,5

R 2 = 0,509

11

R 2 = 0,977

10,5 10

2,00 3,0

4,0

5,0

6,0

3,0

7,0

Asphalt Content %

Figure 2.

4,0

5,0

6,0

Asphalt Content %

M and C specimens Marshall hot mix asphalt design graphs.

363

7,0

Axial Deformation (mm)

3,5 3 2,5 2

M

1,5

C

1 0,5 0 0

500

1000

1500

2000

2500

Num ber of Cycle

Figure 3.

Test results showing plastic deformation values of specimens.

the necessary specification limits. High stability and low stability value is not a desirable properties in the production of hot mix asphalt. Because the high stability and low flow value may cause a rapid deterioration because of repeated load applied during the course of time. The flow value that determines behaviors and elastic and plastic properties of asphalt concrete layers under traffic load. The flow value, a rapture of the Marshall load application, represents deformation corresponding internal friction. There is a linear and inverse relationship with the flow value. The maximum flow value indicated on the specification represents plasticity of the mix, max. Binder percentage used and the lowest value represents brittleness and stability of the mixture (The Asphalt Institute 1993; The Asphalt Institute 1989). Relationship between flow and asphalt content are shown in Figure 2. If asphalt content is increased flow value will be increased. It is the lowest flow value was saved for M mixes. The void content filled with asphalt of the specimen C has a higher than the specimen M. The %void content of the mix C has a lower than the mix M. This means that the specimen C may have a tendency of bleeding compared to the specimen M (see Figure 2). Void content of the sample M is higher than the sample C, so specific gravity of the sample M is lower than the sample. The flow value and bitumen content relationship is shown in Figure 2. As asphalt content is increased the flow value also increased. The lowest flow value is provided with the sample M. VMA of the sample C is higher than the sample M. Void content of sample C is lower than the sample M, which may mean the sample C may cause bleeding compared to the sample M in Figure 2. 3.3 Indirect tensile test results Despite each wearing courses and base courses which expose repeated traffic loads hence elastic deformation, even if not much it presents some plastic deformation. Figure 3 presents of the test results of plastic deformation value of the specimens. According to the results, the mix made of aggregate M shows more plastic deformation compared to the specimen C. So the specimen M has a lower life span compared to the C. It may be thought that if M was used on low trafficked road of surface and binder courses, it would meet the design life. As fatigue life increases with the thickness of asphalt layers, specimen M will presents a longer fatigue life with the increase of the layer. Despite deformation arising from vehicles passing from every road structure is elastic, however, small amount of plastic deformation accruing on bituminous layers. Plastic deformation values of the specimens are shown in the Figure 3. The results show that the mixture made with sample M has a more plastic deformation compare to the sample C. So life span of the sample made with M is lower than the sample made with C. Since the sample M will be used in low trafficked roads, this will not cause any obstacle in the binder course. As fatigue life of mixture is depending on the layer thickness, there would be an increase for the sample A with the increase of layer thickness. 364

4

CONCLUSIONS

Based on these studies results, waste marble aggregates properties were correlated control aggregates. For this purpose, Standard pavement aggregates tests and Marshall Stability tests were carried out. These studies results are listed below: • The aggregates which were used in wearing course, must be better than other courses aggregates, but base, subbase and binder courses aggregates properties not essential as good as in wearing course nevertheless, binder aggregates must have definite properties. According to the Los Angeles abrasion test results, M specimens abrasion loss is 27,44% and this value within the specification limits nevertheless, M specimens (AIV) aggregate impact abrasion’s values are greater than limit value of 18,00%. M and C specimens AIV values is 18,60% 16,83% respectively. • Both of the aggregate specimens loss value lowers than 12% (limit value) according to the Freezing and thawing test results. It is the maximum Loss of LAV values after freezing and thawing was showed by M specimen. It was certain that when M specimen was used in binder course it hasn’t been affected as wearing course as. • Because the flat particles, which have low tensile strength, could be formed not strong locations in asphalt concrete pavements. M and C specimen particle shape-flaky index values are higher than others but this values little higher than specifications limits. Nevertheless, when rock crusher was changed in building site and used different sieving methods, flat particles could be reduced. Statistical correlations showed that particle shape-flaky index is proportion to properties of wearing course (De Rezende & De Carvalho 2003; Gürer 2005). Therefore, if flat particles were decreased wearing properties were improved. • According to the Marshall Mix Design results, Stability value of M mixes is higher than C mixes. Both of the specimen’s stability values are higher than specification limits. Flow measurements are: C > M respectively. Relationship between Marshall Stability—Asphalt Content Marshall Flow-Asphalt Content are shown in Figure 2. • Optimum asphalt cement contents are: 4,68%, 4,30% in M and C mixes respectively. Both of the contents are between in economical limits. • Results of aggregate and hot mix tests results show that waste marble aggregates could be used in light trafficked asphalt pavements binder courses. • The test results carried out on hot mix asphalt show that aggregates produced from marble could be used in binder course of lightly trafficked hot mix asphalt pavements. • This type of waste utilizing methods could be developed with law sanctions. The increasing volume of waste could be restricted by legislation. This does not limit the way in which disposal is carried out but imposes appropriate “environmental” taxes which have prompted waste generators to implement procedures for safe disposal or if possible reuse of the waste generated. • With legal regulations organized by state and local highway authorities may be encouraged using these waste in highway constructions.

ACKNOWLEDGMENT This study was supported by the Afyonkarahisar Kocatepe University Scientific Research Commission (AKU BAPK Project Number: 031.TEF.07). Authors would like to thank Afyonkarahisar Kocatepe University Scientific Research Commission.

REFERENCES ASTM Standards D5-97. 2003. Standard Test Method for Penetration of Bituminous Materials. Annual Book of ASTM Standards, USA. ASTM Standards D70-03. 2003. Standard Test Method for Specific Gravity and Density of Semi-Solid Bituminous Materials (Pycnometer Method). Annual Book of ASTM Standards, USA.

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ASTM Standards D36-95. 2000. Standard Test Method for Softening Point of Bitumen (Ring-and-Ball Apparatus). Annual Book of ASTM Standards USA. ASTM Standards D6-95. 2000. Standard Test Method for Loss on Heating of Oil and Asphaltic Compounds. Annual Book of ASTM Standards USA. ASTM Standards D92-02b. 2003. Standard Test Method for Flash and Fire Points by Cleveland Open Cup Tester. Annual Book of ASTM Standards USA. ASTM Standards D113-99. 2003. Standard Test Method for Ductility of Bituminous Materials. Annual Book of ASTM Standards USA. ASTM Standards D4402-02. 2003. Standard Test Method for Viscosity Determination of Asphalt at Elevated Temperatures Using a Rotational Viscometer. Annual Book of ASTM Standards USA. ASTM Standards C127-88. 1992. Test Method for Specific Gravity and Adsorption of Coarse Aggregate. Annual Book of ASTM Standards USA. ASTM Standards C128-88. 1992. Test Method for Specific Gravity and Adsorption of Fine Aggregate. Annual Book of ASTM Standards USA. ASTM Standards D1559-89. 1992. Standard test method for resistance to plastic flow of bituminous mixtures using Marshall apparatus. Annual Book of ASTM Standards. USA. ASTM Standards D1559-89. 1992. Standard Test Method for Resistance to Plastic Flow of Bituminous Mixtures Using Marshall Apparatus. Annual Book of ASTM Standards USA. ASTM Standards C136-84a.1992. Standard method for sieve analysis of fine and coarse aggregates. Annual Book of ASTM Standards. USA. Barksdale, R.D. 1991.The Aggregate Handbook. National Stone Association. Washington D.C. BSI, British Standards Institute, BS 812, part 114. 1989. Method for the determination of polished stone value. London, England. CEN, European Committee for Standardization, EN 1367-1. 1999. Tests for thermal and weathering properties of aggregates—Part 1: Determination of resistance to freezing and thawing. Brussels. CEN, European Committee for Standardization, EN 933-3. 1997. Tests for general properties of aggregates: Part 3, Determination of particle shape, Flakiness index. Brussels. CEN, European Committee for Standardization, EN 1097-2. 1998. Test for mechanical and physical properties of aggregates—Part 2: Methods for the determination of resistance to fragmentation. Brussels. Çetin, A. 1997. Assessment of industrial wastes on asphalt concrete pavement mixtures. MSc Thesis. Natural Science Institute, Department of Civil Engineering. Anadolu University. Eskis¸ehir, Turkey. [in Turkish]. De Rezende, R.L. and De Carvalho, J.C. 2003. The use of quarry waste in pavement construction. Resources Conservation & Recycling. 39: 91–105. Drew, L.J., Langer, W.H., Sach, Janet, S. 2002. Environmentalism and Natural Aggregate Mining. Natural Resources Research. 11 (1): 19–28. Gürer, C. 1 January 2005. Using waste marble within the asphalt pavement. MSc Thesis. Afyonkarahisar Kocatepe University. Natural Science Institute. Department of Construction. Afyonkarahisar, Turkey. [in Turkish]. Gürer, C. and Akbulut, H. 2006. An Alternative Waste Utilization . Method for Quarry Waste Marble. Proceedings of 6. National Environment Congress. 196–202 . Istanbul, Turkey. [in Turkish]. Karas¸ahin, M. and Terzi, S. 2007. Evaluation of marble waste dust in the mixture of asphaltic concrete. Construction and Building Materials, 21: 616–620. Kus¸çu, M. and Bagˇcı, M. 2003. Afyonkarahisar marble sector and its place in Turkish marble sector, Turkey National IV. Marble Symposium, Symposium Books. The University of Afyonkarahisar Kocatepe, 127–137. 18–19 December 2003. Afyonkarahisar: Turkey. Ministry of Public Works. 2004. General Directory of Highways. Turkish State Highway Specifications. Ankara, Turkey. Okagbue, C.O. and Onyeobi, T.U.S. 1999. Potential of marble dust to stabilize red tropical soils for road construction. Engineering Geology. 53: 371–380. The Asphalt Institute. 1989. The Asphalt Handbook (MS-4). Manuel Series N:4, US. The Asphalt Institute. 1993. Mix designs methods for asphalt concrete and other hot mix types. MS-2. White, M. 1992. Bituminous Mixes and Flexible Pavements an Introduction. BACMI, 22–23, England. Zoorob, S.E. and Suparma, L.B. 2000. Laboratory design and investigation of the properties of continuously graded asphaltic concrete containing recycled plastics aggregate replacement (Plastiphalt). Cement & Concrete Composites. 22: 233–242.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Discrete element analysis of aggregate variability, blending, and fracture in asphalt mixture E. Masad Texas A&M University at Qatar, Doha, Qatar

E. Mahmoud Texas A&M University, College Station, Texas, USA

S. Nazarian University of Texas at El Paso, El Paso, Texas, USA

ABSTRACT: Aggregate strength, gradation, and shape play a vital role in hot mix asphalt (HMA) performance. Many studies have demonstrated the effect of these factors on HMA performance in terms of resistance to fatigue and rutting. This paper introduces a numerical approach that account for aggregate strength, gradation, and shape to model HMA performance. The discrete element method (DEM) is the numerical tool used to achieve this approach. The approach allowed the study of the internal forces developing within the aggregate skeleton in the HMA under loading, studying the influence of aggregate strength variability on HMA performance, as well as studying the effect of blending different types of aggregates within one mix. 1

INTRODUCTION

Hot Mix Asphalt (HMA) is a combination of aggregates and asphalt binder with about 85% of the total mix volume is aggregates. Gradation of the aggregate blend as well as stiffness, strength, and shape of individual aggregate particles are all important factors that affect aggregate resistance to fracture and therefore the performance of asphalt pavements. Aggregate fracture could occur during construction or under traffic loads resulting in a mix that does not satisfy the targeted volumetric properties (Prowell et al, 2005) or experiences high deformations under traffic loads (Cheung & Dawson, 2002). The new generation of asphalt mixes such as Porous Friction Course (PFC) and Stone Matrix Asphalt (SMA) rely on stoneon-stone contact to develop a strong aggregate structure that can sustain applied loads. However, such stone-to-stone contact leads to higher stresses at the contact points, which could increase the possibility of aggregate fracture within HMA. This paper introduces an approach that combines the Discrete Element Method (DEM) and image processing techniques to account for aggregate strength, gradation, and shape in modeling HMA resistance to fracture. The following tasks were performed in order to achieve this objective: • • • • •

Design HMA with different gradations for different types of aggregates. Obtain aggregate properties from laboratory tests. Capture the internal structure of the different mixes through image processing techniques. Transfer the internal structure to DEM and simulate asphalt mix resistance to fracture. Analyze the influence of variability in aggregate strength and blending different types of aggregates in a mix on HMA resistance to fracture.

367

2

BACKGROUND ON DISCRETE ELEMENT METHOD

The discrete element method is a finite difference scheme that has been used to study the interaction among assemblies of distinct particles (Cundall 1971). Cundall and Strack (1979) used DEM for the simulation of two-dimensional non-continuous materials. Since then, it has been applied to study many different types of engineering problems, such as understanding the deformation mechanisms in geo-materials, developing constitutive relations, and modeling the movement of granular media (Abbas 2004). Cundall and Hart (1992) provide a summary of advancements in discrete element codes. Several research studies utilized DEM to characterize the behavior if asphalt mixtures. You and Buttlar (2004) used DEM to predict the modulus of asphalt mixtures at different test temperatures for a range of loading frequencies in both extension and compression. Abbas et al. (2005) used micromechanical-based models along with DEM to model the stiffness of asphalt mastic. Kim et al. (2008) used DEM to study fracture of asphalt mixtures through modeling fracture tests of disk-shaped specimens. In this study, a commercially available DEM code called Particle Flow Code in 2-Dimensions Version 3.1 (PFC2D 2004), developed by Itasca Consulting Group was used. The DEM concept is simple in principle. It is based on consecutively solving the law of motion and the force-displacement law for each particle (PFC2D 2004). In PFC2D, particles are circular (balls). They are allowed to overlap at the contact points, which occur over a very small area (i.e., at a point). The amount of overlap is related to the force at the contact via the force-displacement law. All overlaps are assumed to be small relative to the particle sizes. Bonds can be added to the contacts between the particles in order to increase the stiffness of the contact and/or to include a strength parameter above which the bond breaks. PFC2D allows different types of bonds to be assigned. In the absence of bonding, particles slide over each other once the shear force exceeds the friction resistance. 3

MATERIALS, MIXES, AND TESTS

3.1 Materials and mixes Five different aggregates were selected: granite, hard limestone, soft limestone, gravel, and sandstone in preparing asphalt mixes with different gradations (see Table 1). These gradations differ from one another providing different aggregate structures in the HMA. The PFC is an open-graded mixture with a high percentage by weight of coarse aggregates. It is composed of 89% aggregates larger than a No. 8 sieve. Superpave-C is a wellgraded mixture that consists of 35% coarse aggregates and 65% fine aggregates. The Type-D mix is also a well-graded mixture but it has a finer gradation than Superpave-C. The CMHBC mix is a gap-graded mixture that is very similar to SMA in its volumetric designs. All the mixes were prepared using the Superpave Gyratory Compactor (SGC). The same binder (PG 76-22) was used for all the mixes to reduce the effect of binder grade on the results. 3.2 Aggregate tests The indirect tensile tests on cores from rock masses retrieved from quarries were carried out at the University of Texas at El Paso to determine the tensile strength of the aggregates Table 1.

A list of aggregates and mixtures.

Aggregate type

Superpave-C

CMHB-C

PFC

Type-D

Granite Hard limestone Soft limestone Gravel Sandstone

× × × × ×

× × × × ×

× × × × ×

× ×

368

(Alvarado et al, 2007). The rock specimens tested were of cylindrical shape with a 5.8-cm (2.3-in.) diameter and a 5.1 cm (2 in.) height. The specimen was positioned with its axis placed horizontally with two bearing strips placed between specimen and both the upper and lower bearing blocks of the compressive machine. These bearing strips were of 0.32 cm (1/8 in.) nominal thickness, 2.54 cm (1 in.) wide, and of length equal or a little larger than that of the specimen. Once in place, a constantly increasing compressive load was applied to the specimen until splitting occurred. Rock cores similar to those for the indirect tensile tests were used determine the compressive crushing strength of the aggregates. Two bearing blocks were used in this test (upper and lower) both cylindrically shaped. Moduli of aggregate rocks were obtained using the “V-meter” which is a nondestructive testing technique based on ultrasonic testing. The V-meter is an ultrasonic device that measures the travel time of compressive waves by means of electric impulses. Table 2 summarizes the different experimental results of the different aggregate tests. 3.3 Asphalt mix tests For the asphalt mixes, the indirect tensile test was performed by applying a compressive load to a cylindrical specimen through two diametrically opposed, arc shaped loading strips. Each specimen, which was nominally 10.2 cm (4 in.) in diameter and 5.1 cm (2 in.) thick, was compacted at 93 ± 1% density. The test specimen was placed in a constant temperature apparatus for a long enough time to ensure a consistent temperature of 77 ± 2 oF through out the test. The specimen was then placed on the lower loading strip; the upper loading strip is then brought into light contact with the specimen by slowly lowering it, and then loaded at a 5.1 cm/min (2 in./min) rate. Table 3 summarizes the asphalt mixes results. 4

DISCRETE ELEMENT MODELING OF AGGREGATES

The PFC2D software was used to model the different aggregate tests of the five aggregates used in this study. The compressive test geometry was a rectangle that represents a vertical cross section of the laboratory specimen. The splitting tensile was represented by a circular geometry which is the vertical cross section of the specimen tested in the laboratory. Each model consisted of particles or balls with a diameter of density of 2560 kg/m3. The dimension of the square geometry or the diameter of the circular geometry was 36 mm. Two walls were added at the top and the bottom of the sample; the walls allow and define how the load is applied and interacts only with the balls. In turn, the wall movement introduces loading on the aggregate particles A bonding model, stiffness model, and slip model are included in the constitutive representation of contact points between the elementary particles. The bond model can be envisioned as elastic springs at the contact point. The bond defines the maximum shear and normal forces the contact can bear before breaking, thus the bond will break, if either the shear force or the normal tension force exceeds the bond limit. In the linear stiffness model, an effective

Table 2.

Experimental results of the aggregate tests (1 psi = 6.89 kPa).

Material

Compressive strength, psi

Tensile strength, psi

Modulus, ksi

Hard limestone Granite Soft limestone Sandstone Gravel

10427 (38%)* 14034 (7%) 6970 (8%) 13952 (31%) Not feasible

1412 (20%) 1062 (23%) 682 (-)** 1677 (11%)

10328 (13%) 6686 (6%) 5473 (11%) 8659 (7%)

* Numbers in the parentheses are the coefficients of variation from triplicate tests. ** Only one specimen was tested for the soft limestone.

369

Table 3.

Experimental results of the asphalt mixes (1 psi = 6.89 kPa).

Material

Mix type

Tensile strength at failure, psi

Hard Limestone

CMHB-C Superpave-C PFC CMHB-C Superpave-C PFC CMHB-C Superpave-C PFC CMHB-C Superpave-C PFC Type-D CMHB-C Superpave-C PFC Type-D

106 120 66 83 116 61 94 125 50 207 226 78 207 204 183 58 203

Granite

Soft Limestone

Sandstone

Gravel

normal and shear contact stiffness is calculated from the particles’ stiffness assuming that they act in series. The mathematical expressions for the stiffness’s assuming that they act in series, Kn =

kn[ A]kn[ B ] kn[ A] + kn[ B ]

(1)

Ks =

ks[ A]ks[ B ] ks[ A] + ks[ B ]

(2)

where, ks: shear stiffness, kn: normal stiffness, Kn: effective normal stiffness, Ks: effective shear stiffness, and A & B are the designations of particles in contact. The slip model becomes active once the bond between two adjacent particles breaks. It allows slipping between particles to occur when the shear force between them exceeds the allowable shear force. The aggregate contact stiffness and strength in the model were determined such that the model results matched the experimental measurements on aggregate samples shown in Table 2. Following the work that was conducted by McDowell and Harireche (2002) and Cheng (2004), the simulation was conducted using a value of unity for the ratio of the normal stiffness to shear stiffness. The coefficient of friction between the model elements was set to a small value such that sliding can occur after the bond breaks. The friction between the loading walls and the model elements was set to 0.5 as recommended by Cheng (2004). Using a very high bond strength that prevents breakage, the contact stiffness among the model particles was varied until the aggregate modulus of the model matched the experimental modulus measurements in Table 2. The next step was to vary the normal and shear bond strengths until the compressive and indirect tensile strengths from the model matched the experimental strength measurements in Table 2. This required conducting iterative analysis 370

Compressive Strength (DEM), kN/m

2

120000 100000 80000 60000 40000 20000 0 0

20000

40000

60000

80000

100000

120000 2

Sandstone

Figure 1.

Compressive Strength (Experimental), kN/m Soft Limestone Hard Limestone Granite

Equality Line

Comparison of modeling and experimental results of compressive strength.

to determine the parameters that had the best match with both tests. The experimental and numerical results compared quite well; Figure 1 shows the compressive strength results. 5

DISCRETE ELEMENT MODELING OF ASPHALT MIXES

In order to have good representation of asphalt mix structure in the DEM model, X-ray computed tomography (CT) was used to capture images of the internal structure of the different asphalt mixes. These images were transferred to represent the geometry in PFC2D. Each image pixel was represented by a particle in the PFC2D model. The Image-Pro Plus (IPP) image analysis package was used to recognize the outline pixels of each aggregate particle, and a FORTRAN code was used to group the elements of each aggregate particle in one group (Abbas, 2004). Figure 2 shows an example of a discrete element model differentiating between mastic and aggregate phases. The input parameters for the aggregate phase were selected from the aggregate tests calibration as discussed in the previous section. The mastic phase parameters were selected such that each mix matched the experimental results of the IDT experimental results. The model tracked the force and displacement for each mix as well as the internal shear and normal forces developed among the discrete particles during different loading stages. Figure 3 shows the calibration results for the different mixes and aggregates. The DEM model results matched very well the lab test results. 6

ANALYSIS AND RESULTS

6.1 Internal forces distribution analysis The internal forces of a mix are very important since they control stress localization and mix fracture. The internal forces in the mix models were studied at three stages of loading. Case I was selected at the peak force (just before failure). Case II represented an intermediate force equal to 50% of the peak force. Case III was selected, at a force of 2 kN (450 lb) where the cracking and bond loss were minimal for all the different mixes. The PFC mixes typically exhibited the highest maximum internal forces among all mixtures when compared at the same level of loading. The ratio of the maximum internal force in PFC to the maximum internal force in the other mixes ranged from 1.1 to 2.0 with an average of 1.36. This indicates that aggregates within the PFC mixes experienced higher internal forces 371

than the other mixes. The average and third quartile values are higher for the PFC mixes as well, while there are smaller differences in forces among the remaining mixtures. Figure 4 presents the normalized compressive force distributions within the different aggregate types for the CMHB-C mix. The soft limestone experienced the highest normalized internal forces compared to the other aggregates. On the other hand, the gravel experienced the lowest normalized internal forces. Hard limestone exhibited lower internal forces than the soft limestone but still higher than the granite and the sandstone. Lastly, the sandstone and granite exhibited similar internal forces. Similar trends were observed for other mix types. These results can be used in selecting the aggregate type that can be used with a specific mix design. 6.2 Influence of variability in aggregate properties on mix properties The analyses presented in the previous section used one average value for the bond strength within the aggregates. However, aggregate particles from the same source may exhibit varia-

DEM of internal structure of Type-D mix.

Tensile Strength-kN/m2 (DEM)

Figure 2.

1800 1600 1400 1200 1000 800 600 400 200 0 0

500

1000

1500

Tensile Strength- kN/m2-(Experimental) Soft Limestone Figure 3.

Hard Limestone

Granite

Gravel

Comparison of experimental and modeling results of asphalt mixes.

372

Sandstone

120%

Cumulative distribution

100% 80% 60% 40% 20%

More

75

70

65

60

55

50

45

40

35

30

25

20

15

10

5

0%

Normalized Compression (lb/lb) Hard Limestone

Granite

Soft Limestone

Gravel

Sandstone

Figure 4. Internal compression forces distribution within different aggregates (CMHB-C mix) (1 lbf = 4.45 N).

tions in their properties. In order to account for such variability in the model, aggregate bond strength was assumed to follow a normal distribution. The analysis was repeated seven times for each combination of a mix and an aggregate type. In each run, the locations or positions for the various bond strength values were determined using a random number generator. In essence, all repeat executions represent the same aggregate type, have the same mean and standard deviation, but the positional distributions of the bonds were different among the different repeats. The distributions of the strengths are summarized in Figures 5a and 5b. Average values from the model are compared with the experimental results. The experimental and the model results compare very well. The differences in variation between the model and experimental results, as can be seen by the error bars, could be due to a number of factors including the assumption of normal distribution of aggregate bond values, and assuming no variability in mastic properties and thus attributing all the variability to aggregate particles bond strengths only. 6.3 Aggregate blending A common practice in HMA mix design is to blend aggregates with different properties, in order to enhance the mix properties. This section presents DEM as an effective tool for predicting the change in the behavior of the mixes with changes in blending percentages for two different aggregate types. Soft and hard limestone aggregates were blended at different percentages to assess the blending effect. At each percentage, the model was run nine times representing different distributions of the particles that belong to soft and hard aggregates. The positions of particles that belong to each aggregate were selected randomly in each run. Figure 6 represents a graphical illustration of different cases for selecting 30% of the aggregates to be soft (70% hard). Figure 7 summarizes the results for the PFC mix. From the figure it can be seen that Blending 10 to 50% of the soft aggregate did not affect the strength of the mix; however, the mix experienced a drop in strength when the soft aggregate percentage exceeded 50%. There were differences in the amount of soft aggregate that each mixture could accommodate before 373

Strength, Experimental (psi)

300 250 200 150 100 50 0 0

50

100

150

200

250

300

250

300

Strength, DEM (psi) Gravel

Soft Limestone

Granite

(a) 300

Strength, DEM (psi)

250 200 150 100 50 0 0

50

100

150

200

Strength, Experimental (psi) Sandstone

Hard Limestone

(b) Figure 5.

Influence of variability in aggregate bond strength on mixture strength.

reduction in strength occurred. In general, the strength of dense graded mixtures such as Superpave and Type D dropped more rapidly than the strength of open graded (PFC) and gap graded (CMHB) mixtures due to the use of certain percentages of soft aggregates. 7

CONCLUSION

The discrete element method was used in simulating aggregate and mixture tests. After proper calibration, the discrete element model was used to (1) evaluate the internal force distributions in different asphalt mixtures, (2) examine the influence of variability in aggregate properties on mixture properties, and (3) evaluate the influence of blending aggregates from different sources on asphalt mixture properties. The analysis of internal forces revealed that the PFC mixtures experienced higher stresses than all other mixes. Based on the results, it is recommended that aggregate strength for PFC mixes should be about 25% more than the strength of aggregates used in dense graded mixtures. 374

Black Particles: Soft Materials, Yellow Particles: Hard Materials

Figure 6. Examples of two aggregate distributions using 30% of soft limestone and 70% of hard limestone.

Peak Force (lb)

1000 900 800 700 600 500 0

20

40

60

80

100

% of Soft Materials Figure 7.

PFC Blending Results.

The results have shown that some mixture types were more affected by variability in aggregate properties than others. In addition, mixtures varied in their ability to accommodate soft aggregates as part of a blend. In general, dense graded mixtures had a higher drop in their strength due to the use of certain percentages of soft aggregates than gap graded and open graded mixtures. The developed DEM approach presented in this study can be used to evaluate properties of asphalt mixtures due to the use of different aggregate types and blends without extensive laboratory testing. REFERENCES Abbas, A.R. (2004), “Simulation of the Micromechanical Behavior of Asphaltic Mixtures Using the Discrete Element Method,” PhD Dissertation, Washington State University. Abbas, Ala, Masad, Eyad; Papagiannakis, Tom; Shenoy, Aroon (2005) “Modelling asphalt mastic stiffness using discrete element analysis and micromechanics-based models,” International Journal of Pavement Engineering, Vol. 6, No. 2, June, 2005, pp. 137–146. Aho, B.D., Vavrik, W.R. and Carpenter, S.H. (2001), “Effect of Flat and Elongated Coarse Aggregate on Field Compaction of Hot-Mix Asphalt,” Transportation Research Record 1761, Transportation Research Board, National Research Council, Washington, DC; pp. 26–31.

375

Alvarado, C., Mahmoud, E., Abdallah, I., Masad, E., Nazarian, S., Langford, R., Tandon, V., and Button, J. (2007). “Feasibility of Quantifying the Role of Coarse Aggregate Strength on Resistance to Load in HMA,” Center of Transportation Infrastructure Systems, Texas Transportation Institute, and Texas Department of Transportation, Research Report 0-5268-1, El Paso, TX. Cheng, Yi P.H. (2004), “Micromechanical investigation of soil plasticity,” PhD Dissertation, Churchill College, University of Cambridge. Cheung, L.W., and Dawson, A.R. (2002), “Effects of Particle and Mix Characteristics on Performance of Some Granular Materials,” Transportation Research Record 1787, Transportation Research Board, National Research Council, Washington, DC; pp. 90–98. Cundall, P.A. (1971), “A Computer Model for Simulating Progressive Large Scale Movements in Blocky Rock Systems,” in Proceedings of the Symposium of the International Society of Rock Mechanics (Nancy, France, 1971), Vol. 1, Paper No. II-8. Cundall, P.A., and Hart, R. (1992), “Numerical Modeling of Discontinua,” J. Engr. Comp., 9, pp. 101–113. Cundall, P.A., and Strack, O.D.L. (1979), “A Discrete Numerical Model for Granular Assemblies,” Geotechnique, 29(1), pp. 47–65. Kim, Hyunwook, Wagoner, Michael P., Buttlar, William, (2008) “Simulation of fracture behavior in asphalt concrete using a heterogeneous cohesive zone discrete element model,” Journal of Materials in Civil Engineering ASCE, Vol. 20, No. 8, pp. 552–563 McDowell, G.R., and Harireche, O. (2002), “Discrete Element Modeling of Soil Particle Fracture,” Geotechnique 52, No. 2, pp. 131–135. Particle Flow Code in 2-Dimensions (PFC2D) Manual (2004), Version 3.10, Itasca Consulting Group. Prowell, B.D., Zhang, J., and Brown, E.R. (2005), “Aggregate Properties and the Performance of Superpave Designed Hot Mix Asphalt,” NCHRP Report 539, Transportation Research Board, National Research Council, Washington, DC. Schmiedlin, R.B., and Bischoff, D.L. (2002), “Stone Matrix Asphalt the Wisconsin Experience,” Transportation Research Record. 1616; Transportation Research Board, National Research Council, Washington, DC; pp. 34–41. Wu, Y., Parker, F., and Kandhal, P.S. (1998), “Aggregate Toughness/Abrasion Resistance and Durability/Soundness Tests Related to Asphalt Concrete Performance in Pavements,” Transportation Research Record 1638, Transportation Research Board, National Research Council, Washington, DC. pp. 85–93. You, Z., and Buttlar, W.G. (2004), “Discrete Element Modeling to Predict the Modulus of Asphalt Concrete Mixtures,” Journal of Materials in Civil Engineering ASCE, Vol. 16, No. 2, pp. 140–146.

376

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Multidirectional behavior of bituminous mixture P. Clec’h, C. Sauzéat & H. Di Benedetto Département Génie Civil et Bâtiment, Université de Lyon—ENTPE, Vaulx-En-Velin, France

ABSTRACT: A complex three-dimensional stress field is generated in pavement structure when a wheel passes. However, few experimental results on the cyclic multidirectional behavior of bituminous mixtures are available. An experimental triaxial test device has been developed at the ENTPE/DGCB laboratory to better understand this three-dimensional behavior. The device allows applying, on cylindrical specimens, monitored radial pressure and axial loadings. In order to make experiments easier, the innovative triaxial cell has been divided into two parts which are fixed around the specimen. Constant strain-rate tests with constant confinement pressure have been performed at 20°C. Complex modulus and complex Poisson’s ratio have been obtained for different axial strain levels. 1

INTRODUCTION

When wheels pass over road structures, they generate a complex three-dimensional stress field inside the pavement. Up to now, a lot of simple tension-compression tests have been performed. Comparatively, rather few experimental results concerning the multidirectional behavior of bituminous mixtures are available. None of the existing laboratory techniques is able to reproduce exactly the general stress paths existing in the road. Nevertheless, different authors agreed to underline the importance of considering triaxial behavior including confining pressure (Aussédat 1977, Fwa et al. 1997, Deshpande et al. 1999, Collop et al. 2001, Ebels et al. 2006, Ossa et al. 2006, Taherkhani et al. 2007 among others). The objective of this paper is to better understand the three-dimensional behavior of bituminous mixtures through constant strain-rate tests with constant confining pressure. During these tests, at different given axial strain levels, complex modulus tests are performed after axial stress stabilization. Two different cases are considered: one test is performed without confinement and another one with a confining pressure of 200 kPa. This paper presents the experimental device and the results obtained at 20°C for a BBSG French type bituminous mixture. The aim of the study is to quantify the influence of stress and strain histories on the complex Young’s modulus and complex Poisson’s ratio values. 2

EXPERIMENTAL DEVICE

An INSTRON 1273 loading frame and a servo-hydraulic actuator with a maximum load capacity of ±250 kN and a ±125 mm axial stroke are used to apply an axial load on the specimen. For the presented testing program, axial load is measured with a removable 50 kN load cell (Fig. 1). To ensure uniformity of temperature, the specimens are stored in the temperaturecontrolled chamber at the testing temperature (20°C) for at least 12 hours prior to testing. The triaxial cell is divided into two metallic shells which can be fixed easily around the specimen. They have been designed to resist a pressure of 10 bar. The two shells contain a polyurethane flexible chamber, which surrounds the cylindrical specimen and allows applying a constant (or cyclic) confining pressure (see Figure 2a). For the presented tests, this chamber is filled with air. The pressure is controlled with a pressure filter-regulator and is applied slowly to the cell. An extension of the system will use fluid allowing cyclic lateral loading up to 10 Hertz. 377

Figure 1.

Schematic view of the triaxial testing equipment.

Figure 2. a) Schematic view of the triaxial cell designed at the DGCB/ENTPE, b) Location of axial and radial strain gauges on the specimen (same configuration on the opposite side).

The aim of this design with two metallic shells is to make experiments easier. It is designed to be fitted around the specimen after the axial loading device is set up. The required dimensions of the cylindrical specimen are 75 mm in diameter and 120 mm in height. The principal stresses which are applied on the cylindrical sample (see Figure 3) are given by: Q ⎧ ⎪σ z = A ⎨ ⎪⎩σ r = σ θ = P

(1)

where Q is the axial load, P is the confining pressure and A is the cross-section area of the specimen. During the presented test program, strains are measured with four 50 mm long strain gauges, which are stuck on the specimen. Two axial strain gauges centered in the mid height of the specimen are stuck diametrically opposite. Two radial strain gauges are stuck centered on each axial strain gauge (see Figure. 2b). The average of the signals of the two opposite 378

Table 1.

Test parameters.

Specimen number

Compaction (%)

σr kPa

G5E1

97.0

G4E1 97.8

Figure 3.

0

0 200 200 200

Point number Point 0 Point 1 Point 2 Point 3 Point 4 Point 5 Point 0 Point 0P Point 1 Point 2

εi for which E* and ν* are measured % ε0 = 0 ε1 = 0.197 ε2 = 0.390 ε3 = 0.618 ε4 = 0.374 ε5 = –0.010 ε0 = 0 ε0P = 0.010 ε1 = 0.227 ε2 = 0.491

Schematic stress-strain path applied to the specimens.

strain gauges is considered in the analysis for axial and radial strains. The homogeneity of the strain field is also checked by comparing the values given by opposite gauges that should remain close during the whole test. 3

MATERIAL AND SAMPLE PREPARATION

The French type of bituminous mixture, used for wearing course, BBSG (“Béton Bitumineux Semi-Grenu”) is chosen. It represents a common bituminous mixture for which many data are available. It is made using diorite crushed aggregates from “Moreau” quarry and designed to have the following proportions of aggregates (by mass): 32% for 0/2, 23% for 2/6 and 43% for 6/10. 2% of limestone filler and 6% (aggregate weight) of 50/70 penetration grade bitumen are used in the mixture. Cylindrical samples, 138 mm in diameter and 160 mm in height, are compacted using a static double effect oedometric technique with a hydraulic press. The targeted air void content (volume of void divided by the total volume) of these samples was chosen to be 4%. This compaction method is easy to perform in laboratory and provide samples with good homogeneity (Yan 1992, Doubbaneh 1995). Prior to mixing, aggregates are sampled (NF EN 932-1, NF EN 932-2), washed and heated at 160°C at least 8 hours. Bitumen is heated at the same temperature between 3 and 5 hours. 379

Next, aggregates and bitumen are mixed with the 50/70 bitumen at a temperature of 150°C during 3 minutes maximum (NF EN 12697-35). Then the mixture is settled into a cylindrical mould. No radial strain is possible during compaction, which is performed at a loading rate of 10 kN/s until the sample height of 160 mm is achieved. The maximum load is maintained during 10 minutes. After cooling, the sample is extruded from the mould. Then, after a minimum of two weeks, a 75 mm diameter core is taken from the central part of the sample. Both ends of the specimen are sawn to obtain the cylindrical specimens to be tested, which is 75 mm in diameter and 120 mm in height. The specimens are stored in a room at 7°C, at least one week, until they are required for testing (Olard 2003). This paper presents results for specimens G4E1 and G5E1. The first figure refers to the batch number and the second figure refers to the specimen number in the batch. G4E1 compaction (real volume of aggregates and bitumen divided by the apparent total volume) amounts to 97.8% and G5E1 compaction to 97.0%. 4

TEST DESCRIPTION

Two tests are performed at a temperature of 20°C. Test on G5E1 specimen is without confinement and a confining pressure of 200 kPa is applied on specimen G4E1 (Fig. 3). Complex Young’s modulus (E*) and complex Poisson’s ratio (ν*) are investigated for different axial strain levels during the two tests (Table 1). At the beginning of each test, a complex modulus test is performed when no confining pressure is applied and when the axial strain is still null (Point 0, σr = 0, ε0 = 0). During complex modulus test, sinusoidal axial strain is applied for frequencies from 0.03 Hz to 10 Hz at strain amplitude of about 60 μdef. It has been shown that the material behavior remains inside the linear domain for this small level of deformation (Di Benedetto et al. 2007). The sinusoidal evolution with time of the three measured values is defined by the following equations: εz(t) = ε0z sin (ωt), σz(t) = σ0z sin (σt + φE) and εr(t) = ε0r sin (ωt + π + φν) = −ε0r sin (ωt + φν). φE is the classical phase angle between the axial strain and the axial stress, and φν is the phase angle between the axial strain and the opposite of radial strain. Considering complex notations where j is the complex number defined by j2 = −1, the measured values are written: εz*(t) = ε0z ejωt, σz*(t) = σ0z e j(ωt + φE) and εr*(t) = ε0r e j(ωt + π + φν) = –ε0r ej(ωt + φν). If the material is considered as isotropic, complex modulus E* and complex Poisson’s ratio ν* can be obtained from these homogeneous tests with:

E * (ω ) =

σ 0 z jφE ε ε r* jφE * * and = E ( ω ) e = e ν ( ω ) = − = ν * (ω ) e jφν = 0r e jφν * * ε 0z ε 0z εz εz

σ z*

(2)

For G4E1 test, the confining pressure of 200 kPa is applied while axial stress σz is maintained equal to zero. Then axial strain is set back to zero and another complex modulus test is performed after relaxation (Point 0P, σr = 200 kPa, ε0P = 0). Then, a constant compression strain-rate of 0.25% /min is applied to the specimen up to a first axial strain level ε1. Axial strain is held constant (relaxation) until stress stabilisation. A complex modulus test is performed at this strain level (Point 1). The same procedure is repeated for other axial strain levels εi (Point i). The complex modulus (resp. Poisson’s ratio) obtained for axial strain level εi is named Ei* (resp. νi*). After Point 3, G5E1 specimen is unloaded with a strain-rate of 0.25%/ min and complex modulus tests are also performed at different axial strain levels during unloading. The different axial strain levels (εi) for G5E1 and G4E1 tests are presented in Table 1. 5

TEST RESULTS

Figure 4 shows the stress-strain paths q (= σz—P) versus εz, for test on G5E1 specimen with null radial pressure and for test on G4E1 specimen with a 200 kPa confining pressure. Deviatoric 380

Figure 4.

Stress-strain paths for tests on G5E1 sample and G4E1 sample.

Figure 5. a) Evolution of axial and radial strains as a function of time for G5E1, b) Evolution of axial stress as a function of time for G5E1.

stress q is higher for G4E1 specimen during loading than for G5E1 specimen at a same axial strain level, which was expected. G5E1 specimen failure occurs in tension. A crack appears outside the area of axial strain gauges measurement. At Point 5, a small stress increase during complex modulus test results in specimen global failure. G4E1 specimen failure occurs during stress stabilization at the compression axial strain ε3 0.756%. Indeed axial stress which is relatively high (6 MPa) could not become stable and the axial strain gauge which is used to monitor the hydraulic jack breaks. Figure 5a) shows the evolution of axial and radial strain as a function of time and figure 5b) shows the evolution of axial stress as a function of time for test on G5E1 specimen. During the compression phase, when the general axial strain increases from ε0 = 0% to ε3 = 0.618%, the radial strain decreases down to –0.442% (extension). Figure 6a) shows the evolution of axial and radial strains as a function of time and figure 6b) shows the evolution of axial stress as a function of time for the test on G4E1 specimen. 5.1 Complex modulus test results 5.1.1 Complex Young’s modulus (E*): Figure 7a) (respectively b) shows the evolution of the norm of complex modulus |E*| at 20°C as a function of frequency for G5E1 specimen (respectively G4E1 specimen) at the different axial strain levels where complex modulus tests were performed. 381

Figure 6. a) Evolution of axial and radial strains as a function of time for G4E1, b) Evolution of axial stress as a function of time for G4E1.

Figure 7. a) Evolution of |E*| as a function of frequency for G5E1 sample at different axial strain levels at 20°C, b) Evolution of |E*| as a function of frequency for G4E1 sample at different axial strain levels at 20°C.

Before applying confining pressure and starting loading (Point 0, table 1), the measured norm of the complex modulus |E0*| at 20°C varies from 1400 MPa for 0.03 Hz up to 8000 MPa for 10 Hz. The |E0*|differences between the 2 specimens are smaller than 7%, which indicates a rather good repeatability of the test for this first level. During the compression loading phase, |Ei*| increases with axial strain level whatever the frequency, with or without confining pressure. During the unloading phase, |Ei*| decreases with axial strain level whatever the frequency. For identical axial strains during loading and unloading (for example ε2 and ε4), |Ei*| is much smaller after unloading (|E4*| in the example). |E4*| and |E5*| are even smaller than the initial value |E0*| whatever the tested frequency. For G4E1 test, it can be noticed that application of 200 kPa confining pressure induces very little change in the norm of the complex modulus (|E*0P | values are very closed to |E0*| values). To study |Ei*| increase or decrease with axial strain level, the parameter Δ|E*| is used. Δ|E*| is obtained at each frequency and each strain level from the following equation:

(

)

(

)

Δ | E* i , f = | E* ε i , f j | − | E* ε 0 , f j | = | E i* |

(

j

)

* ( f j )− | E 0 | ( f j )

(3)

where εi is the axial strain level and fj the frequency which ranges between 0.03 Hz to 10 Hz. Figure 8 a) (respectively b)) shows the evolution of Δ|E*| as a function of frequency for G5E1 sample (respectively G4E1) at different axial strain levels. During loading, the difference between |Ei*| and |E0*| is independent of frequency with or without confining pressure. During the unloading phase, the difference Δ|E *| increases in absolute value when frequency increases (Figure 8 a). 382

Figure 8. a) Evolution of Δ|E *| as a function of frequency for G5E1 sample and for different axial strain levels at 20°C, b) Evolution of Δ|E *| as a function of frequency for G5E1 sample and for different axial strain levels at 20°C.

Figure 9. Evolution of Δ|E*| as a function of axial strain for G5E1 and G4E1 samples and for different frequencies at 20°C.

Figure 9 shows Δ|E *| values for G5E1 test and G4E1 test as a function of axial strain. During loading phase, as Δ|E *| is independent of frequency, it is possible to identify four points for G5E1 test (ε0 = 0, ε1 = 0.197%, ε2 = 0.390% and ε3 = 0.618%) and four points for G4E1 test (ε0 = 0, ε0 = 0,010% ε1 = 0.227% and ε2 = 0.491%). Δ|E*| increases more significantly with axial strain when the 200 kPa confining pressure is applied. For identical axial strains, Δ|E*| is higher with 200 kPa confining pressure. Figure 10 shows complex modulus values at 20°C in Black space for specimens G5E1 and G4E1 at different axial strains levels. For each frequency, the phase angle ϕE* decreases when axial strain level increases. The effect of axial strain εz on ϕE* is complex. With or without confining pressure, E* curve seems to shift to lower phase angle ϕE* and higher complex modulus norms |E*| when axial strain level increases. The application of confining pressure seems to reduce ϕE* at identical axial strain levels. Figure 11 a) (respectively b)) shows the evolution of Δ|E*| as a function of ΔϕE * for G5E1 sample (respectively G4E1) for different axial strain levels. ΔϕE * is obtained with the following equation: ΔϕE*

( i , f j ) = ϕE* ( ε i , f j ) − ϕE* ( ε 0 , f j )

ΔϕE* depends on frequency. 383

(4)

Figure 10. Complex modulus in Black space for G5E1 and G4E1 samples at 20°C for different axial strain levels.

Figure 11. a) Evolution of Δ|E *| as a function of Δϕ|E*| for G5E1 sample and for different axial strain levels at 20°C, b) Evolution of Δ|E*| as a function of Δϕ|E*| for G4E1 sample and for different axial strain levels at 20°C.

5.1.2 Poisson’s ratio (ν*): Figure 12 a) (respectively b)) shows the evolution of the norm of Poisson’s ratio |ν *| at 20°C as a function of frequency for G5E1 sample (respectively G4E1 sample) for different axial strain levels. During the compression phase, |νi*| increases with axial strain whatever the tested frequency, with or without confining pressure. During loading for both tests, decrease of |νi*| with frequency is more important when axial strain level is higher. |νi*| decreases with axial strain during the unloading phase whatever the tested frequency. For close axial strain values (ε2 during loading and ε4 during unloading), |ν4*| is slightly higher than |ν2*|. The values of |ν0*| and |ν5*| obtained at close axial strain values are nearly the same. As observed previously for |E *|, the application of 200 kPa confining pressure implies little change in |ν *| [ |ν0*| and |ν1*| are very close (see Figure 12b)]. As a first approximation, in the considered frequency domain and at the temperature of 20°C, |ν*| seems to decrease linearly with log(f). |ν0*| is roughly estimated constant with frequency. For each axial strain level during the compression phase, |νi*| can be fitted by (see Figure 12):

ν i* = α ν i * log( f ) + β ν i * α|ν*| and β|ν*| can be obtained by linear regression. 384

(5)

Figure 12. a) Evolution of |ν *| as a function of frequency for G5E1 at different axial strain levels at 20°C, b) Evolution of |ν *| as a function of frequency for G4E1 at different axial strain levels at 20°C.

Figure 13.

α|ν*| as a function of axial strain for G5E1 and G4E1 samples.

Figure 13 shows the evolution of α|ν*| with axial strain level for G5E1 and G4E1 tests. α|ν*| decreases when axial strain level increases. The confining pressure seems to not or slightly influence this decrease. 6

CONCLUSIONS

Constant strain-rate tests with constant confining pressure are performed at the temperature of 20°C with an innovative triaxial testing equipment developed at the ENTPE/DGCB laboratory. The strain-rate is set to 0.25%/min during loading and unloading phases and two different confining pressures are considered, 0 kPa and 200 kPa. During these tests, at given axial strain levels, complex modulus tests are carried out after axial stress stabilization. The tested material is a French type bituminous mixture, BBSG, which was compacted with a static double effect oedometric technique. The results presented in this paper allow quantifying the influence of stress and strain histories on the complex Young’s modulus and complex Poisson’s ratio values. The main tendencies are summarized below. During the compression loading phase, the norm of the complex modulus |E*| increases with axial strain level whatever the frequency, with or without confining pressure. The difference between |Ei*| and |E0*|, Δ|E *|, is independent of frequency, with or without confining pressure. For identical general axial strains, Δ|E *| is higher with 200 kPa confining pressure than without confinement (see Figure 9). |E *| decreases with axial strain level during the unloading phase whatever the tested frequency. For identical axial strains during loading and unloading, |Ei*| is much smaller during unloading phase. 385

For each frequency, the phase angle ϕE* decreases with axial strain level increase. The presence of confining pressure seems to reduce ϕE* at identical axial strain levels. During the compression phase, |ν*| increases with axial strain whatever the frequency, with or without confining pressure. During loading for both tests, the decrease of |νi*| with frequency is more important when axial strain level is higher. The slope of |νi*| as a function of frequency, α|ν*|, decreases when axial strain increases. This decrease seems being few affected by confining pressure. |νi*| decreases with general axial strain during the unloading phase whatever the frequency. REFERENCES Aussédat, G. 1977. L’essai de fluage dynamique dans la formation des enrobés et le dimensionnement des chaussées. Bulletin de liaison des laboratoires des ponts et chaussées—bitumes et enrobés bitumineux, numéro spécial V ISSN 0458-5860 [in French]. Clec’h, P. 2006. Comportement des enrobés bitumineux sous sollicitations multidirectionnelles—essais de module complexe sur éprouvettes parallélépipédique et cylindrique, master recherche ENTPE. Lyon. [in French] Collop, A. C. & Shahab, K. 2001. Permanent deformation in idealised “sand asphalt” bituminous mixtures. Journal Road Materials and Pavement Design, vol. 2 n°1: p. 7–28. Deshpande, V. S. & Cebon, D. 1999. Steady-state constitutive relationship for idealised asphalt mixes. Mechanics of Materials, vol. 31 n°4: p. 271–287. Di Benedetto, H., Partl, M. N., Francken, L. & De la Roche Saint André, C. 2001. Stiffness testing for bituminous mixtures. Journal of Materials and Structures, vol. 34: p 66–70. Di Benedetto, H. & Corté, J. F. 2005. Matériaux routiers bitumineux 2: constitution et propriétés thermomécaniques des mélanges, 288 p, Lavoisier. [in French] Di Benedetto, H., Neifar, M., Sauzéat, C. & Olard, F. 2007. Three-dimensional thermo-viscoplastic behaviour of bituminous materials: the DBN model. Journal Road Material and Pavement Design, issue 2: p. 285–315. Doubbaneh, E. 1995. Comportement mécanique des enrobés bitumineux des “petites” aux “grandes” déformations. Thèse de doctorat. INSA de Lyon. 219 p [in French]. Ebels, L. J. & Jenkins, K. J. 2006. Determination of materials properties of bitumen stabilised materials using tri-axial testing. 10th international conference on asphalt pavements. p. 12–17. Québec city, Canada. Fwa, T. F., Tan, S. A. & Low, B. H. 1997. Relating triaxial test properties of asphalt mixtures to mix parameters determined by Marshall stability test. Journal of testing and evaluation, vol. 25 n°5: p. 471–478. Olard, F. 2003. Comportement thermomécanique des enrobes bitumineux à basses températures. Relations entre les propriétés du liant et de l’enrobé. Thèse de doctorat. INSA de Lyon. 221 p [in French]. Ossa, E. A. & Collop, A. C. 2006. Dilation behaviour of asphalt mixtures. Journal Road Materials and Pavement Design, vol. 7 special issue European Asphalt Technology Association (EATA): p. 93–109, Nottingham. Taherkhani, H. T., Grenfell, J. R. A., Collop, A. C., Airey, G. D. & Scarpas A. 2007. Characterization of repeated creep recovery behavior of asphaltic mixtures. Advanced characterization of pavement and soil engineering materials: p. 271–279. London.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Design of pavements containing foamed bitumen recycled layers M. Losa, R. Bacci, A. Terrosi Axerio & P. Leandri Department of Civil Engineering, University of Pisa, Pisa, Italy

ABSTRACT: Cold in place recycling of asphalt pavements with foamed bitumen is a technique traditionally used for base course or subbase construction on low or medium volume roads, but in some recent applications it has been used on heavy trafficked roads to build base courses upon which the binder course is laid directly. For the last type of applications, improvements of material stiffness are required and they are obtained by increasing the cement content which has the positive effect of reducing permanent deformation, but the negative effect to make the material less flexible. The aim of this paper is to identify a specific design criteria for this type of applications, which is based on the results of experimental tests carried out on these materials, and which try to take into account undesired effects of the high cement content on material performance. A new concept of fatigue life for foamed bitumen stabilized courses could be developed which can be used for the design of heavy trafficked road pavement rehabilitation. 1

INTRODUCTION

Cold in place recycling (CIR) of asphalt pavements is a cost effective technique for reconstruction of existing pavements widely used worldwide. In particular, the CIR technique with foamed bitumen is recognized as more cost effective compared to the use of bitumen emulsion and, nowadays, this technique is becoming more popular; even if usually it has been used for reconstruction of base course or subbase on low or medium volume roads, in some recent applications this technique has been used for reconstruction of base courses too, upon which the binder course is laid directly. It is well known that in the CIR process foamed bitumen glues together granulated pieces of Reclaimed Asphalt Pavement (RAP) rather than causing a complete remix of the bituminous mixture as with hot mixes or other processes which use bitumen emulsion. It is for this reason that foamed bitumen mixtures performance are strongly influenced by RAP percentages (Ruenkrairergsa et al. 2004). At the optimum content of foamed asphalt, although mixtures with higher percentage of RAP produce lower indirect tensile strengths, their retained strength, under influence of water, is higher. On the other side, 50% RAP mixtures produce higher resilient moduli, longer fatigue resistance and lower permanent deformation than those with higher RAP percentages. Based on these known results, foam bitumen mixtures are usually produced by using about 50% of RAP and 50% of reclaimed or new crushed stone. The mixes produced with a foamed bitumen are normally of a less stiff nature and tend to be used in pavements on less demanding roads with respect to amount of heavy traffic that do not require a high degree of stiffness. In order to use foamed bitumen mixtures on heavy trafficked roads, the stiffness of materials is improved by including cement into the process, but the stiffness will not be immediate and it will take time to develop. It is for this reason that in the early stage the mixture is more sensitive to permanent deformation and the internal structure can be damaged by traffic loads. Moreover, considering that reclaimed materials are obtained from binder and base layers, with low bitumen content, they tend to contain a higher proportion of cement as well as foamed bitumen. This will make the recycled material more similar to a cement bound material than to a bitumen bound product. Anyway the material, correctly formulated, is suitable for use in road pavements, but the real engineering properties must be considered into design of pavements in order to define where and how they should be used. 387

Figure 1.

Types of foamed mixes, after Asphalt Academy (2002).

Some cases of premature failure are documented in literature. Two principal types of failure have been identified: one is related to the formation of transverse or block cracking (Loizos & Papavasiliou 2008, Ramanujam & Jones 2007), the other is related to moisture susceptibility of some foamed asphalt mixtures which exhibits a severe loss of strength when subjected to moisture (Chen et al. 2006). Both of them are strongly related to use of cement in the mixture. It is known that high cement contents make the mixture stiffer (see Figure 1) with less flexibility which make them prone to cracking once the bending strength has been exceeded under loading or shrinkage occurs. As far as moisture sensitivity is regarding, experimental tests have shown that cement has an important role in reducing moisture sensitivity of mixture more than bitumen, while bitumen content is important in reducing water permeability of the mixture. Taking into account these aspects, the use of foamed bitumen recycled mixture must be carefully evaluated, and design of pavements must take into account engineering properties. A methodology for design of pavements containing foamed bitumen mixture layers has been proposed recently, and it is based on the development of transfer functions which account for the two-phase behavior of these materials: the stiffness reduction phase and the accumulation of permanent deformation (Long & Theyse 2004). In this technical paper, taking into account the aforementioned problems, we analyze some pavement sections which have been designed and constructed on a heavily trafficked Italian high speed road. In particular, we describe design criteria, tests carried out for design and quality control of mixtures, and finally in situ evaluation of pavement performance to check the agreement between design considerations and real behavior of pavements. What is important to note is that they are real pavements and not experimental sections for which more severe quality control tests can assure a better quality of construction; on these pavements only routinely control tests have been carried out and enterprises have worked as they usually work for road construction. It is for this reason that results are reflecting the best performance we can obtain in practice by using this technique. 2

PAVEMENT DESIGN CRITERIA

Some sections of a high speed road in Tuscany (Italy) required constant repair for many years. In 2004 experimental tests with FWD and GPR were carried out to evaluate the existing pavement structure, and test pits were excavated to obtain samples for laboratory tests; based on the results of these data, a rehabilitation program started up. The design of pavement rehabilitation was carried out for 35 * 106 of 100 kN equivalent axle loads and taking into account the opportunity to re-use existing materials. Different recycling techniques were examined (cement, bitumen emulsion, foamed bitumen) and finally, considering costs and expected 388

Figure 2.

Existing and pavement rehabilitation sections.

performance of the different alternatives, available funds and the opportunity to rehabilitate more as possible pavement sections, the Administration chosen to use foamed asphalt recycling technology after checking that existing pavement structures were suitable to the process. At that time, not enough information was available concerning field performance of foamed treated recycled materials, and available data were limited to low or medium volume roads. For design of pavement rehabilitations the following prudential criteria were considered: – Due to the lack of knowledge about transfer functions for fatigue resistance and permanent deformations of foamed bitumen recycled materials, they were considered as a cement stabilized base and the limit value of horizontal strains was assumed equal to 60 με; – In order to reduce strains at the bottom of foamed bitumen recycled layers, the subgrade was lime-cement-stabilized to improve the resilient modulus up to 180 MPa; subgrade stabilization had the aim to reduce also capillary rise in the base layer which could be exposed to moisture wick up; – In order to have thin asphalt layers on top of the base that will not be too soft in the summer period, causing an increase of stress and strain at bottom of the foamed asphalt layer, a high modulus asphalt concrete (HMAC) was introduced into pavement design; the elastic modulus of asphalt was assumed equal to 12,000 MPa @20°C and 10 Hz frequency. This mixture has been designed based on French principles of the “Enrobé à Module Élevé” (EME), by using very hard bitumen (pen grade ≤25 dmm). Existing and new pavement sections with design parameters are reported in Figure 2. Pavement rehabilitation works started in 2006 and 23.3 km of the road pavements have been rehabilitated according to design. 3

MIX DESIGN OF FOAMED ASPHALT MIXTURES

Mix design was performed on materials taken from test pits and it was carried out in accordance to Italian Motorway Agency specifications. Laboratory testing was carried out to determine gradation of existing materials, the percentages of RAP and of reclaimed aggregates from the existing foundation to be used in combination in order to fulfill the aggregate gradation specifications reported in Figure 3. It was found that by combining 50% of RAP and 50% of reclaimed aggregates, the aggregate gradation of the mixture satisfied specifications. A 70/100 penetration bitumen was used which allowed to achieve an expansion ratio ER > 20 and a Half-Time T½ > 25 s at 180°C and 2% of injecting water. Laboratory tests were carried out on blended samples stabilized with foamed bitumen contents ranging from 2.5% to 3.5%, in 0.5% increments together with cement content ranging from 1.5% to 2.5% as active filler. 389

100 90 80 70 % Passing

60 50 40 30 20 10 0 0,01

0,1

10

1 Sieve size (mm)

sample 1

Figure 3.

sample 2

sample 3

sample 4

RAP gradation.

Table 1.

ITS after 24 + 72 hour curing.

% foamed bitumen

% cement

ITS (MPa)

2.5 2.5 2.5 3.0 3.0

1.5 2.0 2.5 1.5 2.0

0.37 0.43 0.41 0.35 0.34

% foamed bitumen

% cement

ITS (MPa)

3.0 3.5 3.5 3.5

2.5 1.5 2.0 2.5

0.39 0.29 0.30 0.42

Specimens were compacted by the Gyratory Compactor in 150 mm diameter molds, with the following parameter sets: load pressure 600 kPa; total number of gyrations 180; rotation speed 30 r/min; inclination angle 1°25’. Compacted specimens were cured for 24 hours at 25°C and then for 72 hours in a climatic chamber at 40°C and at 95% controlled humidity. Specimens were tested in laboratory to evaluate short term performance, and the following mixture characteristics were determined at equilibrium water content (Houston & Long 2004): – Bulk specific gravity of the mixture; – Indirect Tensile Strength (ITS) at 25°C; – Stiffness modulus at 20°C. In accordance to the Italian Motorway Agency specifications, ITS tests were performed at 25°C and with a speed of the vertical displacement equal to 20.2 mm/min, whilst stiffness modulus was determined, according to UNI EN 12697-26 Annex C, at 20°C and with a loading frequency of 1 Hz corresponding to a rise time of 200 ms as required from specifications. The foamed bitumen optimum content for optimal strength was found to be at 2.5% and 2.0% cement as active filler (Table 1). For these contents, the ITS at 25°C was greater than 0.40 MPa and the stiffness modulus @20°C and 1 Hz frequency, determined on the specimens with the bitumen optimum content and cured in the same conditions, resulted equal to 2750 MPa with a standard deviation σ = 312 MPa. 4

PERFORMANCE AND MONITORING TESTS

During construction we carried out tests on samples of the mixture taken in situ, compacted by the gyratory compactor and cured by following the same procedures adopted for the mix 390

design. The following quality control tests have been carried out on the foamed asphalt recycled mixtures at equilibrium water content after curing: – Indirect Tensile Strength @25°C; – Resilient modulus @20°C and 1 Hz frequency (Stiffness Modulus); Field density tests were carried out to check the compaction ratio while field monitoring was carried out by Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR); in order to evaluate immediate performance and the evolution of the elastic modulus, early tests were performed after 24 hours since recycling process, whilst post-construction monitoring was carried out after 90 days. Elastic moduli were evaluated considering layer thickness calculated by the GPR data and calibrated with thickness measured on cores. Results of tests carried out on mixtures and layer field performance in some of the more representative sections, at the early stage, are shown in Table 2. It can be seen that the in situ elastic modulus at the early stage (after 24 h) is more dispersed (Coefficient of Variation COV = 47%) than after 90 days (COV = 32%). Values at early stage are more sensitive to the mix properties and are more representative of the goodness of the work. The results of performance tests carried out by FWD and GPR on pavements 90 days after construction are reported in Table 3. We can observe that some values of the asphalt mixture backcalculated modulus seem to be very high, but these high values, which are typical of high modulus asphalt mixtures, have been confirmed by values determined in laboratory on cores taken from pavements. 4.1 Fatigue testing In order to evaluate fatigue resistance of foamed recycled layers, tests have been carried out on specimens sawed from full depth cores taken in different sections. On some sections cores disintegrated showing that poor quality recycled layers have been produced. Fatigue tests were carried out in indirect tensile fatigue configuration, in a controlled strain mode, according to UNI EN 12697-24-E. Fatigue failure is determined when stiffness modulus drops to 50% of initial value (Thammavong & Lavansiri 2006). Results are shown in Figure 4. The fatigue model developed for these mixes is composed of two parts: the first part is related to high strain level and, as it is well known, foamed bitumen stabilised mixes have a much lower fatigue life compared to HMAs when they are compared at the same tensile strain level (Saleh 2007); the second part regards lower strain levels for which the fatigue resistance of the mixture is significantly better. It has been checked that at strain levels lower than 80 με the fatigue life is greater than 106 and the stiffness modulus, after this number of cycles, didn’t

Initial tensile strain (με)

1000

100 10

Figure 4.

100

1000 10000 Cycles to failure

Fatigue resistance test results.

391

100000

1000000

Table 2.

Results of tests during and after pavement section rehabilitation.

Location

ITS (MPa)

Stiffness modulus (MPa)

Elastic modulus after 24 h (MPa)

Elastic modulus after 90 days (MPa)

28 + 850 E 14 + 900 E 13 + 450 E 12 + 400 E 12 + 150 E 11 + 100 E 7 + 000 E 5 + 500 E 1 + 800 E 5 + 100 W 7 + 000 W 7 + 400 W 10 + 500 W 22 + 350 W 23 + 950 W 25 + 840 W 26 + 850 W 29 + 500 W

0.22 0.42 0.42 0.32 0.33 0.30 0.20 0.43 0.43 0.40 0.50 0.36 0.25 0.25 0.35 0.21 0.31 0.21

2405 5565 6640 1950 3850 2840 2495 5490 5555 4500 6545 3360 2955 2630 4145 2795 3505 2330

– – 1055 1795 950 1875 450 600 – 585 1100 920 – 1575 830 1965 1185 480

4900 4900 2800 3100 3450 5950 4500 5650 1950 4550 4550 2650 2450 3200 2300 3600 5850 4650

Mean Stand. deviation

0.33 0.09

3864 1509

1098 520

3994 1271

Table 3.

Results of FWD tests 90 days after rehabilitation. Thickness* (mm)

Km

Asphalt concrete

Foamed bitumen recycled base

28 + 850 E 14 + 900 E 12 + 150 E 12 + 400 E 13 + 450 E 11 + 100 E 7 + 000 E 5 + 529 E 1 + 800 E 5 + 100 W 7 + 000 W 7 + 401 W 10 + 500 W 22 + 350 W 23 + 950 W 25 + 850 W 26 + 850 W 29 ± 500 W

145 125 190 200 195 220 150 125 140 140 130 135 140 170 150 140 160 155

250 265 240 205 185 260 380 280 240 195 260 205 260 190 230 195 245 230

*

Elastic moduli (MPa) after 90 days LimeCement stabilized subbase

Asphalt concrete 20°C

Foamed bitumen recycled base

LimeCement stabilized subbase Subgrade

490 430 – – – 420 410 395 – 475 430f 430 – 310 – 325 265 425

7050 9980 6050 6150 8000 6850 14750 14350 9450 13350 11700 6650 7500 12150 12900 10950 11100 13400

4900 4900 3450 3100 2800 5950 4500 5650 1950 4550 4550 2650 2450 3200 2300 3600 5850 4650

1150 2300 – – – 4850 3950 4150 – 2850 3500 2000 – 2050

Thickness obtained from GPR data analysis.

392

1450 4150 4150

265 285 210 800 475 665 675 265 325 390 495 550 470 300 195 250 305 250

reduce at all; this strain value can be considered a safe value with regard to the fatigue risk and it can be assumed as limit value of strains in foamed asphalt recycled layers (Molenaar 2008). A fatigue relationship could be identified for low strain levels, but it should not be reliable being the regression line quite horizontal and with the correlation coefficient too low. 5

ANALYSIS OF RESULTS

The analysis of data reported in Table 2 shows that performance of the recycled layer is not uniform on all the sections and it differs from results obtained in laboratory during mix design. Two main reasons have been identified to explain this circumstance: – Inhomogeneous work conditions which could have determined variations in the mixture; – Different support conditions which could have determined variations in the effectiveness of stabilization or compaction. It is well known that foamed asphalt mixtures prepared in laboratory are different from those mixed in field by using the recycling machine; moreover, during construction it is more difficult to control the real bitumen and cement content, and we obtain mixtures which are different from those designed. Many difficulties arise in the field concerning the type and temperature of bitumen, which influence the foamability of the bitumen; for all these reasons, and taking into account also the costs of the two binders, enterprises prefer to use more cement than bitumen producing mixtures that allow obtaining higher stiffness in order to avoid penalties for construction defects. From the analysis of results reported in Table 2, we can see that a good relationship exists between ITS and stiffness moduli determined on samples taken in the field, compacted and cured in the same conditions as reported in paragraph 3 (Figure 5). This relationship is valid for ITS values greater than 0.20 MPa; smaller values refer to very poor mixes and aren’t significant from a practical point of view. The relationship between ITS and stiffness modulus explains the influence of the cement on the mixture properties; the increase of the cement content produces an increase of both the tensile stress mixtures can withstand before failure and the elastic stiffness. On the other side, the reduction of flexibility makes mixtures prone to cracking once the bending strength has been exceeded under loading. Since stiffness modulus and ITS at equilibrium water content are strongly related, the cement and bitumen contents can be determined to enhance both the strength and stiffness of the material, but without compromising flexibility of the mix. On the other side, no relationship has been found between stiffness moduli determined in laboratory on specimens compacted by the gyratory compactor and elastic moduli determined in field after 24 hours. Local conditions, in particular subgrade stiffness, can influence compaction of the mixture and performance of the layer so that it is difficult to forecast the behavior of the mix in the field. This aspect is of particular importance to evaluate the behavior of the mix in the curing period when it is more sensible to traffic loading; in this period stress produced by the traffic load can damage the action of the binder and penalize long term layer performance. What is important to note is the evolution of stiffness in the recycled layer (Loizos & Papavasiliou 2006); in the figure 6 we have reported the elastic modulus after 24 hours versus the ratio between elastic moduli after 90 days and 24 hours. As you can see this ratio is strongly influenced by the initial value of the elastic modulus after 24 hours when it is less than 600 MPa; otherwise, when this modulus is greater than 600 MPa this ratio is in the range from 2 to 5, with lower values (from 2 to 3) when the elastic modulus after 24 hours is greater than 1500 MPa. The relationship is valid for values of the elastic modulus after 24 h greater than 400 MPa; lower values refer to very poor mixes. The significant increase of the elastic modulus after 90 days is strongly related to the percentage of the active filler introduced in the mix compared to that of the foamed bitumen; for higher percentage of cement compared to bitumen we have lower initial elastic modulus and significant increase of the modulus with time; obviously, this will result in a mix which will be stiffer and more sensible to cracking. 393

Figure 5.

Stiffness modulus versus ITS on specimens after 24 + 72 hours curing.

Figure 6.

Increase of elastic modulus with time.

6

RECOMMENDED DESIGN CRITERIA

Based on the results obtained in the field, some design criteria can be identified for pavements containing recycled foamed bitumen, which can integrate those reported in the literature (Wirtgen, 2004), when stiffer mixtures are required for unconventional applications. Three principal phases can be identified in the life of these pavements: – The first phase refers to the period soon after construction of the recycled layer up to the principal curing period of the mixture, when it reaches a satisfactory elastic modulus; – The second phase refers to the period after curing, during which a stiffness reduction occurs probably due to cracking or micro-cracking of the layer; – The third phase refers to the steady state, at lower stiffness values, after layer fatigue cracking. Obviously, the first and the third phases are the more critical in the service life of the pavement. In order to explain what happens in these two phases, some simulations have been carried out for evaluating stresses and strains in recycled layers. One section has been chosen, which is composed of 150 mm of asphalt concrete and 230 mm of foamed asphalt recycled layer. Two values of the elastic modulus have been considered for the foamed asphalt mix, one of which refers to the layer soon after construction (600 MPa), the other refers at the end of the principal curing period (7 days). Three different levels of stiffness have been considered for the subgrade (100, 150 and 200 MPa) The load is equal to 50 kN and is distributed on a circular surface with a pressure of 700 kPa. In order to evaluate strain level in the third phase, another section has been simulated, where the foamed asphalt recycled layer has an elastic modulus equal to 3400 MPa which, 394

Table 4.

Stress/strain distribution in foamed bitumen treated layer.

Thickness (mm)

Elastic modulus (MPa)

HMA

Foamed asphalt

HMA @20°C

Foamed asphalt

150 150 150 150 150 150 190

230 230 230 230 230 230 240

6200 6200 6200 6200 6200 6200 2950 2950

600 600 600 2300 2300 2300 3440 1720

*

Stress* (MPa)

Strain** (μm/m)

Subgrade

σxx

σzz

εxx

εzz

200 150 100 200 150 100 210 210

–0.067 –0.072 –0.107 –0.209 –0.233 –0.264 –0.235 –0.158

0.052 0.040 0.037 0.036 0.031 0.024 0.031 0.039

106 124 150 72 78 88 53 74

143 146 151 61 63 67 43 69

Principal stress (σxx) and (σzz) at the bottom of foamed asphalt layer. Principal strain (εxx) and (εzz) at the bottom of foamed asphalt layer.

**

after stiffness reduction for fatigue, drops to 50% of the initial value. Results are reported in Table 4. They show that, at early stage, in the recycled layer we have stress levels lower than those determined in ITS tests but strain levels significantly higher than those admissible for these types of materials. High strain levels can damage bonds in the mixture determining quicker stiffness reduction and less fatigue resistance; this effect is more sensible on low stiffness subgrade. It is for this reason that it is suggested to open the layer to traffic after the elastic modulus is at least greater than 50% of the long term expected value. As far as strains in the reduced stiffness layer, we can see that in the case of a stiffer subgrade we have an increase of strains but they are still below 80 με, which is the value recommended to reduce fatigue risk. Probably, the estimated strain value may not be valid in the field given the simplicity of the analysis approach; however, it is a prudential value needed to overwhelm the lack of knowledge about the material behavior in the steady state. Based on these results, a conservative criterion for design of these pavements should be to evaluate strains considering the cracked layer modulus (50% of the long term expected value) and to check that these strains are less than 80 με. Although not discussed in this paper, we believe that climate induced transverse cracking can occur in these layers and they can successfully be controlled by sawing shrinkage cracks in the foamed bitumen recycled layers in the same way as this has been proposed for cement treated bases (Moolenaar 2008). 7

CONCLUSIONS

The following conclusions can be drawn: – Mixtures analyzed in this paper have been used for base layer construction on a heavy trafficked road and are characterized by a high cement content, which provides the higher stiffness needed for these types of applications compared to that obtained in traditional foamed bitumen recycled layers; – In the design of the foamed bitumen recycled mixes, the optimum foam bitumen, active filler and water content can be determined so that the ITS of the mix will be greater than a lower limit value, but this limit must not be too high (ITS ≤ 40 MPa); in order to obtain higher tensile strengths, the active filler content must increase, and this has adverse effects in terms of flexibility and fatigue resistance. For this reason, the active filler content should be lower than 2.0% and the resilient modulus at equilibrium water content after curing lower than 4000 MPa; – Design of pavements containing foamed bitumen stabilized mixtures must consider that layer life is divided in three phases, and for each phase we must check the right critical 395

parameters with particular regard to the behavior of materials in the early stage, to the stiffness reduction and to the material poor fatigue resistance; – A limit value of tensile strain, equal to 80 με, has been identified for these mixtures, which allows to reduce the fatigue risk when the material is used as base layer and on heavy trafficked roads; this value should not be exceeded both in the early stage and after stiffness reduction, and must be evaluated considering the material stiffness reduced to 50% of the value obtained at the end of the curing period. – Rehabilitated pavements will be monitored in the future, in order to obtain performance data which can make possible to determine a field fatigue relationship for foamed bitumen recycled courses to be used on heavy trafficked roads. – Considering all the aforementioned aspects, we think these mixtures, on heavy trafficked roads, should be used more conveniently as subbase instead of base layers. REFERENCES Asphalt Academy. 2002. Interim Technical Guidelines (TG2): The design and use of foamed bitumen treated materials. Pretoria, South Africa. Chen, D.H. et al. 2006. Failure Investigation of a Foamed-Asphalt Highway Project Journal of Infrastructure Systems. 33–40. Donovan, H.B. 2003. Experience with Full Depth Reclamation/Stabilization Using Expanded Asphalt (Foamed Bitumen) in Edmonton, Alberta Proceeding of 2003 TAC Annual Conference. St. John’s, Newfoundland and Labrador 21–24 September 2003. Houston, M. & Long, F. 2004. Correlations between different ITS and UCS tests protocols for foamed bitumen treated materials Proceeding of 8th Conference on Asphalt Pavements for Southern Africa Sun City, South Africa. 12–16 September 2004. Jenkins, K.J. & van de Ven, M. 2001. Guidelines for the mix design performance prediction of foamed bitumen mixes. Proceeding of 20th South African Transport Conference, South Africa. 16–20 July 2001. Jenkins, K.J. et al. 2007. Foamed bitumen mixes = shear performance? International Journal of Pavement Engineering. Vol. 8 (2): 85–98. Jenkins, K.J. et al. 2000. Developments in the use of foamed bitumen in road pavements. HERON Vol. 45 (3): 167–176. Kekwick, S.V. 2005. Best Practice: Bitumen Emulsion and Foamed Bitumen Materials Laboratory Processing. Proceeding of SATC 2005: The 24th Annual Southern African Transport Conference and Exibition. Pretoria, South Africa 11–13 July 2005. Kuvhanganani, L.T. 2008. Moisture sensitivity of selected foamed bitumen treated materials. Thesis for Master’s Degree in Technology Pavement Engineering Tshwane University of Technology. Liembenberg, J.J. & Visser, A.T. 2004. Towards a mechanistic structural design procedure for emulsiontreated base layers. Journal of the South African Institution of Civil Engineering. Vol. 46 (3): 2–8. Loizos, A. & Papavasiliou, V. 2006. Evaluation of Foamed Asphalt Cold In-Place Pavement Recycling Using Nondestructive Techniques. Journal of Transportation Engineering. 970–978. Loizos, A. & Papavasiliou, V. 2008. Evaluation of cracking in recycled pavements with foamed asphalt and cement stabilization. Pavement Cracking, Taylor & Francis Group, London, ISBN 978-0-415-47575-4: 519–527. Long, F. & Theyse, H. 2004 Mechanistic-empirical structural design models for foamed and emulsified bitumen treated materials. Proceeding of 8th Conference on Asphalt Pavements for Southern Africa Sun City, South Africa. 12–16 September 2004. Molenaar, A.A.A. & Pu, B. 2008. Prediction of fatigue cracking in cement treated base courses. Pavement Cracking, Taylor & Francis Group, London, ISBN 978-0-415-47575-4: 191–199. Saleh, M.F. 2007. Effect of rheology on the bitumen foamability and mechanical properties of foam bitumen stabilized mixes. International Journal of Pavement Engineering. Vol. 8 (2): 99–100. Ramanujam, J.M. & Jones, J.D. 2007. Characterization of foamed-bitumen stabilization. International Journal of Pavement Engineering. Vol. 8 (2): 111–122. Ruenkirairergsa, T. et al. 2004. Engineering properties of foam bitumen mixtures in Thailand Proceeding of 8th Conference on Asphalt Pavements for Southern Africa. Sun City, South Africa. 12–16 September 2004. Taha, R. et al. 2002. Cement Stabilization of Reclaimed Asphalt Pavement Aggregate for Road Bases and Subbases. Journal of Materials in Civil Engineering. 239–245. Thammavong, A. & Lavansiri, D. 2006. Stabilization of Reclaimed Asphalt Pavement Using Foamed Asphalt. Proceeding of TISD2006 Conference. Khon Kaen, Thailand. 25–26 January 2006. Wirtgen, 2004. Cold Recycling Manual—2nd edition.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Long-term study on asphalt mixture segregation in Connecticut: Preliminary results on use of MTV D.J. Nener-Plante & A. Zofka Department of Civil and Environmental Engineering, University of Connecticut, Storrs, Connecticut, USA

ABSTRACT: This paper presents a preliminary analysis of an ongoing long-term thermal segregation study of asphalt mixtures in Connecticut. This study monitors about 40 sites that were constructed between 2000 and 2003. Several factors examined throughout this study were combined with the use of a thermographic camera to provide further insight as to the material properties as well as the practical application of asphalt pavement construction. This paper discusses five pavement sections on Route 94 that were constructed with and without the use of an MTV. The sections are compared in terms of roughness and cracking data collected by automatic road analyzer (ARAN) between the construction in 2002 and year 2007. The performance data shows a qualitative and quantitative benefit of usage of the MTV in the construction. Sections constructed with the aid of an MTV displayed a significant reduction in transverse cracking as well as roughness. 1

INTRODUCTION

The vast majority of the pavements in Connecticut are constructed with hot mix asphalt (HMA). For successful placing and compaction of HMA, each step in the placement procedure must be accomplished without major temperature loss. When mix temperatures vary within the placed material the compaction and performance of the in-place pavement can be expected to vary. Large temperature differentials within the mat from discontinuous or improper paving are found to be likely to lead to segregation within the mix. Research has shown that segregated areas often perform poorly; frequently raveling and breaking up at much younger ages than areas with tighter surface texture. It has been found that temperature differentials of more than 10°C (19°F) in HMA mats are associated with segregated areas (Stroup-Gardiner & Brown 2000). The higher the temperature differential the more likely segregation will occur. Mixes with consistent temperatures and continuous placement reduce segregation. Infrared cameras have been widely used in the US and Europe to identify locations with large temperature differentials and pavement distresses (Oba & Partl 2000). A method used to help reduce segregation within HMA is to include a material transfer vehicle (MTV) in the paving train. The use of an MTV provides the paving process a greater capacity and better connects the paver to the haul trucks. The MTV features large storage bins to allow extra time in between truck exchanges and also offers augur remixing systems. The remixing characteristics of the MTV allow it to deliver a more homogenous mix to the paver to improve mat quality (Zettler 2006). Research has shown that by including an MTV in the paving train the resulting pavement will have fewer areas with temperature differentials of greater than 10°C. The use of an MTV also led to reduced International Roughness Index (IRI) values in comparison to the sites where an MTV was not used (Harris et al. 2004). 2

BACKGROUND

Previous research has shown the effect of using an MTV on the uniformity of HMA mix. A study conducted at Auburn University in 2004 compared the roughness of roadways 397

constructed with and without the use of an MTV. Four sections constructed between 2001 and 2002 were evaluated for initial ride quality with and without the assistance of a MTV. For most sections, a segment of 3,000 ft was paved using one method, then the operation was switched and a second section of 3,000 ft was paved using the other method. The same crew, equipment, plant, and materials were used for both sections, which were done with and without a MTV. Areas in the placed roadway with temperature differentials of greater than 10°C were identified with an infrared camera and their approximate locations were marked. An automatic roadway analyzer (ARAN) was used to obtain IRI values for 4.6-m (15-ft) segments on the constructed sections before they were opened to traffic. The statistical comparisons of section IRI values showed a significant difference between the section using an MTV and the ones that didn’t. The use of an MTV reduced the average IRI value as well as reduced the number of 15 ft sections with high IRI values (Harris et al. 2004). The use of the MTV was also found to reduce pave stopping and starting, which in turn decreased IRI. A study conducted by the Colorado Department of Transportation (CDOT) was conducted to indentify factors that control segregation in constructed HMA pavements. Infrared cameras and guns were used to identify cold and hot spots in the placed mat. These spots were identified as locations where the cold spot was at least 25°F cooler than the surrounding area. Temperatures, paver types, roller types and other data was collected on projects to identify factors that can negatively or positively impact the density of the asphalt mat. A total of twenty CDOT construction sites were visited during the study. A result of the study was that the use of the MTV was found to be a positive influence on increasing density and limiting segregation (Gilbert 2004). Paving trains utilizing MTVs to remix and store the HMA material before it enters the paver were found to have ten times fewer cold spots when compared to projects not using an MTV. 3

PROJECT DESCRIPTION

The project monitored was Route 94 in Glastonbury, Connecticut and was constructed in September 2002. The placement of the 12.5 mm Superpave mix was monitored on five different days. The original pavement was milled by 2 inches and the overlay was compacted to the same thickness of 2 inches. No MTV was used on the first three days of observation, September 3rd–5th. A Roadtec SB-2500 MTV was used on construction observed on September 10th and 17th. The weather experienced during placement was sunny with ambient air temperature (AAT) of 65°F–90°F except for September 4th where the weather was overcast with intermittent light rain. Base pavement temperatures ranged from 75°F– 110°F over the five monitored days. HMA material was transported to the site from the plant in Newington, approximately 16 miles and 20 minutes from the site. Table 1 below displays the conditions experienced and the length of each of the studied sections. Traffic data from 2001–2007 for Route 94 was obtained from the Connecticut Department of Transportation (ConnDOT). The annual average daily traffic (AADT) for each of the studied sections is shown below in Table 2. A plot of the AADT for each section can be seen in Figure 1. The traffic on sections 1–3 is currently greater than 12,500 vehicles per day and

Table 1.

Section information for Route 94 at time of construction.

Section

Date constructed

Weather

AAT °F

MTV used

Length of section km

1 2 3 4 5

9/3/2002 9/4/2002 9/5/2002 9/10/2002 9/17/2002

Sunny Sprinkling Sunny Sunny Drizzling

80 85 75 90 65

No No No Yes Yes

0.33 0.18 0.80 0.22 0.36

398

Table 2.

AADT traffic data for Route 94 sections.

Section

2001

2002

2003

2004

2005

2006

2007

1 2 3 4 5

15100 15100 15100 6100 4300

15200 15200 15200 6100 3800

13100 13100 13100 6800 4300

13100 13100 13100 6800 4300

13000 13000 13000 6800 4300

12700 12700 12700 7200 4300

12700 12700 12700 7300 4300

Figure 1.

AADT traffic data for Route 94 sections by year from 2001–2007.

the traffic on these sections has been slowly declining since 2001. The traffic on section 4 has steadily climbed from 6,100 in 2001 to 7,200 in 2007. The AADT on section 5 of Route 94 has stayed nearly constant at 4,300 vehicles per day since 2001. 4

CONSTRUCTION

Construction of all Route 94 sections was completed with the same crew and equipment, neglecting the MTV itself. The contractor used a CAT AP1055B paver on all sections and additionally a Roadtec SB-2500 was used for MTV sections. Hypac C766C vibratory breakdown rollers and Ingersoll Rand vibratory roller were used for compaction. Representative thermal images from construction can be seen below in Figures 2 and 3. The image in Figure 2 was taken at a site where the MTV was not used in construction. The image in Figure 3 was taken at a site where the Roadtec MTV was used for placement of the mat. Sections constructed without the use of an MTV typically contained more cold spots than sections constructed with the MTV. Sections without the assistance of an MTV also contained a greater amount of segregated areas when examined visually. Figure 2 depicts a typical thermal image of a mat placed without a MTV. A temperature differential of more than 30°C can be seen between the center of the cold spot and the hottest location on the mat. Locations where the paver had to stop for a truck change contained the majority of the cold spots observed for sections not using the MTV. Rarely cold spots were observed in the middle of a paving pull. Sections using an MTV to remix pavement material displayed far fewer cold spots when the mat was examined with a thermal imaging camera. Figure 3 399

Figure 2.

Image of cold spot on September 4th, taken at section 2 (chainage 1.66 km) (no MTV).

Figure 3.

Image of mat on September 17th, taken at section 5 (chainage 10.36 km) (MTV used).

contains a representative image of the uniform map produced by the paver and MTV. The MTV virtually eliminated all of the cold spots normally observed and the remixing action of the MTV produced a nearly homogeneous temperature profile in the placed mat. 5

DATA COLLECTION

Performance data from all five sections was collected before, during and after the construction in 2002. Data collection involved several processes. Temperature differentials and cold spot locations were recorded at the time of construction using a ThermaCAM PM575 thermal imaging camera. During paving operations the infrared camera was used to observe the mat material behind the paver. For each monitored site, cold spots or areas and their 400

respective higher-temperature counterparts were located with the infrared camera and geo-referenced with a portable GPS unit. Additionally, the differences between the high and low temperatures were recorded. Images were then processed and analyzed using ThermaCAM Researcher 2000 software on a laboratory computer. GPS coordinates were correlated to a specific chainage for the given section. An automatic road analyzer (ARAN) from ConnDOT was used to obtain IRI values for both the left and right wheelpaths. Runs were completed annually before and after construction at speeds between 30 and 70 mph. The IRI data was collected at 10 m intervals along all sections. In addition to IRI data, the ARAN also collected pavement pictures. The pictures were taken at smaller intervals and then merged to determine representative data for 10 m sections. Pavement pictures were next analyzed by WiseCrax® (Roadware) software to determine the amount (length), type (longitudinal vs. transverse) and severity (width) of cracking in the pavement. 6

RESULTS

The five different sections of Route 94 were each analyzed in terms of roughness and surface distress. The roughness of the sections was evaluated using the IRI of the roadway. The surface distress of the sections was evaluated by examining the amount of cracking in the roadway. The analysis of IRI and cracking data involved segmenting the sections into 10 m intervals of the roadway. Both longitudinal and transverse cracking were examined for the study. 6.1 Effect of MTV on IRI The average IRI for each section was calculated for each year from 2001 to 2007 and compared against each other. Figure 4 displays the plot of the average IRI and 95% confidence interval for the mean for each section in every year. The average IRI for all sections decreased sharply from 2002 to 2003 due to the new overlay constructed on the roadway in September 2002. The section employing the MTV (sections 4 & 5) displayed lower roughness immediately following construction compared to the other sections. The IRI values of the MTV sections stayed relatively constant from 2003 to 2007 while the non-MTV sections increased slightly over the time period. The confidence intervals for the non-MTV sections are significantly larger than those of the MTV sections, suggesting a greater variability in roughness for the sections not employing an MTV.

Figure 4.

Plot of average and 95% confidence interval IRI values for each section by year.

401

Figure 5.

IRI standard deviations and 95% confidence intervals for section 5 (MTV used).

Figure 6.

IRI standard deviations and 95% confidence intervals for section 1 (no MTV).

A test for equal variances was performed for each of the studied sections using Bartlett and Levene’s test. The standard deviation of the IRI data for each section by year was examined for extreme variability. Standard deviations for the years before construction were higher than the deviations found after construction. Sections using an MTV in construction were found to have equal variances in all of the years studied. These sections had small standard deviation when compared to the mean IRI’s (small Coefficients of Variations). The plot of the standard deviations and their respective 95% confidence intervals of section 5 can be found in Figure 5. It is apparent that overlay construction was done in 2002 after data collection and since then IRI stayed virtually constant. Sections without the aid of an MTV displayed larger IRI standard deviations and more variability from year to year. These sections had IRI standard deviations that were often greater than 1.0 m per 10 m intervals and displayed large 95% confidence intervals. Section 1 was found to be representative of the sections not employing an MTV. The plot of the IRI standard deviations and their respective 95% confidence intervals versus the year can be found in Figure 6. 402

The use of the MTV in the studied sections resulted in lower average IRI values when compared to sections without the MTV. The IRI of MTV sections appeared to hold constant for five years following construction while the sections not using the MTV increased in IRI from 2003 to 2007. The IRI for MTV sections had far less variability than section not using the MTV when compared to their respective mean IRI values. The lack of variability suggests that the MTV sections were more uniform and homogeneous than their non-MTV counterparts. The use of the MTV resulted in a pavement surface that had lower initial surface roughness and maintained that initial roughness longer after construction. On the other hand, section 5 received far less traffic as compared to section 1 (see Table 1 and Figure 1). One can argue that this limited roughness development in section 5 and contributed to roughness increase in section 1. Direct impact of the traffic on the IRI development will be investigated in the further analysis on the sections with comparable traffic levels. 6.2 Effect of MTV on transverse cracking The amount of transverse cracking in each section was evaluated before and after the overlay construction. The plot of the average amount of transverse cracking for each section by year is shown in Figure 7. Sections 4 and 5 that used the MTV both had very high amounts of transverse cracking before construction in late 2002. All sections displayed zero cracking in 2003, immediately after the construction of the overlay. MTV sections 4 and 5 displayed minimal transverse cracking from 2003 to 2006, while the remaining sections without the MTV showed increased cracking during this period. All sections displayed a significant increase in the transverse cracking between 2006 and 2007 due to sever winter conditions. Sections using the MTV also have much smaller confidence intervals when compared to the non-MTV sections. All this observations imply that the use of an MTV reduces the amount and variability of transverse cracking in the pavement. A plot of the transverse cracking length per 10 m intervals versus the chainage/location for section 5 can be seen in Figure 8. The section is representative of the other sections where the MTV was used. The plot shows that the overlay construction reduced the cracking per interval in section 5 from 6 m to nearly zero from 2001 to 2003. The transverse cracking has only increased to a length of 3 m per interval over the service life of nearly five years. The transverse cracking observed in 2007 was still less than the amount that was in the roadway in 2001 before construction. Sections that did not use an MTV for overlay construction

Figure 7. Average and 95% confidence interval transverse cracking length per 10 m increments for each section by year.

403

Figure 8.

Plot of transverse cracking length per 10 m increments for section 5 (MTV used) by year.

Figure 9.

Plot of transverse cracking length per 10 m increments for section 1 (no MTV) by year.

currently have surpassed the amount of cracking present before construction. Section 1 is a representative interval for all the sections not using the MTV. The plot of the transverse cracking length per interval versus the chainage/location for section 1 can be seen in Figure 9. The plot shows that the section had very minimal transverse cracking before construction. Immediately after construction the transverse cracking is reduced to zero, but the 2007 measurement shows that the transverse cracking is now greater than in 2001. The section had a preconstruction cracking length of only 0.75 m but five years following its overlay construction the cracking is nearly an average of 4 m per interval. The use of the MTV on the studied sections appears to reduce transverse cracking in the pavement surface when compared to sections not employing the MTV. Sections using the MTV had more severe cracking prior to construction and now have far less transverse cracking five years following the overlay construction. The overlay in late 2002 reduced the cracking in all sections to zero but the sections with the MTV remained at a low level for another four years. All of the sections showed an increase in cracking from 2006 to 2007. 404

Figure 10. Average and 95% confidence interval longitudinal cracking length per 10 m increments for each section by year.

The variability of the cracking amount through the sections was reduced with the use of the MTV during construction. 6.3 Effect of MTV on longitudinal cracking The average length of longitudinal cracking per 10 m intervals for each section was evaluated before and after overlay construction in late 2002. The plot of the longitudinal cracking for each section by year is shown below in Figure 10. Sections 4 & 5, which used the MTV, both had very large amounts of longitudinal cracking before construction (not shown in Figure 10). The longitudinal cracking for all sections was reduced to zero in 2003 due to the overlay construction. From 2003 to 2007 all of the sections displayed a steady increase in longitudinal cracking. All of the sections appear to have similar amounts of longitudinal cracking for each year. All of the sections also appear to experience a jump in longitudinal cracking from 2006 to 2007. One of the potential causes of this increase is the presence of some structural deficiency and/or fatigue damage in the pavement. Possibly one of base or subgrade layers is experiencing fatigue which is causing the increased longitudinal cracking. From these observations it appears that the MTV has rather minor effect on the longitudinal cracking of the five studied sections. 7

CONCLUSIONS

The following conclusions can be drawn from this preliminary analysis: − The use of an MTV in the paving train significantly improves initial roadway surface roughness and reduced the variability in surface roughness along the roadway. − The use of the MTV increased the period for which roadway surfaces maintained their initial post-construction IRI. − The addition of the MTV to the paving train reduced the amount of transverse cracking in the mat and reduced the variability of cracking in the roadway surface. − Longitudinal cracking seems to be independent from the use of the MTV for the sections analyzed in this study. The above conclusions can most likely be attributed to the reduction in thermal segregation during the construction with the use of the MTV. The increased capacity and remixing characteristic of the MTV produce material that is more homogeneous and uniform. 405

The lack of this homogeneity can result in roadway variability that is shown in the non-MTV sections above. The more widespread use of the MTV technology can result in pavements that show less roughness and distress for more of their service life. ACKNOWLEDGEMENTS The authors would like to thank Edgardo Block and Bradley Overturf from ConnDOT for providing the ARAN data. The results and opinions presented are those of the authors and do not necessarily reflect those of ConnDOT. The authors also acknowledge James Mahoney and Scott Zinke from the Connecticut Advanced Pavement Laboratory (CAPLab) for providing the construction data and thermal images. REFERENCES Gilbert, K. 2004. Thermal Segregation: Final Report. Colorado Department of Transportation. Research Branch. Harris, J.K., Parker, F. & Stroup-Gardiner, M. 2004. Effect of Material Transfer Devices on Flexible Pavement Smoothness. Transportation Research Record Vol. 1900: 50–55. Henault, J.W. & Larsen, D.A. 2006. Thermal Imaging of Hot-Mix Asphalt Paving Projects in Connecticut. Transportation Research Record Vol. 1946: 130–138. Mahoney, J., Zinke, S.A., Stephens, J.E., Myers, L.A. & DaDalt, J.A. 2003. Application of Infrared Ther-mographic Imaging to Bituminous Concrete Pavements—Final Report. Report 2229-F-03-7. Connecticut Advanced Pavement Laboratory, Connecticut Transportation Institute, Storrs, Conn. Oba, K. & Partl, M.N. 2000. Non-Destructive Detection of Distress in Asphalt Pavements and Bridge Deck Surfacings Using IR-Thermography. International Journal of Road Materials and Pavement Design Vol. 1: 407–418. Roadware, http://www.roadware.com/software/wisecrax_nt/, accessed on 12/16/08. Stroup-Gardiner, M. & Brown, E.R. 2000. NCHRP Report 441: Segregation in Hot-Mix Asphalt Pavements. Transportation Research Board, National Research Council, Washington, D.C. Zettler, R. 2006. A More Efficient Material Transfer: Material Transfer Devices and Vehicles Keep the Mix Flowing. Associated Construction Publications (19).

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In-situ measurement techniques and developments

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Development of the UK highways agency traffic speed deflectometer B. Ferne, P. Langdale & N. Round Transport Research Laboratory, Crowthorne, UK

R. Fairclough Highways Agency, UK

ABSTRACT: One of the headline objectives of the UK Highways Agency (HA) is to reduce congestion and improve road safety whilst undertaking highway maintenance. To this end the HA has invested significant resources in appropriate technology to collect road condition and structural data at traffic speed. Surface condition surveys of the English strategic road network are already carried out using survey vehicles operating up to 100 km/h, however currently there is no traffic speed facility for measuring the structural condition of the road network. Deflection measurements remain the most reliable non-destructive method for determining the structural condition of flexible pavements and therefore in 2005 the HA instructed TRL to procure a prototype Danish Traffic Speed Deflectometer (TSD), on their behalf, and tasked them with developing it into a survey tool capable of providing an estimate of structural condition. This paper presents the results of the TRL project to date and concludes that, with further development, the HA TSD will be capable of measuring structural condition at traffic speed. 1

INTRODUCTION

In recent years, the volume of traffic carried by the UK Motorway and Trunk Road network has increased significantly. The Highways Agency (HA) Business Plan listed headline objectives to reduce congestion and improve road safety for both road users and persons undertaking highway maintenance. In order for these aims to be successfully fulfilled, it was necessary that the work on active highways be kept to a minimum. Hence there existed a need to facilitate the collection of condition and structural data for the strategic network at traffic-speed wherever possible. Deflection measurements currently remain the only reliable non-destructive method for determining the structural strength of flexible and flexible-composite pavements. Although the intro-duction of the long-life pavement (LLP) concept in the UK has changed the way in which deflection results are interpreted, deflection still plays a fundamental role in classifying pavements as long-life, determinate, or potentially upgradeable to long-life, as well as in determining any structural strengthening that is required. In the UK, pavement deflection measurements are currently undertaken by two devices; the Deflectograph and the Falling Weight Deflectometer (FWD). Both these devices provide a stationary frame of reference relative to which the pavement deflections are measured. To-date, this approach has been the only one capable of achieving the required resolution and accuracy. However, they employ slow-moving or static measurement techniques that are expensive to operate and can be hazardous for operators and disruptive for road users. These limitations resulted in suspension of the Deflectograph for routine network-level assessment in 2000. Nevertheless, due to the importance of deflection measurement on treatment design, the Deflectograph together with the FWD, continue to be used for scheme, or project-level, pavement assessment. In 2005 TRL, on behalf of the HA, identified the High Speed Deflectograph originally developed in Denmark by Greenwood Engineering A/S (Greenwood, 2008) as being capable 409

of performing deflection surveys at traffic speed. TRL were then commissioned to procure and develop the High Speed Deflectograph (subsequently renamed as the Traffic Speed Deflectometer (TSD)) into a survey tool capable of providing routine estimates of structural condition of the UK strategic road network. This report describes the initial commissioning of the equipment and the acceptance testing. It also describes TSD testing conducted under controlled conditions and modifications made to the equipment and its operation in response to the results of this testing. Finally, it details the development of the TSD into a fully functioning research tool and investigation into its applicability for routine surveys of the strategic road network. 2

THE TSD AND ITS OPERATION

The TSD contains a complex array of instruments and recording equipment within an insulated steel container which is mounted on a single rear axle trailer assembly having a rear axle load of approximately 10 tonnes. The layout of the primary instrumentation is shown schematically in Figure 1. A view of the container interior is given in Figure 2. The basic functionality is designed to measure the pavement response under the rear wheels, in the nearside wheel-path, by using four Polytec OFV 503 Doppler vibrometer heads positioned on a rigid steel beam. The instruments measure velocity along the axis of the laser by exploiting the Doppler effect. All four laser sensors are connected to their own Polytec LSV6200 Velocimeter Controller units that process the signal and extract the velocity measurement from the frequency content of the reflected laser signal. When the TSD was procured the three measurement lasers were located at the rear of the beam and measured pavement surface velocity at 100 mm, 200 mm and 300 mm in front of the rear wheel assembly. This configuration is shown in Figure 3. In early 2008 the laser mounted in the 200 mm position was moved to a position 750 mm in front of the rear axle in order to better investigate the structural contribution from the lower pavement layers. In this paper the outputs from the lasers, in their initial positions, are referred to as P100, P200 and P300, respectively, or generically as Px. The fourth Doppler laser is located 3 m in front of the rear axle and measures the pavement response (Pref) at a point that is designed to be relatively unaffected by the load applied by the trailer or tractor unit. Separate measurements with an accelerometer mounted in the pavement (Ferne et al, 2009) have shown that the deflection velocity 3 m in front of the load is typically less than 5% of the peak velocity. If the lasers were mounted exactly vertically then they would measure the required vertical pavement velocity superimposed on the varying positive and negative velocities generated by the suspension movement. However, for ideal and accurate operation the Doppler lasers require a relatively constant velocity input. The problem is solved by providing a bias to the velocity signal

Reference laser: Pref

3 Measurement lasers: Px

Figure 1.

Cutaway of the HA TSD. Inset: the TSD surveying.

410

Figure 2.

Inside of HA TSD container showing measurement beam and computer unit.

Figure 3.

Original positions of the four Doppler lasers relative to the deflection bowl.

by mounting the lasers at an angle of approximately 2ο from the vertical. This gives an approximately constant velocity input, as a component of the horizontal vehicle velocity is measured, whilst having little effect on the magnitude of the component of vertical velocity measured. In this configuration the lasers measure velocities from three sources; • the horizontal vehicle velocity; • the vertical and horizontal vehicle suspension velocity; and • the vertical pavement deflection velocity. Due to its location, mid-way between the loaded trailer axle and the rear axle of the tractor unit, laser Pref is expected to measure very little vertical pavement deflection velocity and its response can therefore be used to remove the unwanted signals from the three measurement lasers. If the lasers were all mounted at exactly the same angle then this could simply be done by subtracting Pref from the Px values. However, this is not the case so a correction must be made to take into account the small difference between the angles of the measurement lasers, Px, and the reference, Pref. A further correction is then made to take into account the fact that Pref is at the opposite end of the beam to the measurement lasers. This correction is provided by the pitch gyro which is mounted on the measurement beam. The need to derive a correction for the difference between the angles of the lasers provides the basis for the TSD calibration process recommended by the manufacturer. This process 411

vh Slope = Vv/Vh

vv

Slope

Figure 4.

Calculation of the slope of the deflection bowl.

involves removing the detachable 5 tonne load and then testing a length of road with an extremely stiff pavement. TRL selected a length of Continuous Reinforced Concrete Pavement in a tunnel for this purpose. It is assumed that, under these conditions, the actual deflection slope will be negligible and ‘calibration factors’, can then be calculated for each of the measurement lasers such that the deflection slope recorded is zero. This calibration process has some obvious disadvantages and therefore a more quantitative approach is being developed by TRL (Ferne et al, 2009). Following correction, the measured vertical deflection velocity (vv) for each measurement laser is divided by the instantaneous survey speed (vh) to provide the deflection slope (i.e. gradient) of the point on the deflection bowl for which the Doppler laser is measuring, as shown in Figure 4. 3

ACCEPTANCE TESTING

As part of the acceptance testing, preliminary testing in Denmark was carried out at speeds of 40, 60 and 80 km/h on a relatively strong three kilometre length of motorway in Odense and then at approximately 60 km/h on weaker country roads near Kerteminde, north of Odense. These results are shown in Figure 5, where a 100 point moving average (approximately equivalent to a length of 5 to 10 m) has been used to smooth out some of the noise in the data. The results confirmed that the TSD was able to clearly distinguish between structurally weak and strong pavements. Following the testing in Denmark, the TSD was shipped to the UK in October 2005 for further acceptance tests on the test roads at TRL. These were completed in October/November 2005. The purpose of these tests was to: • • • • •

validate the location referencing systems (odometer & photocell); validate the distance measurement; review the effect of testing speed on the deflection slope; establish the repeatability of runs performed at the same speed and temperature; and confirm the results collected in Denmark on structurally weak and strong pavements.

To validate the location referencing and distance measurement, a series of tests were conducted over a measured 550 m length. The length was marked with reflective marker posts at each end and the TSD was driven between the two posts over a series of six repeat runs. The outputs from the odometer wheel and event files showed that the odometer wheel consistently read to within ±1 m, as did the photocell trigger. To review the effect of testing speed, the TSD runs on the TRL track were initially carried out over a range of speeds. The results showed that as the speed was increased a slightly lower 412

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TSD measurements on relatively weak and strong pavements in Denmark.

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value of deflection slope was recorded. This being the case, the testing speeds used during further tests were strictly controlled to enable repeatable results to be obtained. Figure 6 shows a sample of the results from a 440 m length of the TRL track, having mainly a flexiblecomposite construction but including a 50 m length of jointed concrete. The six runs, in the figure, were carried out at a nominal speed of 70 km/h, and as can be seen, the data showed reasonable short-term repeatability, with a relatively low standard deviation despite the relatively wide range of deflection slopes measured, i.e. changing by a factor of over seven. To confirm whether the TSD could differentiate between strong and weak road pavements a series of comparative tests were carried between the TSD, the UK Deflectograph and the FWD on three, 45 m test sections, having a known construction and deflection response. The UK Deflectograph is a loaded lorry which measures the vertical deflection of a road pavement relative to a reference frame at 3.5 m intervals at a survey speed of 2.5 km/h (UK Highways Agency, 2008). The results of these tests are presented in Figure 7 and show that the TSD was equally as good as the other deflection measuring devices at differentiating between the structural strengths of the three sections. After the completion of the tests both in Denmark and at TRL, the HA TSD was deemed to have passed the acceptance criteria and the HA took possession of the TSD.

4

DEVELOPMENT OF A FULLY FUNCTIONAL RESEARCH TOOL

Following the acceptance testing, the first task in developing the equipment into a fully-functional research tool was to identify and assess the conditions which would be likely to influence the operation of the TSD on the HA road network. It was anticipated that these factors would include at a minimum: testing speed, road temperature, type of road base construction and type of road surfacing. In order to manage the number of variables, two local circular, routes, A and B, were established close to TRL such that the effect of these variables on the performance of the TSD could be assessed. Route A was 46 kms long and contained lengths of both flexible composite/semi-rigid pavements and pavement quality jointed concrete pavements. Route B was 93 km long and contained a substantial amount of fully flexible pavements. The road surfacing on the two local loops included surface dressings, thin surfacings, hot rolled asphalt wearing course and jointed-concrete. 4.1 Effect of testing speed Early surveys at nominal testing speeds of 60, 70 and 80 km/h showed that although, in general, the TSD gave comparable results at these speeds the rate at which acceptable data was collected by the lasers, termed the data rate, significantly decreased at higher speeds contributing to excessive noise in the processed results. This can be seen by comparing Figures 8 and 9. This decrease in data rate continued to give unsatisfactory results during the early months of 2007 and after discussions with Greenwood Engineering A/S, the manufacturers, they recommended that the TSD be returned to Denmark for modifications. These modifications included mounting the supports of the steel measurement beam, on which the lasers are fitted, immediately onto the chassis rather than onto the floor of the container. The modifications are shown in Figure 10. The modifications made by Greenwood allowed the TSD to be operated satisfactorily at speeds up to 80 km/h. The relations between deflection slope and testing speed for three types of roadbase construction, recorded since these modifications, are shown in Figure 11. 4.2 Type of road surfacing By surveying on various types of road surfacing and in various conditions, it has been established that the optics perform better on lighter surfaces, e.g. jointed-concrete, and least well on new bituminous surfaces. This can be seen in Figure 12 where the data rate of the four Doppler lasers is shown for one particular survey along a 13 km length of Route A. The figure clearly shows 414

Figure 8.

TSD slope profile over 6 km of Route A at 60 km/h (initial TSD configuration).

Figure 9.

TSD slope profile over 6 km of Route A at 80 km/h (initial TSD configuration).

Figure 10.

Diagram of modified TSD showing beam mountings welded directly to trailer chassis.

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Effect of the road surfacing type on the data rate from each of the lasers.

changes in data rate over lengths of the jointed-concrete and a length of freshly laid thin surfacing in comparison to the ‘old’ bituminous surface. Similarly, surveys on damp roads yield a lower data rate than those on dry surfaces. It is likely that this phenomenon is due to the optical properties of the different surfaces or surface condition and, although it is not fully understood, it is important to identify such features as they help to define the capabilities of the technology, and such information will probably be employed in the quality assurance of TSD data in the future. 4.3 Effect of temperature Since repeatability testing on the local routes began in October 2006 it has been apparent that temperature has an effect on the value of deflection slope recorded by the TSD, as might be expected for many pavement types. However, it was not entirely clear whether the temperature was affecting the response of the equipment or the road or both. The testing first identified that at very low temperatures of the measurement beam, the data rate of the lasers decreased significantly, resulting in a commensurate drop in the value of deflection slope. It is believed that this effect was caused by the measurement beam acting as a ‘heat sink’ which was preventing the lasers reaching their correct operating temperature. Subsequent to this, repeatability testing was restricted to data collected when the temperature of the measurement beam was greater than 15οC. Despite this, the longer term variation in repeat testing on the local routes, was still greater than had been anticipated. A more thorough investigation showed that as the lasers heated 416

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up they were causing temperature gradients, of up to 4οC, within the measurement beam itself. These temperature gradients were sufficient to cause the recorded differences in deflection slope by distorting the measurement beam. Since March 2008 the TSD has been fitted with two fans which have virtually eliminated the development of temperature gradients within the measurement beam. At the same time the laser, originally mounted in the 200 mm position, was moved to 750 mm in front of the rear axle. Local route testing is continuing to establish how the absolute temperature of the beam and the temperature of the road pavement affect the value of deflection slope recorded. 4.4 Repeatability testing Repeatability testing since the fitting of the fans has showed the results to be considerably more consistent. Figure 13 shows a sample of the results since the fans were fitted. In the figure the deflection slope (P100) from six tests, over a two month period, for 5 km of flexible composite road on Route A are shown. The standard deviation of deflection slope (based on the 10 m mean values) recorded by P100, P300 and P750 were 0.040, 0.045 and 0.053 mm/m respectively. It is anticipated that the repeatability can be further improved as the effect of temperature on the measurement beam and the road pavement are better understood. 5

RELATION WITH OTHER DEFLECTION DEVICES

In order that the TSD can be used as an effective network survey assessment tool it is important that the data it provides is not only repeatable but also that it can be shown to relate to the structural performance of the pavement at a prescribed level of confidence. In the long term this will be done by directly relating TSD data to the performance of the motorway and trunk road network, however, in the short term it is hoped that this can be achieved by developing a simple relation between deflection slope, as measured by the TSD, and deflection, as measured by the UK Deflectograph. If this can be achieved then the existing UK relation between Deflectograph deflection and residual life (UK Highways Agency, 2001) can be used to estimate the structural condition of the road pavement. There are a number of possible problems with this approach as it assumes that there is a single relation between Deflectograph deflection and the TSD slope for flexible pavements. This is obviously unlikely to be entirely true when the different types, thickness and condition of a range of flexible pavements are considered. However, the potential variability in the results can be reduced by determining relations for each construction type. The level of subclassification will depend on the desired level of consistency for network level use. In order to determine these relations it is desirable to carry out the TSD and Deflectograph surveys at approximately the same time and hence limit any substantial real change in the structural strength of the pavement due to environmental conditions. Figure 14 illustrates 417

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one of these comparisons for a 7 km length of a local road and it shows the good correlation between the two measures of structural strength. 6

CONCLUSIONS

Traffic-speed deflection surveys are an important extension of the current traffic-speed surface condition surveys that are routinely carried out on the UK trunk road network. Through testing in both Denmark and the UK, the TSD has been shown to be able distinguish between weak and strong pavements and the promising relationship being developed between TSD and Deflectograph suggests that the TSD will be capable of measuring structural condition at traffic speed. Work done by TRL has identified a number of challenges to achieving this, notably in understanding how speed and temperature effects are to be corrected for. However, recent success in controlling the variation in results due to temperature gradients within the measurement beam is an example of how these challenges are being met. ACKNOWLEDGEMENTS © Copyright Transport Research Laboratory 2008. This paper has been produced by TRL Limited as part of a contract placed by the Highways Agency. Any views expressed in it are not necessarily those of the Agency. REFERENCES Ferne, B.W., Langdale, P., Round, N. and Fairclough, R. 2009. Development of a calibration procedure for the UK Highways Agency Traffic Speed Deflectometer. TRB, 2009. Greenwood Engineering A/S 2008. Traffic Speed Deflectometer. www.greenwood.dk/TSD/default.asp. Accessed July 31, 2008. Round, N., Langdale, P., Jones, C., Nell, S. and Isola, R. 2008. Developing the HA Traffic Speed Deflectometer—Final Report. Published Project Report PPR332. Transport Research Laboratory (TRL), Wokingham, Berkshire, 2008. UK Highways Agency 2008. Data for pavement assessment. Design Manual for Roads and Bridges (7.3.2) HD 29/08. The Stationery Office, Norwich, UK. UK Highways Agency 2001. Processing of Deflection Data. HAPMS Document 104 Version 01.05. HAPMSII Project Office, The Highways Agency.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Implementation of a network-level falling weight deflectometer survey of Virginia’s interstate system B.K. Diefenderfer Virginia Transportation Research Council, Charlottesville, Virginia, USA

T. Chowdhury & R.A. Shekharan Virginia Department of Transportation, Richmond, Virginia, USA

ABSTRACT: The Virginia Department of Transportation currently uses the results of automated video distress surveys to develop a pavement maintenance budget based on a needs assessment. However, these data consist only of quantities of distress that were visually observable at the pavement surface; no information regarding the actual structural capacity of the pavement system was available. Therefore, it is likely that maintenance activities assigned to certain locations are not the optimal treatment because of conditions unseen at the surface. This study presents the results of a network-level FWD survey of Virginia’s interstate system and describes an implementation process where the data are used in an updated decision tree structure. The results of this study can be used by pavement design and management engineers to ensure that maintenance funding is optimally spent and to develop condition forecasting tools to assist with future funding allocations based on the structural capacity of the pavement. 1

INTRODUCTION

The Virginia Department of Transportation (VDOT) uses the results of automated video distress surveys to assist in developing maintenance priorities to manage the pavement on Virginia’s interstate and primary roadways. Totaling nearly 43,200 lane-km (27,000 lane-miles), these roadways consist of flexible, rigid, and composite (flexible over rigid) pavements. The video-based surface distress data consist of quantities of distress that are visually observable at the pavement surface; however, no information regarding the structural capacity of the pavement system on a network level is currently available. The distress quantities are then transformed into a condition index. Along with the condition index, individual distress quantities and severities are used to determine typical maintenance treatments and associated costs are calculated. It is from this process that an unconstrained performance-based maintenance budget is developed. Previous research conducted at the Virginia Transportation Research Council (VTRC) developed a protocol to collect pavement structural capacity data using the falling weight deflectometer (FWD) on portions of Virginia’s interstate system (Alam et al. 2007; Galal et al. 2007). The FWD has also been used by many U.S. state departments of transportation, including those of New Jersey, Kansas, Texas, and Indiana, to develop structural data for their pavement networks (Zaghloul et al. 1998; Hossain et al. 2000; Noureldin et al. 2003; Zhang et al. 2003). Such data typically include the deflection, subgrade resilient modulus, effective structural number, deflection basin area, individual layer moduli, and overall pavement moduli. 2

METHODOLOGY

2.1 Data collection Deflection testing of Virginia’s interstate system was conducted in two phases in accordance with a methodology developed by Alam et al. (2007) and Galal et al. (2007). Testing was 419

performed using a Dynatest model 8000 FWD in the travel (right-hand) lane of the roadway in both directions. The FWD load plate was located within the right wheel path during testing. The FWD was equipped with nine sensors at radial distances of 0, 203, 305, 457, 610, 914, 1219, 1524, and 1829 mm (0, 8, 12, 18, 24, 36, 48, 60, and 72 in.) from the center of a load plate. Testing in the first phase was conducted at 160-m (0.1-mile) intervals and at four load levels, 26.69, 40.03, 53.38, and 71.17 kN (6000, 9000, 12000, and 16000 lbf). At each load level, two deflection basins were recorded. Testing in the second phase was conducted at 320-m (0.2-mile) intervals and at three load levels 40.03, 53.38, and 71.17 kN (9000, 12000, and 16000 lbf). At each load level, two deflection basins were recorded. A total of slightly more than 12,300 data points were collected. In addition to the measured deflection (Sensors 1 through 9), the following data were reported or calculated from VDOT’s interstate network FWD testing for all pavement types: plate load, plate pressure, air and surface temperature, test date, and time. The previous day’s average air temperature (average of high and low) was obtained from Weather Underground (www.wunderground.com) for each test date from a nearby weather station. These data were used to calculate a temperature-corrected deflection under the load plate (D0) for flexible pavement sections. In addition, the resilient modulus, pavement modulus, and effective structural number were calculated for flexible pavements. The deflection basin area and the static k-value were calculated for composite (flexible over rigid) and rigid pavement sections. As described in more detail in the following section, the pavement network was subdivided into structurally homogeneous sections prior to deflection testing. During the testing, deflection data from each section were collected either during one day or over several days depending on the length of the section, the allowable work time, the weather, and other local conditions. The date and time were reported in the raw data along with the infrared pavement temperature and ambient temperature at the time of testing. 2.2 Data analysis The data analysis began by identifying continuous stretches of pavement having similar surface materials and structural cross sections such that they would be expected to act homogeneously with respect to traffic loading. Grouping structurally similar pavement sections was performed for ease of data analysis. A typical pavement cross section may consist of many varied layers, but for the purpose of analysis in this study, the cross section was simplified and considered as an idealized three-layer system. For flexible and rigid pavements, the threelayer system consisted of bound layer(s), aggregate layer(s), and subgrade. For composite pavements, the three-layer system consisted of flexible pavement layer(s), rigid pavement layer(s), and subgrade. The pavement structure information (layer type and thickness) was obtained from VDOT’s Highway Traffic Record Information System (HTRIS) database. During the data analysis process, the pavement sections were identified in accordance with nomenclature standards previously established by VDOT’s Maintenance Division as one of the following types: BIT: flexible pavement (bituminous); BOJ: a composite with flexible pavement over jointed concrete pavement; BOC: a composite with flexible pavement over continuously reinforced concrete pavement; JPC: jointed plain concrete pavement; JRC: jointed reinforced concrete pavement; or CRC: continuously reinforced concrete pavement. In general, adjacent test locations that were determined to be structurally similar (thickness and/or surface layer type) were grouped to form larger homogeneous sections to make the data analysis more computationally efficient. This grouping was performed where the bound layer thickness of adjacent sections differed by less than approximately 51 mm (2.0 in.). Any identified homogeneous section less than 800-m (0.5-mile) in length was grouped with adjacent sections until the total length of the combined homogeneous section was greater than 800-m (0.5-miles). Where multiple sections were joined to create a larger homogeneous section, the thickness of each layer of the larger homogeneous section was calculated based on an average layer thickness weighted by the length of the smaller portions. The thickness of the bottommost layer (subgrade) is given by an analysis of the data to identify the depth 420

to the hard-bottom or rigid layer; in most cases, this ranged from approximately 254 cm (100 in.) to more than 760 cm (300 in.). In some cases, the thickness and layer information obtained from HTRIS did not pass the “test of reasonableness” or appeared to be missing some portions of data. In these cases, the three-layer system thickness for the homogeneous section in question was estimated based on average data for adjacent homogeneous sections that appeared to be of similar structure. FWD data were analyzed using ModTag, Version 4.1.4 (VDOT 2007). Flexible pavements were analyzed by evaluating the subgrade resilient modulus (MR) and the effective structural number (SNeff). Rigid and composite pavements were analyzed by evaluating the deflection at the center of the load plate and the deflection basin area. These criteria were selected based on the collective input of a task group comprised of members of VDOT’s pavement design community. The analyses were conducted in accordance with the 1993 American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures (AASHTO 1993) and the 1998 Supplement to the AASHTO Guide for Design of Pavement Structures: Part II, Rigid Pavement Design and Rigid Pavement Joint Design (AASHTO 1998). Details of the equations used are presented elsewhere (Diefenderfer 2008). 3

DEFLECTION TESTING RESULTS

3.1 Flexible pavements Figure 1 shows the cumulative distribution of the effective structural number for all flexible pavements tested in this study. The effective structural number offers an empirical means for determining the structural capacity of a flexible pavement structure. A higher structural number indicates a higher capacity for carrying traffic. The computed value may be compared to a required structural number (required for carrying future traffic) using the protocols given in the AASHTO pavement design guide (AASHTO 1993) and following VDOT guidelines for using the AASHTO pavement design guide (VDOT, 2000). Figure 1 indicates that the 50th percentile for the effective structural number is approximately 6.5. Thus, half the locations tested had an effective structural number less than 6.5, and half greater. Figure 2 shows the cumulative distribution of the resilient modulus for all flexible pavements tested in this study. The subgrade resilient modulus offers a means for evaluating the strength of the subgrade. A greater resilient modulus value indicates a stronger subgrade.

Figure 1.

Cumulative distribution of effective structural number for all flexible pavements.

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Figure 2. Cumulative distribution of subgrade resilient modulus for all flexible pavements (1 psi = 6.89 kPa)

Figure 3. Cumulative distributions of deflection under the load plate for all composite and rigid pavements (at 40.03 kN, 9000 lbf load level). BOC = a composite with flexible pavement over continuously reinforced concrete pavement; BOJ = a composite with flexible pavement over jointed concrete pavement; CRC = continuously reinforced concrete pavement; JPC = jointed plain concrete pavement; JRC = jointed reinforced concrete pavement (1 mil = 0.0254 mm).

Similarly, Figure 2 indicates that the 50th percentile of the subgrade resilient modulus is approximately 89.7 MPa (13,000 psi). 3.2 Rigid/Composite pavements Figure 3 shows the cumulative distributions of the measured deflection under the load plate for all rigid and composite pavements at the 40.03 kN (9000 lbf) load level. The deflection under the load plate is taken directly from the raw FWD data and is generally indicative of the stiffness of the pavement foundation. Thus, a greater deflection indicates a weaker pavement foundation. The cumulative distributions of the deflection under the load plate are similar for composite (BOC and BOJ) and rigid (CRC, JPC, and JRC) pavement types (see Figure 3). 422

Figure 4. Cumulative distributions of deflection basin area for all composite and rigid pavements. BOC = a composite with flexible pavement over continuously reinforced concrete pavement; BOJ = a composite with flexible pavement over jointed concrete pavement; CRC = continuously reinforced concrete pavement; JPC = jointed plain concrete pavement; JRC = jointed reinforced concrete pavement (1 in. = 25.4 mm).

Figure 4 presents the cumulative distributions of the deflection basin area for rigid and composite pavements, as calculated in accordance with the 1993 American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures (AASHTO 1993) and the 1998 Supplement to the AASHTO Guide for Design of Pavement Structures. Part II, Rigid Pavement Design and Rigid Pavement Joint Design (AASHTO 1998). As may be seen, the cumulative distributions form two distinct groupings. The deflection basin area comprises a means for assessing the overall structural condition of the rigid or composite pavement structure. Although termed an area, the quantity is given in inches as the value is normalized with respect to the deflection under the load plate. A greater deflection basin area value indicates a stronger pavement structure. 4

IMPLEMENTATION

The results of the deflection testing were incorporated into a previously developed decision tree methodology. This methodology is founded on the results of a video-based surface distress survey. Pavements are rated according to the extent and severity of identified distresses (e.g. fatigue cracking, rutting, patching, etc.). From this, a suggested level of rehabilitation is assigned to each section. By assuming a typical cost for each level of rehabilitation, an unconstrained performance-based maintenance budget is developed. Incorporating the deflection testing results allows the unconstrained performance-based maintenance budget assessment to include pavement distresses that are not yet observable at the pavement surface and a measure of structural capacity and allows for a more accurate assessment of the pavement rehabilitation needs. As mentioned previously, the deflection data were used to develop structural capacity criteria by which each pavement section was evaluated. These criteria were also incorporated into a new decision tree methodology. The structural capacity criteria for flexible pavements consist of effective structural number (SNeff) and resilient modulus (MR). The structural capacity criteria for rigid and composite pavements consist of the deflection under the center of the load plate and deflection basin area. For each criterion, a threshold value was established from the consensus of VDOT pavement engineers based on the data presented in Figures 1 through 4, field experience, and 423

information available in the general literature. These threshold values are used to indicate whether or not the structural capacity of a pavement section is adequate as compared to that expected for a typical interstate pavement. For flexible pavements, an effective structural number of 6.0 and a subgrade resilient modulus of 68.9 MPa (10,000 psi) were established as the threshold values. For composite and rigid pavements, a deflection (0.0889 mm, 3.5 mils) under the load plate of the 40.03-kN (9000-lbf) load level and a deflection basin area of 813 mm (32 in.) were established as the threshold values. In addition to the deflection testing results, the existing decision tree models were updated to include age of the pavement surface and traffic level (in terms of annual average daily truck traffic). Figure 5 shows an example decision tree structure where the output of the original decision tree using the results of the video-based surface distress survey is “enhanced” by including structural data from the FWD deflection testing as well as pavement surface age and traffic level. The example in Figure 5 shows the specific decision tree when the videobased distress survey results indicate that preventive maintenance is required on a full-depth flexible pavement on the interstate system. VDOT’s Maintenance Division abbreviates the potential recommended rehabilitation alternatives as DN, PM, CM, RM, and RC indicating do nothing, preventive maintenance, corrective maintenance, restorative maintenance, and reconstruction, respectively. As a way of comparing the output of the original video-based decision tree structure and the enhanced version (including FWD deflection testing results, pavement surface age, and traffic level), Figure 6 shows the distribution of the various recommended maintenance treatments using the two decision tree methodologies for each homogeneous pavement section (weighted by the number of lane-miles having the same surface type) for the interstate pavement network. From Figure 6 it can be seen that use of the enhanced decision tree structure slightly reduces the percentage of lane-miles in the DN, PM, and CM categories while increasing the number of lane-miles in the RM and RC categories.

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Figure 5. Enhanced decision tree for interstate full-depth flexible pavement with a recommendation for preventive maintenance (PM) (from Wu et al. 2009).

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Figure 6. Cumulative distribution of recommended maintenance activity using the existing videobased surface condition decision tree versus the newly developed decision tree using enhanced data (including FWD deflection testing results, pavement surface age, and traffic level).

Table 1. Unconstrained maintenance recommendations for existing video-based surface condition decision tree versus the newly developed decision tree using enhanced data (including FWD deflection testing results, pavement surface age, and traffic level). Recommended maintenance cost, $ Pavement type

Surface condition only

Enhanced data

Percent change, %

BIT BOC BOJ CRC JRC Total

163,925,600 16,720,448 56,955,627 82,119,255 45,015,910 364,736,840

200,754,413 18,119,838 72,945,848 84,503,686 46,257,743 422,581,528

22.5 8.4 28.1 2.9 2.8 15.9

Table 1 shows the financial implications of modifying the decision tree structure. Table 1 presents the unconstrained maintenance recommendations for each pavement type using the existing decision trees based on the surface condition versus the newly developed decision trees using the enhanced data (including FWD deflection testing results, pavement surface age, and traffic level). Table 1 shows that the modification to the decision tree structure results in an unconstrained maintenance recommendation increase of approximately 15.9%. When the output of the two decision tree methodologies for each homogeneous pavement section were compared, 86.0% of the weighted lane-miles received the same recommended maintenance treatment, 10.6% were suggested to have a lesser treatment, and 3.4% were suggested to have a more substantial treatment. 5

CONCLUSIONS

The results of a network level FWD survey of VDOT’s interstate system were incorporated into an existing decision tree structure based on the pavement surface condition to yield an enhanced decision tree that also included pavement surface age and traffic level. Based on 425

these results, unconstrained maintenance recommendations for VDOT’s interstate system increased by 15.9% to approximately $422.6 million. The analysis also showed that the resulting recommended maintenance treatment was modified on 14.0% of the interstate lanemileage when the structural data, pavement surface age, and traffic level were considered. Approximately 10.6% of the interstate lane-mileage was recommended to have a less severe treatment, whereas approximately 3.4% of the interstate lane-mileage was recommended to have a more severe treatment. ACKNOWLEDGMENTS The authors acknowledge the assistance of Affan Habib, Trenton Clark, Bipad Saha, William Duke, and David Thacker of VDOT’s Materials Division; Michael Wells of VDOT’s Richmond District; Thomas Tate of VDOT’s Hampton Roads District; Lutrell Gordon of VDOT’s Maintenance Division; Zheng Wu of Mactec Consulting; Khaled Galal, formerly of VTRC; and Javed Alam, former graduate student at the University of Virginia. The authors acknowledge Randy Combs, Ed Deasy, and Linda Evans of VTRC for their assistance with the graphics and editorial process. REFERENCES Alam, J., Galal, K.A. & Diefenderfer, B.K. 2007. Network-level falling weight deflectometer testing: Statistical determination of minimum testing intervals and number of drop levels on Virginia’s interstate system. In Transportation Research Record No. 1990. Transportation Research Board, Washington, DC, pp. 111–118. American Association of State Highway and Transportation Officials. 1993. Guide for design of pavement structures. Washington, DC. American Association of State Highway and Transportation Officials. 1998. Supplement to the AASHTO guide for design of pavement structures: Part II, Rigid pavement design and rigid pavement joint design. Washington, DC. Diefenderfer, B.K. 2008. Network-level pavement evaluation of Virginia’s interstate system using the falling weight deflectometer. VTRC 08-R18. Virginia Transportation Research Council, Charlottesville. Galal, K.A., Diefenderfer, B.K. & Alam, J. 2007. Determination by the falling weight deflectometer of the in-situ subgrade resilient modulus and effective structural number for I-77 in Virginia. VTRC 07R1. Virginia Transportation Research Council, Charlottesville. Hossain, M., Chowdhury, T., Chitrapu, S. & Gisi, A.J. 2000. Network-level pavement deflection testing and structural evaluation. Journal of Testing and Evaluation, Vol. 28, pp. 199–206. Noureldin, S., Zhu, K., Li, S. & Harris, D. 2003. Network pavement evaluation with falling-weight deflectometer and ground-penetrating radar. In Transportation Research Record No. 1860. Transportation Research Board, Washington, DC, pp. 90–99. Virginia Department of Transportation, Materials Division. 2000. Guidelines for 1993 AASHTO pavement design. Richmond. Virginia Department of Transportation, Materials Division, and Cornell University Local Roads Program. 2007. ModTag users manual. Version 4.0. Richmond. Wu, Z., Shekharan, R., Chowdhury, T. & Diefenderfer B.K. 2009. Development and implementation of network-level selection of pavement maintenance and rehabilitation strategy: Virginia practice. Paper presented at the 88th Annual Meeting of the Transportation Research Board. Zaghloul, S.M., He, Z., Vitillo, N. & Kerr, J.B. 1998. Project scoping using falling weight deflectometer testing: New Jersey experience. In Transportation Research Record No. 1643. Transportation Research Board, Washington, DC, pp. 34–43. Zhang, Z., Claros, G., Manual, L. & Damnjanovic, I. 2003. Evaluation of the pavement structural condition at network level using falling weight deflectometer (FWD) data. Paper presented at the 82nd Annual Meeting of the Transportation Research Board, Washington, DC.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Application of FBG strain sensors in the measurement of three-directional strains within asphalt pavement D. Zejiao, T. Yiqiu & C. Fengchen School of Transportation Science & Engineering, Harbin Institute of Technology, Harbin, P.R. China

L. Hao Center of Pavement Material Development & Research, Beijing Municipal Road & Bridge Holding Company, Beijing, P.R. China

ABSTRACT: Fiber Bragg Grating (FBG) sensor is a relatively new tool to directly acquire dynamic strain responses of pavements subjected to traffic loading. Three-directional strain sensors jointed with a nylon junction are introduced here. At first, a four-point bending beam with FBG sensor embedded was designed to evaluate the coordinated working performance between sensor and pavement material in laboratory. Then, detailed instrumentation scheme on site is introduced followed with a preliminary analysis of different strain response histories. The results show that three-directional strains measurement put forward here gives fine responses for different loading conditions at different depths within the pavement structure. The pavement material is alternatively submitted to compressive and tensile strains, and observable residual vertical strain exists after single loading passes. 1

INTRODUCTION

In recent years, premature failure, such as rutting, stripping and cracking, were observed frequently on asphalt pavements in China. It is difficult to identify the damage mechanism of these failures through traditional investigation methods. FBG sensor is a new technology with promise to allow the real strain state of pavement structure to be monitored, which eliminates most of the assumptions in theoretical calculation. For example, the loading in theoretical calculation by BISAR is assumed to be circular while the actual traffic loadings are dramatically complicated and highly uneven (Zejiao, 2006). The measured strain responses using FBG sensors can acquire internal responses of pavements subjected to traffic loading, and help to design new type pavement structure and validate theoretical calculation (Fengchen et al., 2007). A comprehensive investigation of Beijing expressways in China has been carried out since 2006, which aimed at identifying the causes of premature failure for the existing pavement from the aspects of traffic condition, climate condition, pavement structure and material (Fengchen et al., 2007). During the investigation, obtaining strain responses of asphalt layers induced by the actual traffic loading is one of the most important contents. Different from the references, which just get strain responses in longitudinal and transverse directions, three-directional FBG strain sensors jointed with a nylon junction is proposed here to measure vertical, longitudinal and transverse strains at the same time at a testing site. Compared with traditional strain measurement, the vertical strain added can provide more useful information. The used sensors are developed by Harbin Institute of Technology (HIT), whose detailed information can be found in the reference (Hezhe, 2007). The acquisition and analysis of dynamic strain responses on site is designed to understand structural behavior of pavement and the causes of rutting. At first, a four-point bending beam with FBG sensors embedded was designed to evaluate the coordinated working performance or interaction between sensor and HMA material in laboratory, as the high-modulus protective material wrapping the fiber may change 427

the strain distribution of pavement material. Then, details of instrumentation on Beijing Liuhuan expressway, together with truck components and testing conditions, are presented in the paper. Finally, general observations from the strain responses measured in situ are discussed, followed with the description of the effects of loading speeds and magnitudes. 2

COORDINATED WORKING BETWEEN SENSOR AND PAVEMENT MATERIAL

The detailed parameters and properties of FBG sensors are given in Table 1 and Table 2. These sensors were developed based on Microbend Theory (Wulf, 1999). During strain measurement on site, two LFRP FBG sensors (measuring horizontal and transverse strains, respectively) and one SFRP FBG sensor (measuring vertical strain) were jointed with a nylon junction, and defined as three-directional strain sensor, which is shown in Figure 1a. Figure 1b shows typical structure of fiber cable of the developed sensors. It contains the core and cladding, which light can pass through, the coating, the reinforced Fibre and protective material that protect internal structure. The protective material of the sensors we used is a kind of fiber reinforced polymer, whose modulus is about 50GPa (Jinsheng, 2007). It is acknowledged that there is a significant difference of elastic modulus between sensor and pavement material in situ, which is also common to most of the available sensors currently. Note that the huge modulus difference tends to change strain distribution in the vicinity of the sensor within asphalt pavement, which will influence the reliability of the measured results from sensors (Zafar et al., 2005). As a result, a four-point bending beam test, similar to the reference (Michael et al., 2004; Janauschek et al., 2003), is designed to identify the coordinated working performance between sensor and HMA material, as shown in Figure 2. One of the different points is that the beam is made of HMA material rather than resin, which is used to simulate the interaction between sensor and pavement material in testing site. The length of the beam is 0.4 m, while the planar size is 0.1 m by 0.1 m. The effective length of the beam between two supporting points is 0.3 m, divided into three parts, thus fixes the geometrical positions of the line loadings. The LFRP FBG sensor, which would serve as horizontal or transverse strain sensor in actual pavement structure, was embedded into the bottom area of the beam where is in tension state according to the stress distribution of the beam. And the SFRP FBG sensor, which would serve as vertical strain sensor, was embedded into the top area of the beam where is in compression state. Figure 2 shows the two cases together, while during the actual experiment, just one kind of sensor is embedded. The theoretical strain on the axis of the sensor can be calculated with the following equation, which is independent of the material properties of the beam:

ε= Table 1.

24δ y 23a 2

(1)

Performance parameters of FBG sensor.

Parameter

Strain Range Accuracy Resolution sensitivity Wavelength range Reflectivity Durability με με με pm/με nm % years

Performance ±5000

±2∼3

Table 2.

±1

1.18∼1.22

1510∼1570

≥90

Dimensions and material properties of FBG sensor.

Parameter

Diameter mm

Length mm

Elastic modulus GPa

LFRP FBG sensor SFRP FBG sensor

4 6

70 20

50 50

428

≥25

Reinforced Fibre

SFRP sensor

Coating

LFRP sensor Cladding

Core

Protective material

a) Three-directional strain sensor Figure 1.

b) Typical fiber cable structure

FBG sensor.

h y δ a

a

LVDT

a

Figure 2.

Coordinated working test between sensor and HMA material in laboratory.

Figure 3.

Comparison of horizontal strain between beams with and without sensor embedded. 4000 Theoretical strain (με)

Theoretical strain (με)

4000 3000 2000 1000 0

Figure 4.

y = 8.3594x + 539.11 R2 = 0.8645 0

100 200 Measured strain(με) a) SFRP FBG sensor

3000 2000 y = 1.6489x + 383.19 R2 = 0.9805

1000 0

300

0

500 1000 1500 Measured strain(με) b) LFRP FBG sensor

2000

Testing results of FBG strain sensors in the laboratory.

where ε is the horizontal strain on the axis of the embe-dded strain sensor, y is the vertical distance between the axis of sensor and the central axis of the beam, a is one third of the distance between the supporting points, and δ is the vertical displacement of the beam, which was obtained with two LVDTs. From the equation, it can be seen that the resulted horizontal 429

strain is decided by the vertical displacement of the beam and geometrical parameters only (Shaoxing et al., 2007; Gengliang, 2007). A three-dimensional model for the beam with LFRP or SFRP sensor embedded with the actual sizes was built with ABAQUS software. The interaction between sensor and asphalt mixture was simulated with friction contact, defined with a penalty function in ABAQUS. Element type C3D8R was chosen for the beam, while FBG sensor embedded in asphalt mixture was simulated with element type C3D8I. Both anchors of FBG sensor were meshed with free grids, while element type C3D10M was used. The bottom of the beam contacted with the supporting area were fixed, and the top of the beam contacted with the loading strip were applied a displacement function to simulate the actual loading in the test. Figure 3 shows the comparison between the beam with sensor embedded and the pure beam. It indicates that the presence of sensor has a significant effect on the distribution of horizontal strain, and decreases the magnitude of the strain in the vicinity of sensor. Consequently, it is important to perform test to modify the results from the strain sensors. Figure 4 illustrates the relationship between the measured strain from embedded sensor and theoretical calculation. 3

INSTRUMENTATION

Figure 5 shows the locations of strain sensors along the pavement depth. A total of 24 strain sensors were installed into the pavement structure, which are divided into eight groups, with two LFRP sensors and one SFRP sensor for one group (i.e. eight groups of three-directional strain sensor). Two same sections with the distance of 1.6 m were used to make sure that proper measurement would be obtained. Two groups were located at the bottom of the middle asphalt layer under the two wheel paths, and another two groups were installed at the bottom of the bottom asphalt layer with a horizontal distance of 0.2 m from the upper groups, as shown in Figure 6. Four FBG temperature sensors were installed in pavement shoulder at the same depth as the strain sensors were, in order to take into account temperature effect. As the strain measurement was performed after the asphalt pavement was built, the proper cutting area is important to balance the disturbance of existing material and the boundary effect of embedded sensors. Here, planar size of 0.8 m by 0.8 m is milled and filled with the same pavement material as it was built. The installation of strain sensors on site is shown in Figure 7. All strain sensors were tested before and after installation to ensure proper data to be collected. Three-directional strain responses were measured under various loading conditions. Figure 8 shows the axle components of two trucks used in the experiment. The truck speeds were varied from 5 km/h to 20 km/h (Here, low speeds were chosen as it was difficult to control the loading points of tires right on the sensors when the truck passed by). The SI 425 Optical Sensing Interrogator was used to collect the signals from the sensors, whose frequency is set to 250 HZ. Figure 9 gives the conditions of strain measurement on site.

SMA-16 AC-20 AC-25 Figure 5.

Locations of FBG strain sensors in one section (Not to scale).

430

Figure 6. Layout scheme of strain sensors for testing segment (Not to scale). Note: “B” denotes sensors located in bottom asphalt layer, “M” denotes sensors located in middle asphalt layer.

Figure 7.

Installation of three-directional strain sensor on Liuhuan Expressway.

1540kg

4480kg

11780kg

15240kg

a) Loading level I

b) Loading level II

Figure 8.

Two loading levels in strain measurements.

Figure 9.

Three-directional strain measurement on site.

431

4

RESULTS AND ANALYSIS

4.1 Typical time histories of three-directional strains Concerning time histories from strain sensors, it was found that the shapes of responses from most of the sensors were similar. Figure 10 shows the typical three-directional strain histories, from the middle asphalt layer, at the speed of 10.9 km/h, by the rear axle of load level II. As it can be seen that, in the longitudinal direction, the sensor firstly shows compressive strain from the approaching loading, then important tensile strain during its passing and finally compressive strain when the loading moves away. There is an observable residual strain recovering gradually after the load departs. Generally, pavement material is alternatively submitted to compressive and tensile strains. In contrast, in the transverse direction, the sensor shows a small compressive strain from the approaching loading, and then important tensile strains are observed during the pass of the loading. As for the vertical direction, a small tensile strain is seen when the loading closes, and a primary compressive strain is recorded during the loading passes. What’s more, similar to the horizontal direction, an observable residual strain also exists and recovers step by step when the loading departs. It illustrates that asphalt pavement has obvious viscoelastic characteristics. What’s more, the measured vertical strain can also be used to predict the permanent deformation of asphalt layer, which shows three-directional strains measurement can give more useful information than the traditional method. 4.2 Effect of loading conditions

250

250

200

200

150 100 50 0 -50 0

0.4

0.6

0.8

1

150 100 50 0 -50 0

0.2

-100

Time(s) a) Horizontal strain history 100 Vertical strain(με)

-100

0.2

Transversal strain(με)

Horizontal strain(με)

Many factors, such as loading speeds and magnitudes, lateral distance from the sensors to the loading positions and installation procedure, may have significant effect on the measured strains. Hence, it is important to keep the testing conditions well. Figure 11 illustrates the effect of loading speeds and magnitudes on the vertical strain histories. It is shown that the magnitudes of vertical strain decrease with the increase of testing speeds. And similar trend for the residual strain is also observed. On the contrary, with the increase of loading

0 -100 0

0.2

0.4

0.6

0.8

-200 -300 -400 -600

Time(s) c) Vertical strain history

Typical three-directional strain responses.

432

0.6

0.8

Time(s) b) Transverse strain history

-500

Figure 10.

0.4

1

1

100

0

0

-100 0

0.5

1

1.5

Vertical strain(με)

Vertical strain(με)

100 2

-200 -300 -400 -500 -600

1

-300 -400 Load level I load level II Time(s)

Middle Bottom

200

0.2

0.4

0.6

0.8

1

-300 -400 Middle Bottom

-500

Transversal strain(με)

Vertical strain(με)

0.8

Effects of loading speeds and magnitudes (rear axle).

-200

150 100 50 0 -50

-600

0.0

0.3

0.6

0.9

1.2

1.5

Time(s) b) Transverse strain (V=7.0km/h, Load level II)

Time(s) a) Vertical strain (V=9.2km/h, Load level I)

Figure 12.

0.6

b) Different loadings (middle layer, V≈17km/h)

100 0 -100 0

0.4

-200

-600

a) Different speeds (bottom layer, Load level I) Figure 11.

0.2

-500

V=3.2km/h V=9.2km/h V=17.4km/h

Time(s)

-100 0

Strains at different depths (rear axle).

magnitudes, vertical strains increase on the whole (Comparative speeds for both loading levels, Load level I is at 17.4 km/h while Load level II is at 16.7 km/h). 4.3 Effect of depth Figure 12 presents the strain results at different depths within pavement structure. In the vertical direction, the strain magnitude of the bottom asphalt layer is smaller than that of the middle asphalt layer. What’s more, a time-delay occurs between the two layers (Note that the delayed time due to the horizontal distance between the two sets of sensors, 0.2 m, has been already eliminated here according to the corresponding testing speed). This time-delay is about 0.038 s. Similarly, in the transverse direction, there is also a time-delay about 0.042 s observed. Furthermore, the longer time history in the bottom asphalt layer compared with that in the middle asphalt layer is noticed. Different from vertical strain, the bigger magnitude of the transverse strain in the bottom asphalt layer than that in the middle asphalt layer is got. Similar phenomena have been observed in finite element simulation (Al-Qadi et al., 2005; Zejiao, 2006) and strain measurement on site (Muraya et al., 2004; Xicheng et al., 2004). 5

CONCLUSION AND RECOMMENDATION

This paper gives preliminary results from Beijing Liuhuan Expressway in China using threedirectional FBG strain sensors developed by HIT, and presents details on the coordinated working between sensors and pavement material and instrumentation on site. It is noted that available published information has no vertical strain measurement like that in this paper. From the results of the strain measurement on site, it can be seen that three-directional strain sensors can give fine results for different depths within pavement structure and 433

different loading conditions. The added vertical strain can be used to predict the permanent deformation of asphalt layer, which shows three-directional strains measurement can give more useful information than the traditional method. Whereas, it is acknowledged that available strain measurement including presentation here are all classified as single-point strain measurement, not a distributed one. Therefore, it is important to control the testing conditions as designed, such as loading positions, speeds and magnitudes etc. The numerical simulation of the distributed traffic loading on asphalt pavement based on material characteristics in situ has been carried out now. Further comparison between simulation and measurement, and performance evaluation based on measured strains, are recommended. ACKNOWLEDGEMENT The work presented here was the results of hard work by many fellows. The authors would like to express our gratitude to “Beijing Municipal Road & Bridge Holding Company” for the effort in sensors installation and data collection. Finally, the authors are grateful to the fund from “the National Natural Science Funds (50808056)”, “Development Program for Outstanding Young Teachers in Harbin Institute of Technology (HITQNJS.2007.032)” and “Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) for young teachers (20070213014)”. REFERENCES Fengchen, C., Yiqiu, T., Hao, L. & Baoxin, W. 2007. Analysis of Strain in Asphalt Pavement Using FRP-OFBG Sensors. Proceedings of the 7th International Conference of Chinese Transportation Professionals (ICCTP). Shanghai:1–8. Fengchen, C., Zejiao, D. & Baoxin, W. 2007. Comprehensive Investigation of Asphalt Pavements Performance for Beijing Highways-Material Performance Research and Stress Analysis. Research report of project, Beijing: Beijing Municipal Road & Bridge Holding Company. Gengliang, T. 2007. Study on Asphalt Mixture and Optical Fiber Diffraction Grating Sensor Coordination Distortion. Master Thesis, Harbin: Harbin Institute of Technology. Hezhe, W. 2007. Research on FBG Sensors for Practical Infrastructures and their Application in the Measurement of Highway Road. Master thesis, Harbin: Harbin Institute of Technology. Imad, L. Al-Qadi, Mostafa Elseifi & Pyeong Jun Yoo. 2004. In-Situ Validation of Mechanistic Pavement Finite Element Modeling, 2nd International Conference on Accelerated Pavement Testing, Minneapolis: 1–14. Janauschek, M. & Heinrich, M. 2003. Laboratory Testing on Strain Gauges. final report of Short Term Scientific Mission to COST action 347. Jinsheng, L. 2007. Development and performance of asphalt pavement strain sensors based on FBG technology. Master Thesis, Harbin: Harbin Institute of Technology. Michael, W. & Jacques, P. 2004. Comparative Strain Measurement in Bituminous Layers with Use of ALT, Second International Conference on Accelerated Pavement Testing, Minneapolis: 1–24. Muraya, P.M. & van Dommelen, A.E. 2004. APT Testing and Visco-elastic Analysis of Asphalt Motorway Pavements. 2nd International Conference on Accelerated Pavement Testing, Minneapolis: 1–15. Shaoxing, C., Xiaoning, Z., Quanliang, X. & Shutao, M. 2007. Experiment and Research of Grating Strain Sensor on Asphalt Pavement. Chinese Journal of Sensors and Actuators, (2):39~1410. Wulf von Eckroth 1999. Development and modeling of embedded fiber-optic traffic sensors. Doctor dissertation, Florida: Florida Institute of Technology. Xicheng Qi, Terry Mitchell, Kevin Stuart, Jack Youtcheff, Katherine Petros, Tom Harman & Ghazi AlKhateeb. 2004. Strain Responses in ALF Modified-Binder Pavement Study. 2nd International Conference on Accelerated Pavement Testing, Minneapolis: 1–26. Zafar, R., Nassar, W. & Elbella, A. 2005. Interaction between Pavement Instrumentation and Hot-MixAsphalt in Flexible Pavements, Emirates Journal for Engineering Research, 10 (1): 49–55. Zejiao, D. 2006. Dynamic Response Analysis of Saturated Asphalt Pavement Based on Porous Medium Theory. Doctor dissertation, Harbin: Harbin Institute of Technology.

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3D visualization model of road surface X. Li, S. Ma & X. Hou School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin, Hei Longjiang, China

ABSTRACT: The purpose of this paper is to introduce a new method for 3D visualization modeling of road surface. The modeling data are intensive transects of 3D data, which are collected by multifunction road monitoring vehicle. The first step is to establish a method used for dealing with the massive data, converting the data into the needed format for directly using of modeling. Based on further development of the existing road design software, a road surface terrain model is made, realizing the road surface 3D visualization. This model can provide 3D digital information of the road surface, information of the catchment area and scale calculation of its area. It can also provide complete, objective, and accurate 3D digital information for the road surface distortion distress identification, the road surface condition evaluation, road surface science maintenance management, road safety and so on. 1

INTRODUCTION

During the road maintenance management process, the most important thing to do is monitoring and evaluating the road quality indicators objectively and accurately. According to the results of the evaluation, taking scientific maintenance measures timely is needed for extension of the road serviceable life. Examining and evaluating various distortion distresses fast, accurately and safely, and providing the true 3D information of the road surface circumstances, are keys to the scientific guidelines for the road maintenance management. So establishment of the road surface 3D visualization system is necessary. The purpose of this paper is to present research on a new method for establishing a digital visualization model of the road surface quickly and easily. Existing 3D modeling software mainly concentrates on geographic information systems and does not establish 3D model of the road surface. Existing road design software has been used for road surface terrain model building. Based on further development of the software, road surface terrain model can be used to visualize 3D road surfaces. The model can give the information of the road catchment area, and also can show the depth of its area. 2

REALIZATION OF ROAD SURFACE 3D VISUALIZATION

2.1 Development tool The software which this paper uses is mainly applied for survey and design assignment in civil engineering. It has itself graphics platform, independency data and graph editing system. Its most significant feature is that it can provide a macro control computer language for users (similar to BASIC language) and can directly access the development function of the design data. Users can develop the software further for the purpose of extended functions. Because the software is for road design, the first task to focus on road surface modeling. Based on studying the features and the models of the software, it was concluded that the software could provide a feasible platform for practical work described in this paper and summarized as follows:

435

1. The software provides a macro-control computer language for users (similar to BASIC language) and can directly access the development function of the design data. Users can develop the software further for the purpose of extended functions. 2. The software includes an integrated measurement data-processing module, which can accept external free-format data input. 3. The software has the digital terrain model module, which can provide feasibility for the road surface digital model building. 2.2 Data preparation The data that this paper makes use of are intensive transect 3D data, which were collected by multifunction road monitoring vehicle from a road in Changchun (Hou Xiang-Shen, 2004). The multifunction road monitoring vehicle is shown in Figure 1. The data were collected every other 0.2 m. Each road transect had 16 test points, and the interval of each point was 0.2 m. This paper intercepts 50 meter section of the road for the actual 3D modeling (Fukuhara, 1990). This paper uses the existing road design software to realize the 3D visualization of the road surface, so making the data apply to the requirement of the software was the first task. The requirement for the data format is given in Table 1. 1. Make the data format suitable for the software and save the data file format as TXT or DAT format. 2. The software defaults the point which the value of elevation is 0 as an invalid point. So, on the basis of not changing the existing topography, all the elevation data plus a fixed number reunification are collected. The modeling data pass through a series of transaction, when the data format is suitable for the requirement of the software, it can be used an input into the software. Each operation step can be saved automatically by the system; the generation files are all saved in the project file. Based on the further development of the softwware, a new program was developed to input the data file of the ASCII format. This program that this research effort focused to develop is given as follows:

Figure 1.

The multifunction road monitoring vehicle.

Table 1.

Requirement for data format. Field format

Field name

Initial line

Field width

Field type

Necessity

Point no. Abscissa E Ordinate N Elevation H

1 (Flush Left) 18 (Flush Right) 31 (Flush Right) 44 (Flush Right)

16 spaces 12 12 12

Series Real type (F12.4) Real type (F12.4) Real type (F12.4)

Yes Optional Optional Optional

436

VERSION 8 USE QPREXT.QPC SYMBOLE * !WJM;!PointNo;xx;yy;zz;Kode;Code !WJM="Data file.ASC" FILE_OPEN 1;NAME=!WJM BBB1: FILE_READ 1;EOF;*;!PointNO;NN;EE;HH IF EOF<>0 THEN GOTO BBB2 XX = EE YY = NN ZZ = HH KODE = 88 SAVEPOINT !PointNo;XX;YY;ZZ;Kode;Code GOTO BBB1 BBB2: FILE_CLOSE 1 STOP The command SAVEPOINT can input the coordinate data into the topographic map. According to the method, the external data points can be inputted into software as shown in Figure 2. The elevation data are entered into the software to form a triangulated regular network. The distance between individual points or the grid size is 0.2 m. The grid has 4016 rows and 16 columns, with a length of 50 m and a width of 3 m. The grid is transformed into ASCII data format by a command. The data file is saved as row-column type in the notepad file. It is easy to obtain and deal with the computer data program, in order to meet the requirement of other software as well. It can also open the ASCII data format source file directly in the project folder, and then compile the required data format in the source file, which was done in the modeling work described next. 2.3 Generation of the triangle net After reading the data into the software, it is ready for model building. First the program develops a new digital model, and then the data are entered into the digital model. The data format is checked and modified automatically, and a proper border of the model is formed, then the triangle network is generated by configuration analysis and calculation (He QuanJun, 2006). The triangle network is shown in Figure 3. 2.4 Establishment of the road surface digital model The program establishes a contour layer which can save the elevation information of the data under the option of dealing with the topographic map. Then, the road surface elevation model can be set up under the option of contour.

Figure 2.

Grid points used for modeling.

437

Figure 3.

Triangle network.

Figure 4.

3D space calculation.

The calculation of the contour is based on the triangles. Usually, these triangles are formed by the connection of the middle points in the model. Then the software reads these triangles into the active layer by leading the triangular function into the model. It can also deal with the digital contour model directly. For that, the point should be saved as a point grid format as an ASCII file. Triangles will be generated when the software reads the digital contour model data. These triangles will be used for the subsequent calculation of contours from original data. After entering the triangle network into the software and modifying the parameters, the road surface digital elevation model is set up. The calculation mode uses is 3D methodology. This calculation mode is obtained based on the definition of the triangles in the 3D space and taking into account the properties of triangle edges. Because many triangles pose an arch type surface, as in the processing and analysis modules model calculation, grid and fault lines identify the space location of each adjacent triangle. The principle is to distinguish between the boundaries within adjacent triangles and ease connectivity, that is, whether they appear in the neighboring triangle between easing connections or not. Surface twists and turns to the edges of the triangle are known as the hard edges. And the hard edges of the contour lines intersect in the curved intersection. Always they intersect adjacent triangles, and separate from the soft edges. For hard edges component, the fault lines are defined in the digital terrain model. Under normal circumstances, soft edges are generated by automatic network configuration. The advantage of this method is that contour lines may never intersect, as shown in Figure 4. 2.5 Realization of road surface 3D visualization The space model of Road design software based on DirectX9.0 or OpenGL1.4 version can be shown from different angles, viewing and inspecting of all true models. To import the project 438

(a)

(b) Figure 5.

Road surface 3D visualization model.

which was established in the software, a new space view window should be set up, to select the data model which has been completed. The space-view of the model is established by the system which is shown in Figure 5. In this paper, two data models are illustrated, one is to import all road surface elevation data information in meters, showing the road surface 3D model of the actual road surface. The other data model is to expand all road surface elevation data up to 10 times to improve ease in visualization. it can be very obvious to see that deformation, damages for the rutting and subsidence, and other distresses formed on the road surface, as shown in Figure 5. 3

ROAD CATCHMENT AREA

Asphalt pavements are mainly used for large-scale road construction in China. Evenness becomes the most direct factor that affects the road traveling comfort. The vehicle vibration is mainly caused by the unevenness of the road surface. Vibrations and bumps not only affect vehicles to move safely, but also affect the comfort of the travelers on it, and make people feel too tired (XU Shi-Fa, 1994). Among the many defects of unevenness, for the most important road distress is rutting. That is because if the rutting is formed, the road surface has excess deformation, the evenness of the road surface is destroyed, the comfort factor is reduced, and the rutting seriously affects driving. The catchment area in the rutting leads a floating slip to vehicles; it has seriously affected the security of high speed traffic (HOU Xiang-shen and MA Song-lin, 2006). The depth of the road surface catchment area is an important factor for the phenomenon of floating slip. Therefore, identifying the road surface catchment area was the primary work for road traffic safety evaluation. Using the road surface model developed, this paper visualizes transects of the road surface. Through the data file that transects provide, it can determine the maximum depth of the road surface rutting and identify water regional scope. This work can provide ample database for analysis the degree or the depth of rutting catchment area and its effects on traffic safety. 439

3.1 Extraction of road surface transect As the road surface model has established for above, it has already produced a continuous road surface data, through the software, a series of operations generated transects of the road surface. Through processing, the software is dismissed from the transect design operation and generates the transect ground line directly, as shown in Figure 6, on the map of the coordinates of any point and elevation can be real-time display. From the generation of transects, it can analyze the most depth of rutting on the road surface and also can identify possible catchment area. By exporting transect pro system file generated by the software to the project document folder, these data can be used to evaluate and analyze project work. 3.2 Road surface catchment area To ascertain the road surface catchment area, one must first study rutting section. The rutting section pattern is varied, from the clustering analysis; it generally falls into two forms. It is mainly caused by the deformation such as tire wear, round a trace of each with 2–4 rut chutes, and the shape of it is W-shaped; the other is a typical example of China’s expressway rutting patterns, and it is mainly aroused by the asphalt mixture high-temperature creep flow, each round with only a trace identical slot, and the shape is U-shape, as shown in Figure 7 (Kelvin C.P.Wang, 1999). The definitions of the indices in Figure 7 are as follows: RD1—the most depth of rutting; RD2—the most likely depth of the rutting slot catchment area;

0.400

Figure 6.

Transect of the real survey road.

Figure 7.

The rutting transect.

440

0.000

0.035

0.191 0.105 1.5

1.4

1.3

1.2

1.1

1.0

0.9-0.298

0.8 -0.278

0.7 -0.257

0.6 -0.253

0.4

0.3

0.2

0.1

0.0

Road transect(m)

-0.219 -0.124

0.014

0.185 0.195 0.184 0.175 0.099 -0.1

-0.2

-0.3

-0.4

-0.5

-0.6

-0.7

-0.8

-0.9

-1.0

-1.1

-1.3

-1.4

-0.400

0.5 -0.247

-0.300

-0.112

-0.200

-0.132 -0.131 -0.142 -0.142 -0.053

-0.100

-1.2

0.000

0.000 -0.061 -0.136

0.100

0.037 0.091 0.192 0.196 0.178

0.200

-1.5

Elevation(cm)

0.300

Figure 8.

Water flow direction illustration.

Figure 9.

Road surface catchment area.

W1 —the most horizon width of the rutting slot top; W2—the most likely width of the rutting slot catchment area; and W3—the width of the rutting slot bottom. According to the rutting sections analyzed, the depth of the rutting is extracted separately from the left side and right side of the left track and right track of each transect of a 50-m section of the road surveyed. According to the extraction results, coordinates are entered in the software to identify the road surface catchment area. Figure 8 is the sketch map of the road surface catchment area with water flow arrows. The four red lines in it are the critical region lines of the left and right tracks. This paper uses the symbol and document operation of the software to mark the catchment area and the most depth of rutting every five meters of the track, as shown in Figure 9. 4

CONCLUSIONS

Based on studying mapping knowledge about Geographic Information Systems, Digital Terrain Model, and Digital Elevation Model, and using method of the existing terrain 3D visualization model, the findings of this paper support the following summary and conclusions: a. This paper demonstrated pertinent ways for handling massive data collected by the road testing vehicles. The data were conveniently stored entered for modeling. b. Based on the secondary development of the existing road design software, the elevation model of road surface was developed for 3D visualization. The model can capture the digital information of the road surface in an apparent way. 441

c. The developed model can extract the information of the road surface transects, showing the rutting information, and can also give the data message about the highest and the lowest point of the road surface transects. The transect data files which are exported can be used for other research and evaluation work. d. The model generates arrows showing water flow direction on the road surface. It can also show the road surface catchment area and the rut depth information, and calculate the area of catchment. REFERENCES Fukuhara. (1990). “Automatic Pavement-Distress-Survey System.” ASCE Journal of Transportation Engineering, 116(3): 280–286. HE Quan-Jun. (2006). “Implementation of 3D Terrain Visualization System by IDL.” Journal of Geomatics 31(1): 19–20. HOU Xiang-Shen. (2004). “Development Points of Rutting Instrument.” Harbin Institute of Technology: 1–3. HOU Xiang-shen; MA Song-lin; and WANG Cai-xia. (2006). “Research on Measurement and Evaluation of Asphalt Pavement Rutting Based-on Traffic Safety.” Journal of Highway and Transportation Research and Development 8: 14–17. Kelvin C.P. Wang. (1999). “Investigation of Image Archiving for Pavement Surface Distress Survey.” A final report submitted to Mack-Blackwell Transportation Center: 357–405. XU Shi-Fa. (1994). “Pavement Rutting Depth Related to Vehicle Travel Safety.” Journal of Beijing Institute of Civil Engineering and Architecture: 1–5.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Three years of high speed deflectograph measurements of the Danish state road network S. Baltzer Danish Road Directorate, Danish Road Institute, Denmark

ABSTRACT: The Danish High Speed Deflectograph (HSD) is an advanced measuring vehicle that uses laser technology to scan the network with regard to bearing capacity. It operates at traffic speed, at a maximum of 80 km/h, applying a 10 ton axle load on the pavement surface. In 2005, 2006 and 2007 the Danish state road network of approximately 1600 km was surveyed with the HSD. The result is continuous values of the structural curvature index SCI300, providing a remarkable overview of the structural condition of the network. The paper contains comparisons between measurements conducted through the three years. Looking deeper at individual road sections, the possible causes of observed changes from one year to the next will be investigated and discussed. 1

BACKGROUND OF THE HIGH SPEED DEFLECTOGRAPH

The High Speed Deflectograph is a recently developed measuring device. During the period from 1996 to 2001 The Road Directorate, Danish Road Institute and Greenwood Engineering A/S developed a prototype of a device suited for measurement of road pavement bearing capacity (Hildebrand & Rasmussen, 2002). The development was funded with 80 percent of the expenses by the Danish Agency for Trade and Industry. Since then, the HSD has been developed further towards a higher functionality and better data material (additional laser sensors). In 2005 the Danish Road Institute started testing the equipment in its present configuration on full network scale. The idea behind the measuring concept emerged at Greenwood Engineering A/S, which today has patented the concept and markets the device under the name Traffic Speed Deflectometer (TSD). 2

PRINCIPLE OF OPERATION

The High Speed Deflectograph (HSD) is basically a truck with a 10 ton dual wheel rear axle, which is the Danish design load. The movement of the pavement surface caused by the axle load is measured with four Doppler laser sensors positioned as shown in Figure 1. The laser sensors measure the vertical velocity of the deflected pavement surface. This result can be transformed into continuous values of the well known structural curvature index, SCI300, with the unit 1/1000 mm. SCI300 is the deflection in 300 mm’s distance subtracted from the center deflection. The higher value of SCI300, the softer the pavement. Detailed description of the measuring principle and the mathematics involved can be found in (Krarup et al., 2006). The HSD operates at traffic speed, which in practical conditions is up to 80 km/h which is the speed limit in Denmark. Minimum operational speed is 40 km/h. 3

APPROACH OF TESTING AND IMPLEMENTATION

Testing of the prototype and the current version has convinced the Danish Road Institute that the HSD provides reliable and repeatable measurements that correlate well with the Falling 443

Figure 1.

An illustration of the High Speed Deflectograph.

Table 1.

2005 2006 2007

Overview of measured network in 2005–2008. Total network km

Measured Lane km

Measuring time

Daily production km/day

1600 1600 3600

3200 2960 3800

3 weeks 13 measuring days 22 measuring days

210 225 170

Weight Deflectometer (FWD). Next step has been to start implementing it as a scanning tool at network level. Therefore, since 2005 the major emphasis in testing has been to study more practical issues at network level as e.g.: • • • • •

Is the equipment sturdy? How long does it take to measure the entire network? Operators and drivers should get experience, and write manuals Experience with processing of a large number of large data files What kind of numbers to expect, and how do measurements repeat themselves year after year?

In 2005 and 2006 the Danish Road Directorate administered approximately 1600 km of road being mainly motorways. In 2007 Denmark experienced a structural change in road administrations and the Road Directorate’s network expanded with approximately 2000 km of major roads. The table below shows what has been measured and the approximate measuring time. Looking at Table 1, it may seem like a small daily production as the measuring speed is 80 km/h. But this number of daily production kilometers is found satisfactory, as it covers a large range of daily productions. Going only on the motorways, lots of km can be measured in one day. Other days there might be some travelling between sections or some instruments are teasing, and require that the system is shut down and restarted. Also the Danish summer is not stable when it comes to the weather. Sometimes showers delay the measurements, or the drivers have to drive to a different area with a better weather forecast. In 2007 the daily 444

production goes down, as the new roads in the network pass through cities and have roundabouts and crossings. After these three years we can conclude that the equipment is sturdy and stable in its current configuration. Drivers, operators and data analysts now have routines for their work. Data are attached to correct chainage and stored in databases as data from any other measuring vehicle at the Danish Road Institute. Data are not yet used in the pavement management system. With regard to data, three examples will be provided in this paper: Repeatability within a day: Rehabilitation of a short motorway section was necessary, so FWD measurements were required. HSD measurements were performed just before and just after the FWD, and show the repeatability of measurements and correlation with FWD. 35 km of a two-lane road: Two sections had new wearing course in 2006, and FWD measurements from 2005 exist. 65 km motorway: This motorway has a concrete section that clearly stands out. 4

STATE ROAD MEASUREMENTS 2005–2008—EXAMPLES

4.1 Repeatability within a day In April 2007, FWD tests were conducted on slightly more than 1 km of a motorway section that were damaged and needed some degree of rehabilitation. The section was closed for FWD measurements between 10 am and 2 pm, but was measured with the HSD three times before 10 am and twice after 2 pm. For this investigation the SCI300 from the HSD was processed as an average value for every 1 m. The deflections measured by the FWD were used to calculate SCI300 for comparison. The FWD was set up with a 300 mm diameter plate with a pressure of 707 kPa. The measured values show very good repeatability as shown in Figure 2. SCI300 calculated from the HSD measurements result in slightly higher values than the values calculated from FWD measurements, but both devices capture the same change in bearing capacity over the section. Although the FWD is set up to simulate the loading of a 10 ton axle, the loadings are different in nature, and the SCI300 cannot be expected to be completely the

All runs - M4

140

120

SCI300 [microns]

100 Run 1 Run 3 80

Run 5 Run 8 Run 10

60

FWD

40

20

0 2000

2200

2400

2600

2800

3000

3200

3400

Chainage [m]

Figure 2.

Five HSD measurements and one set of FWD-measurements on the same day.

445

Table 2. Summary of HSD measurements on the motorway from km 2.300–km 3.400, April 2007. Runs 1, 3 and 5 were performed before the FWD measurements, 8 and 10 after.

Speed at measurement [km/h] Air temperature avg. [ºC] Surface temperature avg. [ºC] SCI300 average

Run 1

Run 3

Run 5

Run 8

Run 10

FWD

77 16.3 13.6 39.2

81 17.1 14.6 43.9

77 17.4 15.3 44.7

80 18.2 24.3 49.1

79 18.4 24.5 48.4

– 18.9 25.9 31.2

same for the two devices. But the variation in bearing capacity over the section should be reflected by both devices and Figure 2 shows that this is the case. Looking at these data, simple statistic analyses on the ratio between SCI300 from the HSD and FWD, reveals that the SCI300 measured by the HSD is in average 1.8 times greater than measured by FWD. This ratio varies from 0.7 to 3.2 with a standard deviation of 0.7. Table 2 gives a summary of the values measured between chainage km 2.300 and km 3.400. SCI300 from HSD and FWD measurements are difficult to compare as average values, as the HSD-values comes from a dataset of 1200 points, while the FWD dataset only provided 12 points. But as shown by Figure 2, the FWD values again show to be slightly lower than the HSD values. Looking only at the HSD runs there is an increase in the average SCI300 value detected as the day progresses, except for the last run. This shows a softening of the pavement which could very well be explained by the increasing temperature of the asphalt layer. Figure 2 and also some of the following figures show that the HSD measurement may yield negative values of SCI300 on stiff sections. This should not be possible, but is one of the drawbacks in the current calibration procedure. 4.2 Three years of measurements on a two-lane road This two-lane road has been measured every year since 2005 with the HSD. Results of both right and left side of the road are shown in Figure 3. Generally the measurements are very satisfactory. The curves follow each other as well as could be expected. There seems to be no significant difference between the bearing capacity of left and right side of the road. This road had new wearing course at two sections, indicated with vertical lines and arrows in Figure 3. Looking closer at the different sections to see whether the effect of the two wearing courses in 2006 can be detected, one arrives at the numbers shown in Table 3. It shows that the SCI300 increases year after year, indicating a decrease in bearing capacity, at sections where the wearing course has not been renewed. This seems correct. The increase in SCI300 is somewhere between 1 and 13 microns, corresponding also to 1–13 percent. The reinforcement layer in section km 6.900–km 9.700 clearly improves the bearing capacity, as it results in a decrease in the SCI300 values of approximately 30 percent. However it is not clearly detectable whether the wearing course in section km 18.620–km 21.320 was laid out before or after the 2006 HSD measurement. The thickness of the asphalt layer in this section is approximately 180 mm. Possibly, an increase of approximately 30 mm is not enough to show clearly. Figure 4 shows a section with extensive FWD measurements in close up. The FWD measurements were performed in July 2005. Again, the SCI300 calculated from FWD measurements appear to give lover numbers than the SCIs from the HSD measurements. But the general shapes of curves are fairly comparable. A few observations in Figure 4 need explanations: Chainage [km] 11.200–12.500: 29.050: 29.135–32.000:

Information from database on materials give indications of a layer of concrete underneath asphalt surface course. Possibly a drainage pipe. Cannot be clearly detected from photos. There is a gap in chainage. 446

400

350

300

2005 - Right

250

SCI300 [microns]

2006 - Right 2007 - Right 200

2005 - Left 2006 - Left

150

2007 - Left wearing course 2006

100

wearing course 2006 50

0 0

5

10

15

20

25

30

35

40

-50 Chainage [km]

Figure 3. Three years of measurement on 35 km dual carriageway. Both right and left sides of the road are shown. Sections with new wearing course 2006 are indicated with arrows. Table 3. Statistics of HSD measurements 2005–2007. The 35-km road is divided into different sections according to rehabilitation undertaken during the period. SCI300 [microns] Average of left and right Percent change Section [km]

Rehabilitation

2.000–6.900 6.900–9.700

– 2006: 60 mm reinforce ment layer with a 20 mm wearing course – 2006: 30 mm wearing course –

9.70–18.620 18.620–21.320 21.320–35.000 Avg. conditions during measurements

Speed of measure ment [km/t] Air temperature [ºC] Surface temperature [ºC]

2005

2006

2007

94

101

110

7

9

115 107

83 120

94 127

–28 12

13 6

156 154

147 155

132 164

–6 1

–11 6

69 17.5 *

65 23.2 *

2005/2006

2006/2007

75 22.4 28.9

*: Infrared thermometer not recorded in 2005 and 2006.

4.3 65 km motorway This motorway section was measured with HSD in 2006, 2007 and 2008. Results from the left side of the road are shown in Figure 5. Again a few points or sections stand out: Chainage [km] 237.060:

Passing a bridge. The downward peak is likely to be the joint between bridge and road. 447

400

350

300

SCI300 [microns]

250 2005 - Right 2006 - Right 2007 - Right 2005 - Left 2006 - Left 2007 - Left FWD 2005

200

150

100

50

0 21

22

23

24

25

26

27

28

29

30

-50 Chainage [km]

Figure 4.

Close up on section 21–30, where also FWD-measurements are added to the diagram.

140

120

100

SCI300 [microns]

80 2006 - Left 2007 - Left

60

2008 - Left 40

20

0 220

230

240

250

260

270

280

290

300

-20 Chainage [km]

Figure 5.

Three years of measurements on 65 km motorway, left side of the road.

263.200–265.900: 291.400

The concrete section. Photos show an access ramp. Possibly a place where one construction stage ended and another started and therefore different pavement structures. These measurements do not consistently show a slight increase in SCI300 from year to year, as would be expected. The measurements in 2006 and 2008 have a relationship as expected, 448

Table 4. Average values resulting from HSD measurements 2006–2008 from km 230–275 left lane.

SCI300 [microns] Speed of measurement [km/t] Air temperature [ºC] Surface temperature [ºC]

2006

2007

2008

44 81 21.3 *

27 81 15.7 18.5

59 82 19.6 26.0

*: Infrared thermometer not recorded in 2005 and 2006.

with a yearly increase in SCI300 of 5–10 microns as also found in the example above. The measurements in 2007 indicate a much stiffer structure than found the two other years. Some of this increase in stiffness could be explained by the colder weather during the measurements in 2007, and the influence that the temperature has on an asphalt layer with a thickness of approx. 250 mm which is typical for motorways in Denmark. But as there is also an increase of stiffness of the concrete section, there might also be some uncertainty in the calibration angle used for these 2007 measurements, resulting in a slight shift of values. 5

CONCLUSIONS

Looking at network level, the HSD shows very good repeatability in its ability to detect variation in the structural performance of pavements. It can provide a complete and continuous overview of the entire state network in less than one month, and it does not require road closures or other special considerations. This paper has looked deeper into a few examples, selected because the author knew there would be features as new overlays or significant variations in structure, as the concrete section, to investigate. All examples show that different runs with the HSD yield similar “curve” of SCI-variation. Also this curve-shape compares well with SCI300-values calculated from FWD-measurements. Significant changes in structure are clearly picked up by the measurements. Also reinforcement of sections can be detected, whereas only an overlay is not quite as apparent. These examples as well as knowledge from other measurements show that motorway constructions have SCI values less than 80 microns. The two-lane road used as example have typical values around 100–150 microns with maximum values of around 300 microns. This also makes sense knowing that motorways are constructed as much thicker structures than other roads. There is a shift in SCI300 values from year to year. These examples indicate that there is a bearing capacity decrease from year to year of around 5–10 microns. The temperature of the asphalt layer seems to have some influence on this, though. These findings needs to be confirmed with more data. The HSD measurements from 2005–2007 are now stored in databases that can be accessed by the Road Directorate’s Maintenance Unit. Presently data can be used to show relative changes in bearing capacity over the sections, and they can guide in pointing out where supplemental FWD measurements will be useful. Further investigations and research is needed to gain full benefit of the results from the HSD. The next steps for the Danish Road Institute will be to focus on: • Define limits that can divide representative sections into categories of poor, medium or good according to measured SCI300 and traffic level. This also allows for clear graphics on maps. • Optimizing the calibration method and procedure. • Investigate the influence of parameters as speed, the dynamic load, temperature of the asphalt layer and temperature of the measuring equipment. 449

REFERENCES Hildebrand, G. & Rasmussen, S., (2002), Development of a High Speed Deflectograph, Report 117, Danish Road Institute, Roskilde, Denmark. Krarup, J.A., Rasmussen, S., Aagaard, L. & Hjorth, P.G. (2006). Output from the Greenwood Traffic Speed Deflectometer. Proceedings of the 22nd ARRB Conference—Research into Practice, Canberra, 29 October–2 November 2006, Melbourne, ARRB Group.

450

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A method for benefiting pavement quality assurance measures related to roughness condition surveys C. Plati & A. Loizos National Technical University of Athens (NTUA), Athens, Greece

ABSTRACT: Nowadays, profile measurements are widely used either for the evaluation of initial smoothness or for monitoring the roughness of in service pavements. For both cases the adoption of roughness specifications or trigger values is always an issue as they influence the road life-cycle costs. In this paper, consideration is given to some of the available criteria in which roughness indices or methods, such the International Roughness Index (IRI) or the Power Spectral Density (PSD) analysis of a road profile or even the surface tolerance are used for roughness condition survey. The paper briefly describes the development of a method for establishing weighted trigger IRI in terms of roughness acceptance specifications based on some geometrical aspects of pavement surface, which are associated with PSD analysis results and surface tolerance. The related outcomes, which are based on in-situ measurements, benefit quality assurance measures related to pavement condition surveys. 1

INTRODUCTION

Structural capacity seems to be the major concern of many pavement engineers; however road users primarily judge the quality of a road pavement based on its roughness and/or ride quality. Pavement roughness is the principal measure of public satisfaction within a road system. It has been defined as the variation in surface elevation that induces vibrations in traversing vehicles. Earlier studies (Gillespie & Sayers 1983) have shown that rough roads lead to user discomfort, increased travel time due to lower speeds and higher vehicle operating cost. As such, road roughness is now widely recognized as one of the principal measures of pavement performance. Many pavement performance studies have been made based on this measure and with technical advances in automated data collection roughness measurement it has become an affordable and routine practice in many countries (AUSTROADS 2001). A number of computer-based analysis methods are available to “detect” roughness levels and problem areas in a pavement profile that may affect ride quality and vehicle operation. The application of computerized analysis methods to a surface profile has many advantages—the primary one being, highly repeatable and reproducible roughness results. However, the main problem or obstacle to profile analysis is actually obtaining the profile. The profile survey method used must be quick, economical, detailed and accurate. Pavement surface profiles comprised of elevation readings can be analyzed for roughness indices such as the IRI (International Roughness Index). IRI is a repeatable, stable measure of roughness and is considered to be a device-independent index. Also, IRI can be incorporated in the pavement design and life-cycle analysis. However, IRI cannot be used to detect the existence of repeated waves. Also it doesn’t address the discomfort associated with all the surface wavelengths (Sayers & Karamihas 1997). Mathematical representations of road profiles can also be used for the study of roughness. These types of analysis require a more thorough knowledge of the distribution of frequencies with accompanying amplitudes. One such approach used for road profiles, is the Power Spectral Density (PSD). The PSD is often approximated with a simple function, using only a few parameters. This PSD approximation can be used both as a concise description of the 451

road roughness level, and used either directly in vehicle dynamics or as a basis for road profile generation (Sun 2001). However, although PSD analysis provides a lot of information about the surface profile and is also superior in identifying repeated-wave problems, it cannot be used to evaluate the pavement roughness or to predict its performance. Also it cannot be incorporated in the pavement design or cycle-life analysis. Moreover a very strong criterion of the pavement condition evaluation is the surface tolerance. Surface tolerance is commonly used to evaluate the initial pavement smoothness; however it always remains an objective measure of pavement rideability as long as it performs. A straight-edge can be used to measure the vertical deviation from a moving, fixed-length plane (surface tolerance). The measured tolerances are then compared with a maximum allowable value. For instance, in Greece this value ranges between 3 to 5 mm for a fixed-length plane of 3 m. Areas with tolerance exceeding the allowable limit are identified and the appropriate remedial work is performed. Although this type of testing provides an objective measure of pavement surface condition, it is time consuming, insensitive to the ride quality felt by the road users and cannot address the roughness associated with wavelengths longer than the straight-edge base length. In any case a performance-based specification for new or in-service warranted pavements is always necessary in an effort to achieve ride quality assurance. The paper briefly describes the development of a method for establishing weighted trigger IRI in terms of roughness acceptance specifications based on some geometrical aspects of pavement surface. These aspects are associated with PSD analysis results and base-length straight-edge measures. The related outcomes, which are based on in-situ measurements, benefit quality assurance measures related to pavement condition surveys. 2

THE INTERNATIONAL ROUGHNESS INDEX

The International Roughness Index (IRI) is one of the most widely known and used measures as an acceptable standard for road profile measurements (Gillespie 1992). It summarizes the roughness qualities of roads that impact on vehicle response. It was designed to be standard scale on which road roughness information was to be reported. IRI calculation is based on the response of a generic automobile to the roughness of the road profile (ASTM 2005). The reference automobile is a dynamic quarter-car model, the so-called “Golden car” model (Fig. 1).

Figure 1.

Golden car model.

452

Table 1.

Golden car parameters.

Parameter

Value

Unit

ks/ms kt/ms cs/ms mu/ms

63.3 653 6 0.15

s−2 s−2 s−1 –

The “Golden car” is a theoretical model and has standard tire, suspension and damper properties. It is described by the vehicle sprung mass (vehicle body mass) (Ms), the suspension spring (ks), the suspension damper (Cs), the unsprung mass (mu) (axle mass) and the tire spring (kt). The values of these parameters, known as the Golden Car parameters, are given in Table 1. The model is driven over the measured pavement profile at a constant speed of 80 km/h and the vertical movements of the sprung and unsprung mass are calculated. IRI is determined as the summation of the vertical movements along a base length (mm/m or m/km) (CEN 2006). IRI can be expressed as a series of differential equations, which relate to the motions of a simulated quarter-car to the road profile. It is an accumulation of the motion between the sprung and unsprung masses in the quarter-car model, normalized by the length of the profile. Mathematically this can be expressed as follows (ASTM, 2005): IRI =

1 l

1/ s

∫ | Zs - Zu | dt

(1)

0

where IRI is expressed in m/km, l is the length of the profile in km, s is the simulated speed of 80 km/h, Zs is the time derivative of the height of the sprung mass and Zu is the time derivative of the height of the unsprung mass. IRI is used when it is desirable to correlate roughness with general vehicle operating costs, ride quality, dynamic wheel load and with general pavement surface conditions. An IRI value of 0.0 m/km means that the profile is perfectly flat or smooth. There is no theoretical upper limit to roughness, although a pavement with IRI values above 8.0 m/km corresponds to a practically impassable pavement, unless a vehicle is moving at very low speeds (Sayers & Karamihas 1997). The quarter car model theoretical response to the various sinusoids can be calculated as the ratio of the filtered to the unfiltered elevation of the pavement (output/input). The theoretical response of the quarter car model can be also described by equation (2) (Sun 2001). H s (ω ) =

− βω 2 ω 4 − i ( h α s + α s )ω 3 − ( βt + β s + h β s )ω 2 + iα s βtω + βt β s

(2)

where, h = ms/mt; αs = cs/ms; βs = ks/ms; βt = kt/mt i.e. h = 6.67; αs = 6 s−1; βs = 63.3 s−2; βt = 4353 s−2 and ω is the angular frequency (ω = 2πf ). In Figure 2 the theoretical response (gain) is plotted as a function of frequency. The theoretical response gain plot illustrates the influence of the different wavelengths on the IRI calculation. It seems that IRI is mainly affected by sinusoids with wavelengths raging between 1.2–30.0 m since they correspond to high gain values (gain > 0.5). The two peak values detected in the plot of Figure 2 reflect the resonant frequencies of the sprung (1–2 Hz) and unsprung mass (10–15 Hz) respectively (Gillespie 1992). In actual traffic conditions the speed of the vehicle is different to that of 80 km/h and at different speeds the wavelengths responsible for poor ride quality may change. An index such as IRI that is defined for a specific and constant speed cannot describe satisfactorily the pavement ride quality as it is perceived by road users for other vehicle speeds. Vehicle resonance 453

Figure 2.

Theoretical frequency response (gain) of the quarter car model.

is designed in a way that vehicle responses univocally to the numerous sinusoids of different wavelengths. The resonance of the vehicle parts has as a result that two roads which have the same IRI value but irregularities with different wavelengths, cause entirely different disturbances at speeds other than the reference speed of 80 km/h (SNRA 2000; Loizos & Plati 2008). Moreover an IRI value cannot express pavement surface profile properties that induce the surface irregularities. The IRI has been criticized because it is not the best index for quantifying specific road roughness qualities or does not conform to local preferences for a roughness index. However, it is a roughness measure of broadest utility because it encompasses all wavelengths significant to passenger vehicles. 3

PSD ROUGHNESS ANALYSIS

When considering road roughness, road profiles are analyzed in terms of how they can be constructed using sine or cosine waves. It is unusual to encounter a profile that closely resembles a sinusoid. However it is possible to construct a road profile mathematically by adding together a collection of different sinusoids. To improve detail and emulate the true profile closely, it is necessary to use many of these sinusoids with widely varying wavelengths (λ), amplitudes (A) and phases (X0) (Fig. 3). The equation of the sinusoid (Y) as a function of X is: ⎛ 2π ⎞ Y = A sin ⎜ (X − X 0 ) ⎟ λ ⎝ ⎠

(3)

The derivative of a sinusoid, as it is described by equation (3) gives the max slope (S) of the wave for the same wavelength (Eq. 4) S=

2π A λ

(4)

A typical sinusoid road profile encompasses a spectrum of sinusoidal wavelengths. The power spectral density (PSD) function (Eq. 5) is a statistical representation of the importance of the various wavelengths. PSD functions can provide roughness evaluators with a great deal of information regarding the shape of a pavement surface with the emphasis 454

Figure 3.

Sinusoid description.

PSD of slope (m/cycle)

1.00E-04

1.00E-05

1.00E-06

1.00E-07 1

0.1

10

100

wavelength (m) Left wheel path

Figure 4.

Right wheel path

PSD of slope.

being on longitudinal wavelengths particularly those wavelengths responsible for influencing roughness that lie between 0.5 and 50 meters (PIARC, 2002). Zk =

j = N −1

∑

Z je

−12π kj N

(5)

j =0

where k = 0, 1 …, N − 1 Zj: displacement at the sampling point j. PSD is the limiting mean-square value of a signal spectrum per unit bandwidth i.e. the limit of the mean square value in a rectangular bandwidth, divided by the bandwidth, as the bandwidth approaches zero (CEN 2006). For pavement roughness evaluation, the sinusoids can be plotted either as the PSD of elevation, slope or even vertical acceleration versus wavelength (or wave-number). The PSD of slope plots (Fig. 4) are commonly used as they offer a more direct view of the slope variance over pavement providing with more details (Mann et al. 1997). Besides, slope seems to be a more important parameter of pavement surface properties, than elevation since the latter is of less significance unless the corresponding wavelength is known. The area under the PSD curve can be used for the calculation of the Root Mean Square (RMS) of slope or elevation or even vertical acceleration. RMS quantifies the roughness properties. However, it cannot be a ride quality index, since it does not consider other parameters affecting the perceived roughness like vehicle speed and vehicle characteristics. Additionally, 455

it is dominated by the longer wavelengths within the band. But, the influence of this draw back can be limited if the PSD analysis is strictly applied only in the range of the roughness wavelengths i.e. 0.5 to 50 m. 4

METHOD DEVELOPMENT

4.1 The concept There are two main reasons for measuring “trueness” of a pavement surface. The first reason is to determine what people may feel as they travel over a pavement. The second is to determine the level of dynamic loading on the pavement from the heavy vehicles. Both of these items can be reduced to one fundamental property: vehicle vibrations. Since IRI is directly linked to vehicle vibration, it serves as a sound basis for pavement evaluation (Swan & Karamihas 2003). On the other hand IRI cannot provide adequate information about the pavement profile, as the PSD outputs do or it cannot pinpoint irregularities in the pavement surface, as the straight-edge measurements do. Given these obstacles, the thought is to develop a method for establishing trigger IRI values in terms of roughness acceptance specifications adopting some geometrical aspects that are provided by PSD analysis results and base-length straightedge measures. So, assuming that a pavement profile is a sinusoid curve with wavelength λ and amplitude A (Fig. 4), the surface tolerance can easily be measured using a straight-edge of a fixedlength of λ m. Then the maximum surface tolerance or in other words, the maximum vertical deviation (d) from the fixed-length plane will be equal to 2 A (Eq. 6). d=2⋅A

(6)

Based on Equations 4 and 6 the relation between the maximum surface tolerance and the maximum wave slope can be expressed as following: S=

π ⋅d λ

(7)

If we consider an acceptable maximum d value for the wave under investigation then equation (7) gives the maximum slope of the wave. In addition the slope variance over a pavement surface is provided by the PSD analysis approach. However the representative measure of the PSD results is the RMS of slope. For the purpose of the present study the RMS of slope of a pavement section is considered not exceed the maximum slope S. This consideration is the basis of developing trigger values for RMS. But how can these trigger values be related to the IRI? The definition of this relation was the motive for collecting and analyzing roughness data. 4.2 Data analysis In light of the above considerations, roughness data were collected using a laser profiler. The pavement test sections were of different ages in order to consider a range of different levels of roughness condition. Four clusters (1–4) of pavement were defined in terms of pavement age (Table 2). Each cluster included 40 highway pavement sections approximately of 200 m in length. Table 2.

Pavement sections clusters.

Cluster

1

2

3

4

Pavement age (years)

0–1

1–5

5–10

>10

456

Figure 5.

IRI versus RMS. Table 3.

IRI trigger values.

d (mm)

λ (m)

IRI (m/km)

3 5

4 3

1.51 2.95

The collected roughness data was processed and further analyzed. The analysis concerned the outer (right) wheel path profile data. The IRI values were calculated for all the pavement test sections. In addition for all the pavement test sections the PSD analysis was applied. With respect strictly to the roughness wavelengths (i.e. 0.5 to 50 m) the RMS of slope values were calculated. The RMS sample was correlated respectively to IRIs sample. Figure 5 illustrates the linear graph of the correlated data and the correlated factor (R2 = 0.84), while Equation 8 expresses the relation between the correlated parameters. IRI = 201.2 ⋅ RMS + 0.328

(8)

According to the regression analysis results (Table 3) the RMS values are well correlated to the IRI values for the wavelengths range under investigation i.e. 0.5–50 m. So, the developed equations could be used as transfer functions for the estimation of IRIs based on RMS values with respect to the roughness wavelengths. 4.3 Developed criteria The developed transfer functions (Equation 5, Table 3) can be used for the estimation of IRI trigger values. For instance certain Greek specifications applied for quality control of new roads define that if the surface tolerance measured with a fixed plane of 4 m is more than 3 mm, then penalties are levied against the constructor. In this case, the maximum slope S is estimated based on Equation 7 considering the wavelength of 3 m. As it has been defined that the RMS of slope must not exceed the maximum S value and given the aforementioned transfer functions, the IRI trigger value is calculated (Table 3). In the same way the IRI trigger value is calculated when a specification for the evaluation of in-service highway pavements defines that if the surface tolerance measured with a fixed plane of 3 m is more than 5 mm, and then road work must be carried out. Table 3 concerns some preliminary results of the developed method for establishing IRI trigger values in terms of acceptance roughness specifications. It is worthwhile to mention 457

that a basic parameter of the proposed procedure is the length of the test pavement section. The selected length of approximately 200 m could be considered more appropriate in terms of periodical monitoring of pavement rideability in a road network. However, shorter pavement length should be considered on a project level. 5

CONCLUSIONS

The proposed method described in the paper provides a methodology for developing acceptance roughness specifications. IRI serves as the basic index for establishing trigger values. It is admitted that although there are some constraints about the IRI’s suitability to express pavement roughness, it serves as a sound basis for pavement evaluation, as it is directly linked to vehicle vibration. The methodology also involves the PSD analysis approach, the geometry of the surface waves and the surface tolerance. The developed correlations between the involved parameters ends in the definition of IRI trigger values. However, it seems that the developed trigger values are related to the IRI reference length. The method was demonstrated as a way to specify overall ride quality with respect to measured surface irregularities. It can be further developed involving additional parameters such as the IRI’s reference length or travelling speed for benefiting better quality assurance measures related to pavement condition surveys. REFERENCES ASTM 2005. Standard practice for computing International Roughness Index of roads from longitudinal profile measurements. ASTM Standards 04.03, Road and Paving Materials; Vehicle-Pavement Systems, E1926-98. AUSTROADS 2001. Guidelines for road condition monitoring, Part I—Pavement roughness. Sydney: Australia. CEN 2006. Road and airfield surface characteristics—Test methods—Part 5: Determination of longitudinal unevenness indices (Draft). European Standards, prEN 13036-5. Gillespie, T.D. & Sayers, M.W. 1983. Measuring road roughness and its effects on user cost and comfort. ASTM Special Technical Publication 884. Gillespie, T.D. 1992. Everything You Always Wanted to Know about IRI, But You Afraid to Ask! Road Profile Users Group Meeting. Lincoln: Nebraska. Loizos, A. & Plati, C. 2008. An alternative approach to pavement roughness evaluation. International Journal of Pavement Engineering 9(1): 69–78. Mann, A.V., McManus, K.J. & Holden, J.C. 1997. Power spectral density analysis of road profiles for road defect assessment. Road & Transport Research 6(3): 36–47. PIARC 2002. International experiment to harmonize longitudinal and transverse profile measurement report procedure. Technical Report, PIARC Technical Committee on Surface Characteristics (C1). Sayers M W. & Karamihas, S.M. 1997. The little book of profiling. UMTRI. SNRA 2000. Whole body vibration when riding on rough roads. Road Engineering Division, National Road Management Division, Swedish National Road Administration. Sun, L. 2001. Developing spectrum-based models for international roughness index and present serviceability index. Journal of Transportation Engineering 127(6): 463–470. Swan, M. & Karamihas, S. 2003. Use of a ride quality index for construction quality control and acceptance specifications. Transportation Research Record 1861: 10–16.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Structural roadway assessment with frequency response function J.-M. Simonin & D. Lièvre Laboratoire Central des Ponts et Chaussées, Bouguenais, France

J.-C. Dargenton Centre d’Etude et de Construction de Prototype, Angers, France

ABSTRACT: A shock applied to a road structure generates different physical phenomena according to the characteristic of the shock (frequency, intensity). When the load is applied by a Falling Weight Deflectometer (FWD), static surface deflection of the roadway is measured. When the impact echo method is applied, compression waves propagate through the structure and the surface response is measured at a higher frequency. With an intermediate solicitation, the vibratory response on surface road can be measured and the Frequency Response Function (FRF) can be evaluated. This function is sensitive to the presence of internal damage such as voids or cracks. Sensitive frequency band depends on the investigated structure and also the type and the location of damages. To interpret the results, it is necessary to standardize them using a reference function. The paper presents the data processing principle, the statistical process to deduce the reference function which is representative of the healthy structure. It also presents the Colibri device which implements the method. Finally, the method performances are illustrated by several applications on test sites where internal damages are detected. 1

INTRODUCTION

The roadway structures are constituted of superimposed layers. Structural diagnosis needs to collect geometric and mechanic data relating to this structure. Radar and coring allow estimating layer thicknesses. Deflection basin, measured by a deflectograph or a FWD, allows to back-calculate the stiffness of each layer. The interface conditions are an important parameter. However any device gives information on interface bonding. Nevertheless, it is basic information to estimate the residual life and to define the rehabilitation solution. For instance, Ratanavong (2003) designed a structure including well bonded interface for a 20 years service life. A debonding interface between the base layer and sub-base layer reduced the service life to 5 years. In such a case, rehabilitation needs to mill up to the debonded interface. In addition to the measurement of the layer thicknesses, coring gives local interface conditions. However, these tests are slow and destructive. Dynamic investigation of the roadways is an alternative non-destructive technique. This pavement investigation technique began in the 1970’s in order to solve technical problem using the Goodman vibrator (Leger 1968). A homogeneous structure, far from the seismic source, is required to apply this wave propagation technique. To check this homogeneous characteristics, the technique of the “hammer and the hand” was applied. This one consisted in striking the road surface with a hammer (shock), and in subjectively evaluating the structure response by laying one hand close to the shock. This test was first automated by the “Collometre” (Guillemin 1975) which drops down a mass on the roadway and measured the maximum response of the roadway with a geophone (Fig. 1). The “Collographe” (Le Houedec et al. 1983) tried to ensure a continuous measurement. Unfortunately, the

459

Figure 1. The “Collometre” on the left (Guillemin 1975) and The “Collographe” on the right (Le Houedec 1983).

Figure 2.

Colibri prototype mounted behind a vehicle.

solicitation was mono-frequential sinusoidal with a too low frequency. This reduces the field of uses of this technique which has been finally abandoned. In 1991, Bats Villard returns to the original idea by applying a shock and by measuring the response with an accelerometer. Complete time signals were recording and several frequencies were analyzed by using a Fast Fourier Transform. A first prototype, called Colibri (Simonin & Maisonneuve 1998) has been developed and Simonin showed that the measurement principle was based on Eigen frequencies modification when an interface defect exists (Simonin 2005). Finally he proposes a methodology to analyze the results. 2

PRINCIPLE OF THE METHOD

Roadways constitute continuous structures on which the complex Frequency Response Function (FRF) can be measured. Thus, Colibri prototype applies a dynamic solicitation (shock) to the road surface and measures the vertical surface response (vertical acceleration) close to the solicitation. It deduces the inertance frequency response function ( A( f )) which is the ratio between a harmonic acceleration response and the harmonic force (Ewins 2000). It is calculated at each test point in a broad frequency range. 460

Figure 3. Shape of the first vibration mode; a healthy structure (1972 Hz), on the left; structure with a delaminated interface (123 Hz), on the right.

Figure 4.

Comparison of the inertance modulus estimated for a healthy and a delaminated structure.

For a healthy structure, the shock generates vibrations of the whole pavement. Frequency response will be amplified starting from the first Eigen frequency. Damages led to soften the structure, and thus to reduce the first Eigen frequency. Simonin (2005) studies a specific pavement structure: asphalt concrete layer (AC, 0.08 m thick) covering bitumen bound granular mixtures (BBGM, 0.15 m thick) and cement bound granular mixtures (CBGM, 0.21 m thick). The first Eigen frequency of a healthy structure is equal to 1972 Hz while an interface delamination reduces it to only 123 Hz (Fig. 3). This low frequency vibration mode corresponds to the vibration of a part of the structure (above the delamination). A lot of frequency vibrations exist for the delaminated structure in the frequency range (123–1972 Hz). The movement must be built by superposition of each vibration mode. FRF will be influenced by each Eigen frequency. Figure 4 presents the inertance modulus estimated for the healthy structure and the delaminated pavement. The second one combines the different vibration modes in the frequency range (0-1972 Hz). The FRF of the healthy structure is lower than the one of the delaminated structure. The difference is significant from around 100 Hz, a frequency a little lower than the first Eigen frequency of the delaminated structure, to 1950 Hz which is close to this 461

of the healthy structure. This sensitive frequency band, and particularly the lowest frequency, depends on the characteristics of the delamination (extension, depth, nature). 3

APPLICATION TO PAVEMENT INVESTIGATION

3.1 Measurement Dynamic investigation of pavement consists in collecting the inertance function all along a roadway section. Then, the process aims at comparing the FRF modulus by defining a reference FRF representative of the healthy structure and at identifying FRF which are significantly different from this reference function. It has to be noted that the reference function is related to the investigated roadway. So, we suppose that measurements are recorded on a homogeneous roadway (materials and layer thicknesses). The variations observed are quite representative of the presence of damages which lead to a softer structure. Dynamic investigation of a roadway consists in applying a mechanical dynamic solicitation on pavement surface, s(t), and measuring the surface response, x(t), at a fixed distance, d (Fig. 5). In practice, the applied solicitation is usually a shock which allows covering a broad frequency range with a short time solicitation. Vertical acceleration at surface road is measured to estimate the dynamic response of the pavement. Several tests are repeated on the same measurement point to improve the reliability of the frequency analysis results. A succession of test series are renewed as needed according to the section characteristics and the sounding objectives. 4

DATA PROCESSING ON EACH MEASUREMENT POINT

For each measurement point, i, a spectral analysis of the several tests leads to calculate the inertance, A( f , i ), and the coherence function, γ ( f , i ), between the pavement response and the applied solicitation. These functions depend on the frequency, f, and on the measurement point. The coherence function estimates the dependence of the output signal compared to the input signal. It is a real value ranging between 0 (no dependence) and 1 (full dependence). A minimum threshold of coherence (usually 0.8) is chosen to validate or not the calculation of the inertance. This threshold can be adapted according to the studies. For each frequency and each measurement point, FRF is validated if the coherence value is higher than this threshold. Thereafter, the analysis is restricted to the population of validated measurements.

Solicitation s(t)

Response x(t) d

Wearingcourse

Base

Sub-base Figure 5.

Dynamic investigation principle.

462

4.1 Data processing on a homogeneous zone On a homogeneous zone, data are processed in 2 steps: • Estimation of a reference function representative of the healthy structure; • Calculation of a normalized damage. 4.1.1 Calculation of the reference function representative of the healthy structure As mentioned early, we have to compare the FRF measured on each point to this of the healthy structure. Unfortunately, this reference function is usually unknown. The first step consists in building a reference function representative of the healthy structure. We know that this function corresponds to the low level of response (Fig. 4). To estimate the reference function modulus, we supposed that a part of the tests was carried out on a healthy zone. This could be done voluntarily by investigating an un-trafficked zone such as an emergency lane. In practice we usually consider the set of modulus, A( fk , i ) , measured at a fixed frequency, fk . The reference value at this frequency, | Aréf ( f )|, is defined as a percentile of selected population. We usually adopt the percentile 20 which allows obtaining a low value representative of the healthy structure and eliminating abnormal measurements. The set of reference values are used to build the reference transfer function representative of the healthy structure, | Aréf ( f )|. 4.1.2 Calculation of a normalized damage: Inertance modulus increases with frequency. We normalize the FRF modulus A( fk , i ) using the modulus of the reference function. For each frequency and each measurement point, we calculate the damage, D( fk , i ) according to the equation (1). This value is contained between 0 and 1. The matrix D represents the damage on the road section for the different frequencies. It can be presented as a damage mapping where: • X-coordinate is the abscissa along the road section; • Y-coordinate is the frequency band; • Colors represent the level of damage. ⎧0 si | A( fk , i ) | < | Aré f ( fk ) | ⎪ D( fk , i ) = ⎨ | Aré f ( fk ) | ⎪1 − | A( f , i ) | k ⎩

5

(1)

APPLICATION ON TEST SITES

5.1 Detection of interface defect A test site has been investigated using Colibri prototype. Its structure includes 4 layers: a 0.06 m thick AC wearing course, two 0.10 m thick BBGM layers and a 0.20 m thick layer of unbound granular mixtures (UGM). The structure includes 2 pieces of Kraft paper (0.5 × 0.5 m) which represent interface defects. One is placed at the AC/BBGM interface; the second is located at the interface between the 2 BBGM layers. Figure 6 presents the image applying the dynamic investigation method. The theoretical localization of the defects is indicated on the graph. Frequency band between 3000 and 5500 Hz is sensitive to the interface defects. The first one (nearer to surface), is easier to locate because the stiffness contrast between the healthy structure and the substructure located above the defect is high. Its localization is good. The deeper defect is less readable because the structure under the defect is soft. 5.2 Detection and evolution of reflective cracking Dynamic investigation is based on variations of the structure softness. Vertical cracks represent variations of limit conditions which reduce the Eigen frequencies. They also can be 463

1

7000 6000

0.8

3000

0.4

2000 1000 0

Figure 6.

BBGM kraft BBGM

AC kraft BBGM

0

0.5

1

1.5

0.2

2 2.5 Distance (m)

3

3.5

0

4

Damage image deduced from the dynamic investigation of a test site with interface defects.

1

7000

1

7000

0.9 6000

0.9 6000

0.6 4000 0.5 3000

0.4 0.3

2000

0.8 0.7

5000 Frequency (Hz)

0.7

Level of damage

0.8

5000 Frequency (Hz)

Level of damage

0.6

4000

0.6 4000 0.5 3000

0.4 0.3

2000

0.2 1000

0.2 1000

0.1 0

Level of damage

Frequency (Hz)

5000

-0.5

0 Distance (m)

0.5

0

0.1 0 -0.5

0 Distance (m)

0.5

0

Figure 7. Images of estimated damage over a crack between the wheel-path; before fatigue testing (on the left); after fatigue testing (on the right).

detected with dynamic investigation. We used the technique during an experiment which tests different technologies to limit reflective cracking. A concrete structure was sawed. Different anti reflective cracking processes were used before covering the structures with a 0.06 m thick AC wearing course. Pavement fatigue machines applied one million times a load above each crack. Load is a standard 65 kN dualwheel running at 2 m/s. Dynamic investigation has been conducted at the beginning and at the end of the experiment. It extended 0.5 m on each side of cracks in 3 longitudinal profiles: under each wheel path (noted north and south) and between the 2 wheels path (noted center). Intervals between consecutive measurements were only 0.02 m near a crack (<0.20 m) and 0.05 m at farther distance. Pavement sounding was held over one half-day under homogeneous and constant operating conditions. An unloaded zone has been investigated to evaluate the influence of climatic conditions on measurements. We independently processed each longitudinal profile and compared the reference functions. Results from the unloaded zone showed any influence of climatic conditions. On the other 464

1 North wheelpath (BFTE) South wheelpath (BFTE) Between wheelpath (BFTE) North wheelpath (AFTE) South wheelpath (AFTE) Between wheelpath (AFTE)

0.9 0.8 Average damage

0.7 0.6

BFTE: Before Fatigue Testing Experiment AFTE: After Fatigue Testing Experiment

0.5 0.4 0.3 0.2 0.1 0 -0.5

-0.4

-0.3

-0.2

-0.1

0 0.1 Distance (m)

0.2

0.3

0.4

0.5

Figure 8. Average damage in the frequency range 1500–5000 Hz estimated by Colibri on the various profiles before (initial) and after (final) fatigue testing; Reference technique.

1 0.9

Average damage

0.8 0.7

BFTE: Before Fatigue Testing Experiment AFTE: After Fatigue Testing Experiment

North wheelpath (BFTE) South wheelpath (BFTE) Between wheelpath (BFTE) North wheelpath (AFTE) South wheelpath (AFTE) Between wheelpath (AFTE)

0.6 0.5 0.4 0.3 0.2 0.1 0 -0.5

-0.4

-0.3

-0.2

-0.1

0 0.1 Distance (m)

0.2

0.3

0.4

0.5

Figure 9. Average damage in the frequency range 1500–5000 Hz estimated by Colibri on the various profiles before (initial) and after (final) fatigue testing; Alternative technique.

hand, we observed some differences on the reference functions deduced from 2 anti-reflective cracking techniques before fatigue testing. The stiffness of this component influenced the FRF measured. So we defined a reference function for each anti-reflective technique. Using the reference function, we calculated the damage matrix for each crack at the beginning and the end of the fatigue test. Figure 7 shows example of the images deduced from dynamic investigation before and after fatigue testing. Crack is located at the null abscissa. Its influence is readable before and after fatigue testing in a wide frequency range. Before fatigue testing, the crack influences the results at a distance lower than 0.2 m. During fatigue testing, the crack grows up through the anti-reflective system and through a part of the wearing course. That is why damage image after the fatigue testing is influenced in a longer zone. Then, we calculated a damage index for each measurement point. It was equal to the average of the individual damages estimated in the frequency range 1500–5000 Hz. Comparing damage indexes profiles is easier than comparing several images. Figures 8 and 9 present the 465

index variation along the 6 profiles for the reference construction technique (Fig. 8) and for an alternative construction technique (Fig. 9). Before fatigue testing small differences exist in the longitudinal profiles which correspond to transversal dispersion of the test site. Damage level increases up to 0.5 close to the crack. It influences dynamic results only at a short distance (0.2 m). After fatigue testing, the damage index increases. It is different under each wheel path and between the 2 wheels path. For the reference technique, the index grows up to 1 under the wheel paths while between the wheels path, it increases only up to 0.7. The index decreases to match the initial level at a distance of 0.3 to 0.4 m. For the alternative technique, the index increases up to 0.9 between the wheels path close to the crack. Under the wheel paths, the index is always higher than the initial level. Visual inspection in situ and destructive testing (Perez 2008) show us that the bond between asphalt wearing course and concrete failed under the wheel paths with the alternative technique while the interface was always bonded for the reference technique. Dynamic investigation gives us a non-destructive technique to follow up the spread of reflective cracking and the interface bonding. It also allows calculating an objective index to compare different rehabilitation techniques. 6

CONCLUSIONS

Dynamic investigation is a method to detect stiffness variation of structure. In the context, of pavement sounding, defect presences such as unbonded interface, delamination or inside cracking, reduces pavement stiffness. So, these inside damages can be detected with this method. To adapt the method, we define a data process to build a reference frequency response function representative of the healthy structure. Then, we use it to normalize individual results. We propose an imaging result presentation which could be used to locate the defect and to define the affected frequency range. Then, a synthetic index can be estimated which can be used to follow up the crack growing or the delamination extension by time or traffic. Colibri is a research prototype. Its efficiency is low (1 measurement point each 45 s) but it could easily be improved by using non-contact technologies. Current development project studies the opportunity to use them to convert the prototype into an operational device. REFERENCES Bats-Villard, M. 1991. Influence des défauts de liaison sur le dimensionnement et le comportement des chaussées. Thèse de doctorat. Nantes: Université. Ewins, D.-J. 2000. Modal testing: theory, practice and application. Second edition. Letchworth: Research studies press LTD. Guillemin, R. 1975. Le collomètre : Dispositif de détection des défauts au voisinage de l’interface béton bitumineux—assise traitée. Bulletin de Liaison des LPC. n°80: pp 19–21 Paris: LCPC. Le Houedec, D. Marchand, J-P. & Riou, Y. 1983. Approche théorique sur le comportement d’une chaussée soumise à l’action d’un appareil d’auscultation dynamique: Le collographe. Annales des Ponts et Chaussées. Vol 27: 25–38. Leger, Ph. 1968. Utilisation du vibreur Goodman en auscultation des chaussées. Bulletin de liaison spécial J. Paris: LCPC. Pérez, S. 2008. Approche expérimentale et numérique de la fissuration réflective des chaussées. Thèse de doctorat. Nantes: École centrale. Ratanavong, A. 2003. Influence des défauts d’interface sur la durée de vie des structures de chaussées mixtes. Rennes: INSA. Simonin, J.-M. 2005. Contribution à l’étude de l’auscultation des chaussées par méthode d’impact mécanique pour la détection et la caractérisation des défauts d’interface. Thèse de doctorat. Rennes: INSA. Simonin, J.-M. & Maisonneuve, P. 1998. Dynamic investigations in assessing the structural condition of pavements. Bearing Capacity of Roads and Airfiels. Proc. Intern. Conf., Trondheim, 6–8 July 1998. Vol. 1: 187–196. Trondheim: Norwegian University of Science and Technology.

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Deflection measurement: The need of a continuous and full view approach J.-M. Simonin & L.-M. Cottineau Laboratoire Central des Ponts et Chaussées, Bouguenais, France

V. Muzet, C. Heinkele & Y. Guillard Laboratoire Régional des Ponts et Chaussées, Strasbourg, France

ABSTRACT: Road pavement bearing capacity is a crucial point for road maintenance and rehabilitation. Maximum deflection is usually measured discontinuously by mechanical sensors at low speed which implies safety problems. Pavement simulations showed that some parameters describing the deflection basin are more sensitive to pavement damages (cracking or delamination) than the maximum deflection. A direct measurement of surface deflection could be very useful to estimate such parameters. A new measurement system based on an imaging technology is presented. It consists in the projection of a structured pattern on the road surface A camera analyses the pattern deformation, which allows for measuring a surface deflection. The technique has been laboratory qualified in order to measure shapes, displacements and slopes on a road. A first experiment was carried out with a static system on the LCPC test track. The imaging technique was able to measure a surface deflection with satisfactory metrological performance. 1

INTRODUCTION

Deflection measurement is a first element in evaluating roads bearing capacity. Operational devices measure deflection at different distances of a falling or rolling load. This deflection basin is only representative of the neighborhood of the measurement point. It is usually used to estimate the pavement residual life. However, measurements level can quickly change along a roadway. This is well known on concrete pavement by measuring load transfer efficiency at joints (Chen, 2008). This implies a positioning of the measurement system close to the joint. This is not possible when a continuous wearing course covers the concrete layer. Moreover, others internal defects (like delaminations) affect roadways bearing capacity and need to be detected in order to optimize rehabilitation design. There is a need to develop a device that can rapidly provide continuous measurement of deflection basin to estimate either load transfer efficiency or to detect isolated defects. Several continuous prototypes are currently under development. These prototypes measure responses to the rolling load with lasers (Briggs, 1999, Andren, 1999, Rasmussen, 2002, Simonin, 2005) or with a rolling geophone system (Bay, 1998). In the first case, only punctual information on the deflection basin is delivered. This could make fail the estimation of parameters such as load transfer efficiency. In the second case, the speed of the system will be limited to maintain the contact between the road surface and the measurement system. This paper is divided into two parts. The first part presents some results about a numerical study on the variation of deflection basin. After a sensitivity study of viscoelasticity, two cases of road failure have been studied: a delamination and a vertical crack. In the second part, the imaging technique is presented and is applied to the deflection basin measurement.

467

2

NUMERICAL STUDY

A composite pavement which can be affected by horizontal defects (delamination) or vertical transverse cracks is considered. This structure includes bituminous mixtures, which can have a visco-elastic behavior (Huet, 1963). The estimation of the sensitivity of such a structure to viscoelasticity, delamination and cracking has been carried on. 2.1 Description of the pavement The structure consists in an asphalt concrete (AC) wearing course (0.08 m; 5400 MPa), a road base of bituminous bound granular mixtures (BBGM; 0.15 m; 9300 MPa) over a sub-base of cement bound granular mixtures (CBGM; 0.21 m; 23,000 MPa). The structure lays on an infinite pavement foundation of unbound mixtures (UM; 50 MPa). Two damage modes can be found: Transversal cracking of the sub-base can progress through the bituminous layers. Fine cracks can be observed at the surface. These roads need a maintenance in order to avoid an acceleration of the deterioration process due to water infiltration. The bonding between BBGM and CBGM may fail in some places. This leads to a large increase in tensile stresses in the base BBGM, which may in turn fail due to fatigue. Such a roadway is designed to support 20 years medium traffic according to the French design manual for pavement structures (Corté, 1997). On opening to traffic, layers are bonded. The sub-base layer is subject to most stress and becomes damaged by fatigue. Sliding takes place at the interface between base and sub-base layers. With the assumption of an initial bond failure interface, the roadway lifetime is reduced to only 5 years (Ratanavong, 2003). Numerical models use 3D finite elements to include either a 1 meter long delamination or a 1 mm vertical crack in the sub-base layer and optionally in the base layer. Generalized Coulomb friction models the delamination. A small void (1 mm thick) models the vertical crack. We also estimate the visco-elastic effect on a healthy structure. 2.2 Sensitivity to viscosity A Huet Sayegh model (Duhamel, 2003) was used for the 2 bituminous layers with a homogeneous temperature (0–30°C). An equivalent to the French standard dual-wheel is running on the structure at constant speed (0.1–40 m/s). This load is centered at the null abscissa. The deflection basin is observed in the center of the dual wheel. Figure 2 gives the deflection basins calculated in the elastic case and in two different viscoelastic cases. They vary with temperature and speed in the two last cases. The deflection basins are not symmetric for the visco-elastic cases. So the maximum deflection is not centered under the load and the distance of this maximum varies with measuring conditions.

Asphalt concrete (0.08m, 5400MPa) Bituminous Bound Granular Mixtures (0.15m , 9300MPa) Interface delamination

Cement Bound Granular Mixtures (0.23m; 23,000MPa)

Vertical crack Step 1

Unbound Mixtures (50 MPa)

Step 2

Figure 1. Description of the structure. Left: thickness and elastic modulus. Right: position of the different defects.

468

Other derivative parameters like radius of curvature or slope of the deflection basin at a fixed distance (of the load or of the maximum) also vary with measuring conditions. We estimate parameters deduced from the deflection basin such as the maximum deflection or the radius of curvature calculated in a 0.20 m long windows centered on the maximum value. Figure 3 presents an evolution of these parameters according to the loading speed at different temperatures. We observe that the maximum deflection decreases when the speed increases at a fixed temperature. For a speed higher than 5 m/s, the variations are reduced. We also note that the maximum deflection significantly varies with temperature. Variations of curvature radius are also significant for low speed and with temperature variation. 2.3 Sensitivity to delamination A 3D finite elements modeling has been used to include a delamination between the CBGM sub-base and the BBGM base (Savuth, 2006). A generalized Coulomb friction models the delamination. Figure 4 presents the deflection basins deduced for different delamination lengths (2a). The load is centered in the middle of the delamination. So deflection basins are symmetric. On the right, we observe a 1 m length zone where the form of the deflection basin varies with the delamination length. 220 240

Deflection (μm)

260 280

Elastic Viscous-elastic (T = 10°C, S = 20 m/s) Viscous-elastic (T = 20°C, S = 2 m/s)

300 320 340 360 -0.5

-0.4

-0.3

-0.2

-0.1

0 Distance(m)

0.1

0.2

0.3

0.4

0.5

Figure 2. Comparison between different deflection basins according to the bituminous materials behavior and the load conditions. 7000 0 °C 10 °C 20 °C 30 °C

400

Radius of curvature (m)

Maximum deflection (μm)

450

350 300 250 200

0

5

10 15 Speed (m/s)

6000 5000 4000 3000

1000

20

0 °C 10 °C 20 °C 30 °C

2000

0

5

10 15 Speed (m/s)

20

Figure 3. Parameters extracted from the deflection basin according to the running speed for different temperatures. Left: variation of the maximum deflection. Right: variation of the radius of curvature.

469

Figure 4. Comparison between different deflection basins according to the delamination length (Savuth, 2006).

Figure 5. Values of the radius of curvature under the center of a moving load on a structure presenting a 2 m delamination zone (Savuth, 2006).

Savuth models the effect of a standard dual-wheel running on this structure. He deduced from the successive deflection basins the evolution of several parameters such as maximum deflection, radius of curvature under the center of the load and slope of the deflection basin at a fixed distance of the load. Figure 5 illustrates on a structure presenting a 2 meter delamination zone, the variation of curvature radius of the deflection basin under the center of a moving load. The radius of curvature is reduced by 35 percent when the load is over the delamination, which allows to detect it. A continuous measurement of this parameter allows to define the limits of the delaminated area. He also shows that the maximum deflection increases around 15 percent and the slope at 0.30 m in front of the load increases up to 150 percent according to the friction conditions. 470

0

-140 Crack only in sub-base Crack in sub-base and base

Distance load - crack 0.1 m Distance load - crack 1 m Distance load - crack 2 m

-150

-50

Deflection (μm)

Deflection (μm)

-160 -100

-150

-170 -180 -190 -200

-200 -210 -250 -4

-3

-2 -1 0 Crack distance (m)

1

-220 -1

2

-0.5

0 Load distance (m)

0.5

1

Figure 6. The deflection basins calculated close to the crack for different position of the load. Right: according to the crack position. Left: according to the load position.

Maximum deflexion growth (%)

20 Crack only in sub-base Crack in sub-base and base

15

10

5

0 -2 Figure 7.

-1.5 -1 -0.5 [Crack - Load center] distance (m)

0

Variation of maximum deflection according to the distance between crack and load center.

This parameter could be more significant to detect delamination if we are able to measure it accurately. 2.4 Sensitivity to vertical cracking Another 3D finite elements modeling has been used to include a vertical crack 1 mm width in the CBGM and optionally in the BBGM. A standard dual-wheel was applied at different distances of this crack. Figure 6 shows the deflection basins. On the left, 6 cases are presented: the load center is located at 2, 1 and 0.1 m of the crack; Crack crosses only through the CBGM (solid line) or crosses trough CBGM and BBGM (dotted line). On the right, crack crosses the 2 layers; the graph compares the deflection basin for different distances between load and crack (2 m, 1 m and 0.1 m). For a given load position, deflection basins are similar. On the right, we clearly distinguish the deflection basin. A continuous measurement could be used to detect cracks. Figure 7 presents variation of the maximum deflection according to the distance between load and crack. It increases when the distance is smaller than 1 m. For a 10 percent growth of deflection, the distance crack load has to be smaller than 0.2 m which represents a continuous measurement. The difference between a partial crack and a complete crack is less than 5 percent (<10 μm). It will be difficult to detect crack severity using the maximum deflection. 471

2.5 Conclusion Deflection basin is sensitive to local damages such as delamination or vertical cracking. There are several situations where maximum deflection is not sufficient to describe road’s failures or detect damages. Moreover, the maximum deflection could be different due to visco-elastic effect. However other indicators like the curvature radius at the maximum deflection and the slope at a short distance of this maximum, seem to be more sensitive to internal damages. To measure such parameters, a large area of the deflection basin shall be measured by a full view approach, which contains more information than a scalar value. Such measurements are not reachable with classical mechanical sensors. However, a contactless imaging method allows for a full view and continuous measurement of deflection basin. This will give access to other parameters, which are more sensible to structural defect as shown before. The feasibility of a technique of fringe projection is presented hereafter. 3

FULL VIEW DEFLECTION MEASUREMENT WITH THE FRINGE PROJECTION METHODOLOGY

3.1 Basic principle of the fringe projection method Measurement of shape from structured light is based on triangulation. Contrary to ‘Moiré’ methodology, where the interference of two gratings is studied, the technique of fringe projection uses the projection of only one light pattern (line, grid, fringes or more complex pattern) onto an object. This object is observed with a camera from a different viewpoint, making an angle α with the projection direction. Under these conditions of lighting and observation, the resulting distortion of the projected pattern is directly related to the object shape: the height increment Δh is expressed by: Δh = Δp/tan α

(1)

where ΔP = pp – pa is the difference between the period pp of the fringes projected on a planar surface and the apparent period pa of the fringes projected on the object and α is the angle between the incidence of light and the observation directions (Fig. 8). When projecting sinusoidal fringes, the light intensity recorded at each point (x,y) is : I ( x, y ) = I 0 ( x, y ) ⋅ (1 + m( x, y ) ⋅ cos ϕ ( x, y ))

(2)

where I0(x,y) = mean intensity; m(x,y) = fringe contrast; and ϕ(x,y) = optical phase. The physical quantity containing the height information for each pixel of the image is the phase. To compute the displacement of an object like a pavement road deflection, at least two images are considered. The first image is taken on a reference plane or state, providing a reference phase map, ϕref. The second image is taken on the object and the phase ϕobject is Projector Camera

projected fringes

observation direction

incidence of light pa

observation direction p Object Face sight

Top sight

Figure 8.

Principle of the fringe projection method.

472

α Δh

z

x

pp

computed. Since the phase varies linearly from 0 to 2π in one period p, it is straightforward to show, that the height difference, Δz(x,y) is linearly related to the phase difference Δϕ(x,y): Δz = S × Δϕ ,

where S =

P Pa = 2π × sin(α ) 2π × tan(α )

and Δϕ = ϕobject − ϕreference .

(3)

3.2 From phase difference to deflection measurement There are different methodologies to calculate the phase like phase shift (Creath 1985), Fourier transform (Takeda 1985) and wavelet transform (Torrence 1998, Dursun 2004). The use of a wavelet analysis was appropriate in our case because the phase can be computed with a single image. Moreover, since the period of the fringes changes because of the angle of projection, the use of a space-frequency methodology is recommended. We used a 2D wavelet: a Morlet wavelet in the axis perpendicular to the projected fringes and a gaussian one in the axis parallel to the fringes. Such a wavelet constitutes an adaptable frequency filter in one direction and an average filter in the other. The phasis is extracted from the wavelet transform of the signal. Previously, we showed that the height difference Δz(x,y) is linearly dependent of the phase difference Δϕ(x,y) (eq. 3). In practice, an offset can be introduced to account for small variations to the model. In that case, the actual relationship between phase difference and height for each pixel position becomes: Δz ( x, y ) = K ( x, y ) ⋅ Δϕ ( x, y ) + Offset( x, y )

(4)

where K and Offset are determined by regression during calibration. The calibration procedure consists in applying a known translation to a plane object and to calculate the phase maps from which the parameters are deduced. The relation between Δϕ and Δz is better approximated by a three-order regression for bigger displacements. On a classical pavement, the maximum deflection is generally less than 1 mm. But due to the truck vibrations and the structure of the pavement (slab rocking for example) a deflectometer shall be able to measure small displacements for a few centimeter range. An experiment was conducted in laboratory to qualify our methodology. 3.3 Qualification of the methodology in laboratory The measurement accuracy was evaluated in laboratory conditions. A plane surface was translated with a motorized table. The experimental set up is presented on the left of the figure 9. Several millimeter displacements Z were applied (Z = 0, ±1, ±2, ±4, ±10, ±15, ±20 mm). Around each Z displacement, several micrometric displacements were applied (δz = ±10, ±50 and ±100 μm). Surface positive sense Camera

Projector

z

Z+δz Z=0 Reference position

Figure 9. On the left: experimental setup; On the right: results of measured micrometric displacements δzm (left axis) compared to the imposed micrometric displacement (right axis) for different millimeter position (X axis).

473

For each position Z + δz, an image was recorded and treated by comparison with the reference calibration image. The measured displacements are Zm and δzm. The results are presented on the right of the figure 9. The error between the calculated displacements (left axis) and the imposed displacement (right axis) is in any case less than 20 μm in a range of 4 cm. The obtained static accuracy is appropriate for our application (Malek 2006). 3.4 Experiment on a pavement fatigue carrousel The experiment was conducted on the pavement fatigue carrousel of the Nantes LCPC (Fig. 10 left). The LCPC pavement fatigue carrousel is an accelerated pavement test facility for the study of full-scale experimental pavements submitted to heavy traffic levels. The sensor was located on a 2.5 m arm to have a fixation independent from the loading. A picture of our sensor is presented on the middle of figure 10. An image taken by the camera with the projected grating is on the right of figure 10. A reference image was taken at a non loaded state. The images size is 20 × 27 cm2 and the shape of the transversal deflection is studied at about 60 to 90 cm from the maximal loading. Images were recorded at 10 Hz with the camera when the carrousel was operating at about 4.3 km/h. For each acquisition, the displacement of the observed area is computed by comparison with the reference image and the mean displacement is calculated as exposed in sections 3.1 and 3.2. To study the reproducibility of the experiment, different passages of the carrousel arm were compared (Fig. 11, on the left). The difference was less than 20 μm, which corresponds to the background noise of the system, which was about 10 μm in this experiment. The right of figure 11 is a complete displacement map at the maximum deflection. The acquisition has been made when the loaded wheel is the closest to the sensor. This image pixels shows the interest of a full view approach by displaying the state of the structure upon a surface. projector camera wheel track

Figure 10. Picture of an arm of the pavement fatigue carrousel (left). Picture of the sensor (middle). Fringe projection on the analysed area (right).

Comparison of two mean displacements 20 0

μm

0 20

Displacement in μm

-20

40 -50 60

-40

80

-60 100

-80

-100

120

140

-100

100

-120

0

50

100

Measurement Number

200

300

400

500

600

700

800

-150

image pixels

15

time

Figure 11. Left: Mean image displacement in μm for two rotations of the carrousel arm. The first passage is in black and the second passage in dashed grey. Right: Image displacement corresponding to the maximal displacement (maximal load). The scale in grey level represents the deflection in μm. The load is on the right side of the image pixels.

474

Wheels

Transversal profile 0

-20

Typical transversal deflexion curve Micrometer

-40

-60

-80

-100

-120

Observed area

-140

0

100

200

300

400

500

600

700

800

900

Pixels

Figure 12. Left: Localisation of the observed area compared to the transversal deflection curve. Right: Example of transversal profile (rough data in dashed grey and fitted data in black).

μm

time

Image number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

0

-50

-100

-150

Figure 13. Successive images of displacements taken at 10 Hz during the passage of the carrousel arm. The scale in grey level represents the deflection in μm. The load is on the right side.

An example of transversal deflection profile is presented on the right of the figure 12. The shape of the profile could be surprising compared to classical results. This is due to the localisation of the observed area, which is at more than 60 cm from the wheel axis (Fig. 12, left). A measurement was made at 65 cm of the wheel axis with a Benkelman beam and the result (120 μm) is in accordance with our methodology. With our full view approach, it is possible to follow on the observed area the evolution of the transversal deflection during the loading passage. Figure 13 presents successive images of displacements during the passage of one loaded arm at 4.3 km/h. When there is no loading, the image of displacement is uniform and close to zero, as it is for the images 1 to 3 before the loading and 17 to 18 after the loading. The maximal deflection corresponds to images 9 to 11 and to the maximal slopes. 3.5 Conclusions Our first tests have shown that deflection can be measured with a good accuracy in laboratory and with a good reproducibility. 475

The use of a vision technology like fringe projection enables a continuous and full view approach. Different information could be extracted from the images of displacements like the slope at different distance from the loading and the radius of curvature. These parameters are precisely the ones presented in the first part, which shows the pertinence of the imaging technique. 4

CONCLUSIONS

Deflection basin is sensitive to damages and pavement viscosity. The level of maximum deflection is thus modified, but its distance to the applied load is also influenced. Other parameters, such as the curvature radius at the maximum or the slope at a fixed distance from the maximum, seem to be more sensitive to damage than to measuring conditions. To detect, locate and identify such damages, the deflection basin has to be measured in a continuous way. Based on imaging methodology, a new way to measure the deflection area has been explored. First applications show interesting results, which validate the choice of measuring deflection basin with fringe projection. However, this technique needs to be improved in order to obtain an operational device. An ongoing project aims to concept a support beam to mount the system on a heavy truck. With the use of fast camera, it will be possible to measure deflection basin in a continuous way and to compute parameters more sensitive to internal damage. REFERENCES Andren, P. 1999. High-speed rolling deflectometer data evaluation, Non-destructive Evaluation of Aging Aircraft, Airports and Aerospace Hardware III 3586: 137–147. SPIE The International Society for Optical Engineering. Bay, J.A. & Stokoe II, K.H. 1998. Development of a Rolling Dynamic Deflectometer for continuous Deflection testing of Pavement. Publication FJWA/TX-99/1422-3F FHWA/Texas Department of Transportation. Briggs, R.C., Johnson, R.F., Stubstad, R.N.L. & Pierce, L. 1999. A comparison of the Rolling Weight Deflectometer with the Falling Weight Deflectometer, Nondestructive Testing of Pavements and Backcalculation of Moduli. ASTM conference, Seattle. Chen, D.H., Nam, B.H. & Stokoe II, K.H. 2008. Application of the rolling dynamic deflectometer to forensic studies and pavement rehabilitation projects, TRB Washington, D.C. 17. Corté, J.-F. & Goux, M.-T. 1997. French design manual for pavement structures. Technical guide LCPC Paris France. Creath, K. 1985. Phase shifting speckle interferometry. Applied Optics 24 (18): 3053–3058. Duhamel, D., Nguyen, V. H., Chabot, A. & Tamagny, P. 2003. Modelling of multilayer viscoelastic road structures under moving loads. Proc. International Conference on Civil and Structural Engineering Computing, Amsterdam, Netherlands. Dursun, A., Ozder, S. & Ecevit, F.N. 2004. Continuous wavelet transform analysis of projected fringe patterns. Measurement Science and Technology. 15: 1768–1772. Huet, C. 1963. Etude par une méthode d’impédance du comportement viscoélastique des matériaux hydrocarbonés. Thèse de doctorat, Faculté des sciences, Paris, France. Malek, M., Muzet, V. & Guillard, Y. 2006. Utilisation de la transformation en Ondelettes pour la mesure de déplacements par projection de lumière structurée. Communication aux Journées Scientifiques de l’Ingénieur, Marne la Vallée, 5–6 dec 2006. Rasmussen, S., Krarup, J.A. & Hildebrand, G. 2002. Non-contact Deflection Measurement at High Speed. Bearing Capacity of Roads, Railways and Airfields, Balkema, 53–60. Ratanavong, A. 2003. Influence des défauts d’interface sur la durée de vie des structures de chausses mixtes, MS, Insa de Rennes, France. Savuth, C. 2006. Contribution à l’auscultation structurelle des chausses mixtes: detection des défauts d’interface à l’aide de la déflexion, Thèse de doctorat, INSA de Rennes, France. Simonin, J.-M., Rasmussen, S. & Hildebrand, H. 2005. Assessment of the Danish High Speed Deflectograph in France; Proc. 7th international conference on the bearing capacity of roads, railways and airfields, Trondheim; Norway; June 2005, 10. Takeda, M. & Mutoh, K. 1983. Fourier transform profilometry for the automatic measurement of 3D object shapes. Applied optic. 22 (24): 3977–3982. Torrence, C. & Compo, G.P. 1998. A practical guide to Wavelet analysis. Bulletin of the American Meteorological Society, 79: 61–78.

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Modeling & methods of functional testing

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Laboratory characterization of half-warm mix asphalts with high recycling rate by means of the factorial experiment design approach F. Olard & E. Beduneau Research & Development Department, EIFFAGE Travaux Publics, France

D. Bonneau, S. Dupriet & N. Seignez Ciry Central Laboratory, EIFFAGE Travaux Publics, France

ABSTRACT: In-plant reclaiming at strong rate is more and more often used. Nowadays, some asphalt plants enable a 70% recycling rate whatever the production temperature (hot-mix or warm-mix asphalt). This study aimed at determining the influence of the mix composition on the performantial properties of half-warm mix asphalts, produced in laboratory at approximately 95°C following the innovative proprietary low energy asphalt technique labeled LEA®. By means of the factorial experiment design approach, this study highlights the influence of the bitumen pen grade (10/20, 35/50 and 50/70), the RAP content (30%, 50% and 70%) and the vegetable additive content used in the LEA process (0.2%, 0.6% and 1%). Many laboratory tests were conducted, including the French gyratory shear compacting press, the Duriez test (evaluation of water resistance) and the stiffness modulus. This laboratory characterization shows that very high recycling rates (from 30% to 70%) can be used in half-warm mix asphalts. 1

INTRODUCTION

With the threat of oil shortage and price increase, the lack of good quality aggregates, and the general conscience on environmental issues, both low-energy asphalt production and recycling of asphalt pavement are getting more and more attention. As regards the low-energy solutions, they are categorized in warm and half-warm, depending on whether their production temperature is above or below 100°C. This paper focuses on the recent LEA® half-warm technique which is currently used on almost 40 plants mainly in Europe (Romier 2004, 2006, Olard 2007a, 2007b, 2007c, 2008, Prowell 2007, Sauzeat 2008) and the USA (Harder 2007). 250,000 tons have been realized over the past few years, demonstrating the feasibility of lowering the operating temperatures, the energy consumption and the fumes emissions (Gaudefroy 2008). More details on this technology are given in section 2. Insofar as recycling is concerned, a tremendous number of publications can be found on the effect of RAP (Reclaimed Asphalt Pavement) content on the mechanical performances of asphalt mixtures (e.g. Bonaquist 2007, Li 2008). However, the maximum RAP percentage is generally between 30% and 50% according to the considered asphalt plant equipment limitations and to the national specifications. This study focused on using a higher than usually used percentage of RAP –up to 70%– in a typical base course asphalt. Background of the recycling in Europe in particular is briefly given in section 3. 2

DESCRIPTION OF THE INNOVATIVE LEA® HALF-WARM MIX PROCESS

The originality of the LEA process lies in the ability of hot anhydric bitumen to foam or to emulsify when in contact with the residual aggregate moisture just below the water vaporization point at 100°C, therefore allowing coating at lower temperatures. Owing to the 479

Figure 1.

Three main sequential LEA® methods (Olard 2007a, 2007c).

Figure 2.

Binder expansion in a lab mixer (Olard 2007a, 2007b, 2007c).

dispersed water (liquid or steam) inside bitumen, the spontaneous volume expansion of bitumen (see Figure 2) leads to a thicker binder film around aggregate (from the mixing and coating stage in plant to the paving and compaction stage at job site); it thus fosters good mix workability. Some specific additives may be used to improve the foaming and coating ability of the binder. As displayed in Figures 1 & 2, different possible sequential drying and coating processes can be used in relation to the mix formula and to the asphalt plant configuration: – LEA 1: the drying stage only affects a first part of the aggregates, then coated by the whole bitumen. The remaining cold and wet part is then added. All the constitutive elements of the mix are then mixed, or – LEA 2: the drying stage only affects a first part of the aggregates, which is then mixed, before the coating stage, to the remaining moist part, or – LEA 3: all the aggregates are partially dried, then coated by the hot bitumen. 3

SOME KEY FIGURES ABOUT ASPHALT RECYCLING IN EUROPE

Recycling of asphalt pavement is getting more and more attention (EAPA 2005). Table 1 which is drawn from a recent European survey on the use of RAP, reports on the techniques used, 480

Table 1.

Recycling techniques, mainly hot technique (Planche 2008).

Country

Max %RAP in base/binder course

Max %RAP in wearing course

Cold technique

Belgium

50% binder coming from RAP if homogeneous RAP; 20% binder coming from RAP if heterogeneous RAP

Czech Republic

25–40% when fresh binder pen 30–70; 60% for softer grade

No

Foamed bitumen; Emulsions & Cement

France

15% with no testing; 30% in drum dryers; 50% in double drums

10% max (no testing)

Emulsions

Germany

20% in binder course; Up to 100% in base

20%

Emulsions or foams; Recommended for tar contaminated RAP

Italy

Never above 50%; Usually below 30%

No, except for special courses (<20%)

Emulsions or foams; Higher % RAP allowed

Netherlands

50%

50% in some cases

No

Denmark

5 to 10% with no testing

Spain

5 to 10% with no testing; 10 to 50% on layers <15 cm

5 to 10% (no testing)

Emulsions; 100% RAP allowed in base courses (only if RAP made of more than 90% bituminous materials)

Switzerland

70% in sub-base; 60% in base layer; 30% in binder course

30% in surface layer for secondary roads

Slowly increasing; Foamed bitumen

United Kingdom

10% with no testing; 50% permitted with testing

10% with no testing

Foam with cement/lime as adhesion agent; 100% max in base

giving the maximum RAP content authorized, according to the related layer in the new pavement, and to the technique used for mixing with fresh materials (Planche 2008). In fact, these values are based upon field experience of the performance of asphalt pavements built with RAP. Yet, there is little to no information available about the effect of such high RAP contents on the mechanical properties of the resulting mixtures. Thus, it becomes an important priority to study the effects various types and percentages of RAP have on mixture properties. 4

SPECIFIC PLANT FOR VERY HIGH-RATE RECYCLING (>50%)

One concern about recycled mixes is that it is not clear whether adequate mixing of the RAP and new materials occurs in all the cases. We do think that when mixtures with high RAP content lack cohesion and fail in a short period of time, most of these cases involve the use of unprocessed RAP and hot-mix plants that were not designed to handle high RAP content. That is the reason why, this section describes the in-plant HMA recycling by using the specifically developed mobile parallel drum plant of EIFFAGE TP allowing high rate recycling up to 100%. Since the 1980s, the parallel drum batch plants have been widespread first in Germany and afterwards in Nordic countries. This concept was developed specifically for high rate recycling up to 60%. Since 2004, the EIFFAGE TP group has decided to develop its own concept of parallel drum mix plants working on the continuous principle, specifically for high rate recycling up to 100%. The production output of this hypermobile plant—manufactured by BENNINGHOVEN Gmbh—is around 400 tons per hour; very few dust fumes and VOCs (Volatile Organic Compounds) are produced. The virgin aggregates are heated at about 200–250°C in 481

a)

Cold feed bins

200–250°C Drying drum for virgin aggregates

Cold feed bins

Bitumen + additive

Pugmill 110–150°C

Possible addition of water for LEA®

‘Warming’ drum for RAP

b)

Figure 3. Mobile parallel drum plant of APPIA Grands Travaux (EIFFAGE TP group): a) overall view & b) view of the two parallel drum dryers (the 1st one for virgin aggregates, the 2nd one for RAP).

a first drum dryer, whereas the RAP aggregates are warmed at about 110–150°C in a second parallel drum dryer, and afterwards both the virgin and the recycled aggregates are introduced in a continuous pugmill in order to being mixed and coated with hot bitumen. Figure 3 illustrates this new kind of plants: the aged binder of the RAP can be recovered and blended with the neat binder thanks to the warming at about 110–150°C in the second parallel drum dryer and then to the strong mixing with virgin materials in the continuous pugmill. Such very high RAP contents (>50%) can be successfully used only thanks to this specific mobile parallel drum plant allowing both hot and warm recycling. As the evaluation of the effect of the RAP content along with the production temperature on the mix performances is of the utmost importance, a dedicated laboratory study with very high RAP contents is presented hereafter. 5

OBJECTIVES OF THE STUDY

The study presented herein, carried out at the EIFFAGE TP research centre in Ciry-Salsogne (France), aimed at determining the influence of the RAP content (%), the fresh binder penetration (1/10 mm) and the vegetable additive content (%) on the mechanical properties of the half-warm mix asphalt LEA, compared to the traditional HMA acting as a reference material. Many tests were conducted including the French gyratory shear compacting press, the Duriez test (evaluation of the water resistance) and the measurement of the stiffness modulus. 6

EXPERIMENTAL SECTION

6.1 Materials The chosen grading formula is a dense high-modulus asphalt 0/20 (French Enrobé à Module Elevé “EME”), used as base course. The virgin limestone aggregates come from the North of France (French Haut-Lieu quarry in Avesnes/Helpes). The RAP aggregates come from the milling of the A43 highway near Chambéry (French Alps), the content and penetration of the recovered aged binder being respectively 5.53% and 13 1/10 mm. Besides, three fresh pen grade bitumens of naphtenic nature were studied, the acidic nature of which allowing a rather good adhesion to the limestone aggregates. Oleoflux®, a vegetable fluxant (from sunflower), is the binder additive used in this study, acting as both a workability enhancer for LEA production at 95°C and also a recycling agent. An initial water content of 1.7% (before partial vaporization due to the foaming phenomenon) was used for the manufacture of each LEA mixture at approximately 95°C. 482

Figure 4. Mixer used for the manufacturing of LEA® high-modulus mixtures (95°C) and corresponding HMAs (160–180°C) at the EIFFAGE TP research centre in Ciry (France).

6.2 Description of tests used The following performances of LEAs and corresponding HMAs were determined in lab: • Compacting ability, measured from the French gyratory shear compacting press PCG (“Presse à Cisaillement Giratoire”) following the requirements of standard NF P 98 252. The test gives a good idea of the density values observed on the job site, according to course thickness, for HMAs. This compulsory test is thus run first. Yet, for LEAs, the results are somewhat optimistic compared to the in-situ density values. • Water resistance, measured from the Duriez test (see standard NF P 98-251-1) which consists of unconfined direct compression test on two sets of cylindrical samples, one set after conditioning in water. If the ratio of the results (the so-called “r/R” ratio) after and before conditioning is above a certain value, the material is acceptable. The r/R ratio is the French counterpart of the ITSR (Indirect Tensile Strength Ratio) value. • Complex stiffness modulus at 15°C–10 Hz, NF EN 12697-26. 6.3 Factorial experimental design Within the framework of a first part of this study, the three studied factors are the RAP content (%), the virgin bitumen penetration (1/10 mm)—however rudimentary the pen value may seem—and the vegetable additive content (%). Each factor has three levels: – RAP percentage: 30, 50, 70% – bitumen penetration: 17.9 (10/20 grade), 39.5 (35/50 grade), 61.1 (50/70 grade) 1/10 mm – vegetable additive content (by weight of the total combined bitumen): 0.2, 0.6, 1% The complete experimental design of this study corresponds to 33 possible combinations (three factors with three levels) of asphalt formulas. A specific reduced factorial experimental design optimized with 13 formulas (Box-Benken matrix), reported in Figure 5 and Table 2, enables to calculate the effects of the different factors on the properties of LEA mixtures. Each formula “i” is hereafter labeled “Fi” (cf. Fig. 5). A second and last part of the study completes the properties of the “F4” formula and consists in comparing the three low-energy manufacturing methods LEA1, LEA2, LEA3 to the control HMA production (see Table 2). 7

RESULTS AND DISCUSSIONS

Table 2 gives all the results obtained in this study: – First, the results of the 13-experiment Box-Benken factorial experimental design, enabling to calculate the effects of the 3 different factors on the mechanical properties of the studied high-modulus LEA mixtures (compacting ability, moisture resistance and stiffness modulus). These results are discussed in details in the following pages, from Figures 6 & 7. 483

% RAP

% additive

Figure 5.

Spatial repartition of the 13 tested asphalt formulas in the experimental domain.

Table 2. Results of Duriez tests, shear compacting press and complex modulus obtained for each formula. Total binder Duriez test N° Process

Formula RAP/ grade/additive

Pen

LEA2 LEA2 LEA2 LEA2 LEA2 LEA2 LEA2 LEA2 LEA3 (2) LEA3 (2) LEA3 (2) LEA3 (2) LEA3 (2)

30% 10/20 0,6% 70% 10/20 0,6% 30% 50/70 0,6% 70% 50/70 0,6% 30% 35/50 0,2% 70% 35/50 0,2% 30% 35/50 1,0% 70% 35/50 1,0% 50% 10/20 0,2% 50% 50/70 0,2% 50% 10/20 1,0% 50% 50/70 1,0% 50% 35/50 0,6%

>0,75 16.3 14.8 38.4 27.0 30.0 20.8 30.0 20.8 15.3 28.2 15.3 28.2 23.7

Modulus

R Moisture % voids at E* 15°C–10 Hz % voids (MPa) res. 120 gyrations at 3.1% voids 1

Specifications of NF P 98-140 1 2 3 4 5 6 7 8 9 10 11 12 13

PCG

4.1 5.5 3.4 6.1 4.0 8.0 3.1 7.7 5.3 5.5 5.7 4.9 5.7

16.43 15.55 10.71 11.84 13.93 10.50 11.55 9.53 18.82 13.07 16.09 12.04 13.38

0.82 0.81 0.94 0.87 0.92 0.78 0.89 0.84 0.87 0.84 0.84 0.94 0.91

3%–6% 2.8 8.9 1.8 7.7 2.5 8.6 2.3 7.8 4.1 6.6 5.0 6.7 5.3

>14000 11 786 11 797 6 855 8 917 11 435 12 483 10 098 11 700 17 924 15 549 15 912 13 174 14 178

Complementary study with new stock of aggregates (same quarry, but different stock) 4 4' 4" 4"'

LEA2 LEA1 LEA3 Control HMA

70% 50/70 0,6% 70% 50/70 0,6% 70% 50/70 0,6% 70% 50/70 0%

27.0 27.0 27.0 27.0

6.7 6.8 5.5 3.0

10.25 12.01 11.96 18.06

0.89 0.92 0.91 0.97

9.0 10.7 8.4 1.9

11 980 10 460 11 720 13 640

1

calculated at an equi-density of 3.1% thanks to the Francken method (1977). within the framework of this 13-combination factorial design, the process that has been chosen for any formula (either LEA2 or LEA3) is the most appropriate with regard to equipment considerations (production output, …).

2

– Second, the results obtained in the case of the “F4” formula considering the three lowenergy manufacturing methods LEA1, LEA2, LEA3 and the control HMA production. The latter highlight the high influence of the manufacturing process and temperature upon the compacting ability of a mix containing 70% RAP. For a lack of time, the stiffness modulus and moisture resistance of the control HMA have not been characterized yet. Further work still remains to be done over the next few months. 484

b) Duriez ratio (moisture resistance)

a) Voids results at the gyratory shear compacting press

0.2% additive

0.2% additive

Penetration

% RAP

% RAP 0.6% additive % RAP

% RAP

0.6% additive

Penetration

% RAP

% RAP

1% additive % RAP

% RAP

1% additive

Penetration

% RAP

% RAP

% RAP

% RAP

Figure 7. Evolution of the complex modulus of the designed LEA® mixture at 15°C–10 Hz according to the RAP percentage, the fresh binder penetration and the additive content.

Figure 6. Results of a) compacting ability (% voids at the shear compacting press, at 120 gyrations) & b) moisture resistance (Duriez ratio) according to the RAP percentage, the fresh binder penetration and the additive content.

Figure 6 evidences the main following results for the studied high-modulus low energy asphalt: – As regards the % voids obtained at the shear compacting press, the higher the RAP content (in the range 30–70%), the more difficult the mix compaction. Both the fresh binder grade and the Oleoflux® additive content seem to have little influence on the compaction ability. – Regarding the Duriez ratio, the softer the bitumen, the better the moisture resistance. The higher the RAP content (ranging from 30 to 70%), the worse the moisture resistance. As regards Figure 7, it shows that the design of a high-modulus low energy asphalt is possible. Indeed, considering the European specifications and in particular the French one, the minimum value required for a high-modulus asphalt is 14,000 MPa. In the case of this study, for a RAP content ranging from 40% to 60%, a fresh bitumen penetration ranging from 18 to 61 1/10 mm is satisfying. In addition to this Box-Benken factorial study (1st part of Table 2), the 2nd part of Table 2 shows additional results obtained for the “F4” formula considering the three low-energy manufacturing methods LEA1, LEA2, LEA3 and the control HMA production, but using a new stock of aggregates: – First, a poor reproducibility was found considering particularly the modulus results after changing the aggregate stock. – Second, the three different LEA processes bring about quite similar mix performances. – Third, at such a high content of RAP (70%), the control HMA exhibits better performances. 8

CONCLUSIONS

This study aimed at determining the influence of the mix composition on the performantial properties of half-warm mix asphalts. The considered half-warm mix asphalts were produced in laboratory at 95°C following the innovative proprietary low energy asphalt technique labeled LEA®. By means of the factorial experiment design approach, this study highlights 485

the influence of the bitumen pen grade (10/20, 35/50 and 50/70), the RAP content (30%, 50% and 70%) and the vegetable additive content used in the LEA process (0.2%, 0.6% and 1%). The primary conclusions and recommendations from this laboratory study are: – As regards the % voids obtained at the shear compacting press, both the fresh binder grade and the Oleoflux® additive content seem to have little influence on the compaction ability. In addition, the higher the RAP content (in the range 30–70%), the more difficult the mix compaction. For the studied materials and in the case of the LEA process, a 60% RAP limit appear as satisfactory when considering the French specification. – Regarding the Duriez ratio (evaluation of the water resistance), all the results are above the minimum value of the French specification (0.75). It is worth noting that the softer the bitumen, the better the moisture resistance. Besides, the higher the RAP content (ranging from 30 to 70%), the worse the moisture resistance. – For a RAP content ranging from 40 to 60% and for a fresh bitumen penetration ranging from 18 to 61 1/10 mm, the stiffness modulus at 15°C–10 Hz is above 14,000 MPa. It is thus noteworthy that the design of a high-modulus low energy asphalt is possible according to the European specifications and particularly to the French one, even with a high rate of RAP. – For the non conventional formula “F4” of this study (70% RAP, 61 pen grade bitumen), the manufacturing process and temperature have a noticeable influence upon its compacting ability, its moisture resistance, and its stiffness modulus. Far beyond this study, the results of which are very encouraging, half-warm mix asphalts seem to have the potential to allow the producers of hot mix asphalt to lower the temperatures at which the material is mixed and placed on the roadway and to use high RAP mixtures as well–up to a 60% percentage according to the present study. REFERENCES Bonaquist, R., 2007. Can I run more RAP? Hot Mix Asphalt Technology (HMAT), September/October. EAPA, “Asphalt in figures”, leaflet distributed by the European Asphalt Pavement Association, 2005. Gaudefroy, V., Olard, F., de la Roche, C., Antoine, J-P. & Beduneau, E., 2008. “Laboratory investigations on the Total Organic Compounds emissions of half-warm mix asphalt technology versus traditional hot mix asphalt”, ISAP Congress on Asphalt Pavements and Environment, Zurich. Harder, G., LeGoff, Y., Loustau, A., Martineau, Y., Héritier, B. & Romier, A. 2008. Energy and environmental benefits of warm and half-warm asphalt mix. 87th TRB Meeting, Washington, D.C. Li, X., Marasteanu, M.O., Williams, R.C. & Clyne, T.R. 2008. Effect of RAP (Proportion and Type) and Binder Grade on the Properties of Asphalt Mixtures. 87th TRB Annual Meeting, Washington, D.C. Olard, F., Le Noan, C. & Romier, A. 2007a. “Low energy asphalt technique LEA for minimizing impacts from asphalt plants to road works”, RGRA Special Issue, European Roads review N°10. Olard F., Antoine, J.P., Heritier, B., Romier, A. and Martineau, Y. 2007b. LEA (Low Energy Asphalt): a New Generation of Half-Warm Asphalt Mixtures. International Conference on Advanced Characterization of Pavement and Soil Engineering Materials, Athens. Olard, F., Le Noan, C. & Romier, A. 2007c. “Innovative low energy asphalt technique for minimizing impacts from asphalt plants to road works”, AIPCR (World Road Association) Congress, Paris. AIPCR Sustainable Development Prize 2007. Olard, F., Le Noan, C. Beduneau, E. & Romier, A. 2008. “Low energy asphalt for sustainable road construction”, 4th Eurobitume & Eurasphalt Congress, Copenhagen. Planche, J.P. 2008. European survey on the use of RAP, Proceedings of the International ISAP Symposium, 18th–20th August, 2008 Zurich, Switzerland, pp. 140–149. Prowell, B.D. 2007. The international technology scanning program report on Warm Mix Asphalt, Report from the US Department of Transportation, Federal Highway Administration, consulted July 2008 from the internet website http://international.fhwa.dot.gov/pubs/wma/summary.cfm Romier, A., Audéon, M., David, J. & Martineau, Y. 2004. Low energy asphalt (LEA) with performance of hot mix asphalt (HMA). European Roads Review, special issue RGRA 2-2004. Romier, A., Audéon, M., David, J., Martineau, Y. & Olard, F. 2006. Low-energy asphalt (LEA) with the performance of hot-mix asphalt, 85th Annual Meeting of the Transportation Research Board. Published in the Journal of the TRB, Transportation Research Record N°1962. Sauzéat, C., Di Benedetto, H., Olard, F. & Nguyen, M.L. 2008. “Fatigue behaviour of half-warm mix asphalts”, Proceedings of the ISAP Congress on Asphalt Pavements and Environment, Zurich.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Viability of the use of construction and demolition debris in hot mix asphalt I. Pérez & M. Toledano Universidade da Coruña, Spain

J. Gallego Universidad Politécnica de Madrid, Spain

ABSTRACT: This work evaluates resistance to plastic deformation and cracking of two hot asphalt mixtures made with recycled aggregates from construction and demolition debris. On the basis of this study it was inferred that the samples designed with recycled aggregates result in a stiffer mixture and are more resistant to plastic deformation. From the standpoint of fatigue behaviour, however, they present a lower fatigue life for a given deformation amplitude. Finally, a multi-layered elastic-linear model was used to determine the variation in the service life of a section of pavement earmarked for roads with low traffic volumes when layers containing recycled aggregates are added. The viability of the use of construction and demolition debris in hot asphalt mixtures was verified, since the number of standard axles that the section can carry is greater than the predicted number of standard axles that will be carried during the service life of the pavement. 1

INTRODUCTION

Hot mix asphalt (HMA) materials are used in a number of different flexible and semi-flexible layers in highways subjected to short-term loads every time a vehicle passes. Under these working conditions, the structural failure of the HMAs, which limit the service life of the pavement, occurs primarily as a result of the loss of stiffness owing to causes that may be related, among other possibilities, to increasing plastic deformation in the upper layers (Nienelt & Thamfald. 1998) or to the propagation of subcritical fatigue cracking in the lower fiber (di Benedetto et al. 2003). Moreover public administrations have been promoting the use of construction and demolition debris (CDD), owing to the exhaustion of the natural resources and the excess accumulation of such debris. In road building it is common to use sub-products and debris in embankments, subgrade areas and the lower courses of roadbeds, since the technical prescriptions are less restrictive. On the other hand, the use of recycled materials in the surface courses of pavements requires additional research to guarantee the functionality of the asphalt mixes. In the last decade, most of the scientific bibliography related to the fabrication and characterization of HMAs made with recycled materials has focused on the reuse of aggregates from milled pavement material while research on HMAs made with CDD -only in the preliminary stage- is still quite scarce (Der-Hsien & Jia-chong. 2004). This paper has studied two types of hot asphalt mixtures widely used in road building in Spain (General Directorate of Highways. 2002a). The mixtures selected consisted of a semidense mixture, S-20, for the binder courses and a coarse mixture, G-20, for the base courses. Two designs were made for each of these mixtures; one with 100% quarried aggregate (used as control) and the other having a ratio of 50% recycled aggregate (RA) and 50% quarried aggregate in each aggregate fraction. The research focussed on evaluating the influence of these types of CDD in mechanisms leading to pavement failure; excessive deformation caused by the accumulation of plastic deformation in the binder courses (S-20) and fatigue cracking of the binder courses (S-20) and base courses (G-20). 487

2

CHARACTERIZATION OF THE MIXTURES

2.1 Aggregates and bitumen The RA material came from a recycling plant of construction and demolition debris located in Madrid (Spain). These aggregates are composed of 77.4% concrete, 20% stone, 0.6% bituminous material and 2% ceramic (Figure 1). The quarried aggregates came from a quarry situated in the region of Galicia (Spain). The filler used was mineral powder from the quarry aggregate so as not to introduce new variables in the mastic of the mixture (Dukatz & Anderson. 1980). The choice of binder was bitumen with a penetration of 60/70; a material commonly used in hot bituminous mixtures. 2.2 Mix design and properties A total of four types of HMAs were produced in the lab: (a) a semi-dense mixture with aggregate from a quarry (S-C), (b) a semi-dense mixture with quarried and recycled aggregates (S-CR), (c) a coarse mixture with quarried aggregate (G-C) and lastly (d) a coarse mixture composed of quarried and recycled aggregates (G-CR). The optimum content of bitumen (Bo) was determined by means of the Marshall test. Table 1 presents the percentages of filler and bitumen that define the mastic of the mixtures. The volumetric and mechanical properties of the Marshall test samples are included in Table 2. These parameters comply with the Spanish specifications for bituminous mixtures in roads with low traffic volumes (Average Annual Daily Heavy Traffic <50) (General Directorate of Highways. 2002a).

Figure 1.

Aggregates from construction and demolition debris (CDD).

Table 1.

Filler Bo(%)

Percentage of filler and bitumen in the bituminous mixtures. S-C

S-CR

G-C

G-CR

5.5 5.0

6.5 6.0

4.3 4.3

4.8 4.8

488

It is interesting to note that a greater quantity of bitumen and filler is used in mixes with recycled aggregate (S-CR and G-CR). It was necessary to increase the proportion of filler to the upper limit of the grading envelope to maintain the filler-bitumen ratio at a fixed rate. Owing to the large amount of pores in the recycled aggregate, the specific surface is high and therefore, it was necessary to raise the content of bitumen to be able to obtain sufficient cohesion. Despite this increase in the amount of bitumen contained in the mixture, the percentage of air voids in the compacted mixture and the percentage of voids in the mineral aggregates was higher than in the control mixes made with natural aggregates; while the density was lower (Table 2). There was a slight increase in the stability of the mixtures with the addition of the recycled aggregates and the increased content of filler and bitumen. 3

TRIALS

3.1 Plastic deformation The study of the material’s resistance to permanent deformation was carried out by means of the wheel tracking test (General Directorate of Highways. 1992a) using samples with the following dimensions: 300 × 300 × 50 mm. In this test the slab was subjected to the alternating passage of a wheel (21 cycles/min.) under specific pressure and temperature conditions, periodically measuring the deformation depth produced at the midway point along the length of the slab (Figure 2). This test was only conducted on mixtures used as binder courses (S-C and S-CR), since they are the ones that are the most prone to permanent deformation. Table 2.

Properties of the mixtures for optimum bitumen content.

Air voids in compacted mixture (%) Voids in mineral aggregates (%) Stability (KN) Deformation (mm) Density (g/cm3)

Figure 2.

S-C

S-CR

G-C

G-CR

4.0 15.0 10.8 2.6 2.40

8.0 20.2 12.6 2.9 2.28

8.9 18.0 11.0 2.8 2.30

11.0 20.9 11.0 2.5 2.22

Wheel tracking test; plastic deformation in the sample.

489

Figure 3.

Fatigue test; cracks in beam.

3.2 Subcritical propagation of cracks Fatigue tests were conducted in flexotraction at three points on prismatic beam samples measuring 300 × 50 × 50 mm under displacement control using an Instron 8516 universal test unit. The deformation values of the lower sample fiber were measured by means of a dynamic extensometer with a measuring base of 50 mm. The test was considered to have been completed when the value of the cyclic load amplitude is less than or equal to half of the cyclic amplitude of the initial load. It is at this time when the first cracks in the beam are considered to appear (see Figure 3). Each type of mixture was subjected to 10 sample tests, with the displacement amplitude being changed in each case between 80 μm and 350 μm (General Directorate of Highways. 1992b). 3.2.1 Bending fatigue test One of the objectives of the dynamic flexotraction test is to determine the resistance of the bituminous mixture when fissures begin to appear. A mixture’s resistance to cracking is expressed by means of the fatigue law in deformation, which is calculated by the following expression: (1) ε = KNB where N is the number of cycles until the fatigue of the material is reached for a specific amplitude of deformation (2ε). K and B are constants. 3.2.2 Dynamic modulus In the fatigue test, the material is subjected to a sinusoidal wave with relatively low deformation amplitude. Under these conditions, the behavior of the HMA materials which are initially elastoviscoplastic becomes linear viscoelastic and it is therefore feasible to calculate the dynamic modulus (DM) by means of this test. This is defined as the quotient between the cyclic amplitude of the stress function and the deformation function. This parameter is a measurement of the stiffness of the sample. The values of stress and deformation are obtained from the elastic theory of material resistance. 4

RESULTS

The results of the wheel tracking test are given in Figure 4, where the plastic deformation is represented in millimeters in relation to the number of cycles. These tests were performed 490

3.0

Deformation (mm)

2.5

2.0

1.5

1.0 S-C 0.5

S-CR

0.0 0

500

1000

1500

2000

2500

Number of cycles

Figure 4.

Permanent deformation results.

0,001 G-CR

S-C

S-CR

log ε

G-C

0,0001 1,0E + 03

1,0E + 04

1,0E + 05

1,0E + 06

log (N)

Figure 5.

Fatigue laws in deformation.

Table 3.

DM

Dynamic modulus.

S-C

SC-R

G-C

GC-R

3866

5016

4086

4675

on mixtures S-C and S-CR under temperature conditions that remained constant at 60ºC and for a load of 0.9 MPa. A comparison of these graphs shows that the two mixes present similar permanent deformation upon completion of the test. However, the way in which the final deformation, after 2520 cycles, is reached varies slightly with a rapid increase in the early stage, becoming linear for the S-C mix and a more progressive but non-linear increase for the SC-R mix. Figure 5 presents the Whöler curves obtained from the fatigue test under conditions applying constant displacement. The straight lines represent the fit on a semi logarithmic scale of the experimental paired values (semi amplitude of the initial deformation imposed, number of cycles until fatigue failure occurs). The dynamic moduli of each mixture are given in Table 3. 491

0,025

Rd (mm/min)

0,020

0,015

0,010 S-C

0,005

S-CR

0,000 (30–45) min. Figure 6.

(70–90) min.

(105–120) min.

Rate of permanent deformation.

From the results obtained for the fatigue laws, it is possible to observe the difference in behavior between the different types of semi-dense and coarse mixtures. The fatigue laws of mixtures S-C and S-CR are higher than the laws corresponding to mixtures G-C and G-CR. This means that for the same deformation unit, the semi-dense mixtures require a greater number of load cycles to reach fatigue failure. The addition of RA produced a greater decrease in resistance to fatigue in the S-CR mixtures than in the G-CR mix. The behavior of mixture S-C and mixture S-CR to fatigue was markedly different. The fatigue law of mixture S-CR is located more towards the left, indicating that for the same deformation unit imposed, the fatigue life of mixture S-CR is lower. For the coarse mixtures, G-C and G-CR, the two graphs are very close to each other, i.e., their fatigue behavior is quite similar. The addition of RA produced an increase in the moduli of the mixtures in both cases (see Table 3). The values obtained met our expectations, in the sense that mixtures S-CR and G-CR had a higher modulus than mixtures G-C and G-CR, owing to their stiffening behavior, which is greater. 5

DISCUSSION

Figure 6 represents the mean rate of permanent deformation (Rd) obtained at three consecutive time intervals and calculated using the data from the wheel tracking test. This information is indicative of the mixture’s resistance to rutting; the lower the rate of permanent deformation, the greater its resistance. As can be observed, the behavior of mix S-C is stable, maintaining steady rates of around 0.019 mm/min. In mixture, S-CR, on the other hand, the rate of permanent deformation is not stable and shows lower values than in the other mixture. This trend would indicate that semi-dense mixtures made with recycled aggregates are more resistant to permanent deformation. Moreover, the bending fatigue tests performed show that, within the same typology, the mixtures having the greatest stiffness are the one that behave poorly to fatigue; the higher the modulus of the mixture, the lower the number of cycles for a given displacement. The multilayer linear elastic model (Huang. 2004) was used to estimate the service life of pavements using HMA made with CDD. As is well known, the data obtained from the fatigue test in displacement control are associated with pavements having low 492

Table 4.

Structural sections for the analysis of fatigue life. Section 3211 (AADTTH < 50)

Layer

Thickness (mm)

Surface course Binder course Base course Subbase course Subgrade

30 70 80 400 –

Table 5.

Option 1 S-C G-C

Option 2 M-10 S-CR G-CR ZA-25 E1

Option 3

Option 4

S-CR G-C

S-C G-CR

Analysis of fatigue response. Section 3211 (AADTH < 50)

εt (× 10–4) Na (× 105) Nt (× 105)

Option 1

Option 2

Option 3

Option 4

1.36 2.42

1.47 1.82

1.43 1.97

1.40 2.20

1.56

thicknesses (di Benedetto & de la Roche. 1998). For this reason, in this analysis we chose a section of road with low traffic volume (AADTTH < 50) and relatively low thicknesses. The specific section selected was section 3211 (Table 4), included in the official catalogue of road sections of Spain (General Directorate of Highways. 2002b). Table 4 presents 4 different options or possibilities permitted for the use of bituminous mixes. In all of the above, codes M-10, ZA-25 and E1 are repeated throughout Table 4. The surface course, 30 mm thick, is made of hot mix asphalt (M-10) with a discontinuous particle size distribution made with quarried aggregates having a maximum nominal size of 10 mm. Both the binder courses (70 mm.) and the base courses (80 mm) are composed of hot asphalt mixtures. In the binder courses, however, type S-20 mixtures are used, while the base courses are made up of type G-20 mixtures. Also used are mixtures containing RA or quarried aggregates, depending on the option chosen. The subbase courses, consisting of unbound granular material (ZA-25) made with quarried aggregates have a thickness of 400 mm. All of these layers rest on a subgrade formed by a selection on non-plastic soils (E1). Table 5 shows the results of the service life of the sections of road under consideration. Included are the values for the critical strain in the base courses made with asphalt mix, εt, the number of single standard axles the section can carry before fatigue failure occurs (Na) and the number of single axles predicted for a useful service life of 15 years, taking into account an annual traffic growth rate of 2%, (Nt). From this table it may be inferred that all of the sections are structurally valid, since in the four options, the allowable number of axles (Na) exceeds the predicted number of axles (Nt). As is evident, the longest service life is obtained with option 1; i.e., the pavement designed only with quarried aggregates. The lowest pavement service life was found with option 2 which uses RA in the binder and base course. The best alternative for the addition of RA is option 4, which consists of a base course with RA and a binder course with quarried aggregates. 6

CONCLUSIONS

The laboratory test of the mechanical properties of hot asphalt mixes made with 50% quarried aggregates and 50% recycled aggregates from construction and demolition debris suggests that: – The use of recycled aggregates improves the response of semi-dense mixtures to permanent deformation. The S-CR mixtures are less prone to plastic deformation. 493

– The fatigue life of the coarse HMAs, G-CR, underwent very little change with the addition of recycled aggregates. – The semi-dense HMAs, S-CR, are apt to lose fatigue resistance when recycled aggregates are added. – Recycled aggregates increase stiffness in both the coarse and semi-dense mixtures. – Satisfactory service lives were obtained when recycled aggregates were added to the HMA of binder and base courses of pavement sections with low traffic volume. – There is useful evidence supporting the viability of the use of recycled aggregates in HMA of pavement sections with low traffic volume. Nevertheless long term trials are needed to confirm that they are viable alternatives. REFERENCES Der-Hsien, S. & Jia-chong, D. 2004. Evaluation of building materials recycling on HMA permanent deformation. Construction and building materials, 18, 391–197. Di Benedetto, H. & de la Roche, C. 1998. State of the art on stiffness modulus and fatigue of bituminous mixtures. Bituminous Binder and Mixes. RILEM Report 17. Di Benedetto, H. de la Roche, C. Baaj, H. Pronk, A. & Lundstron, R. 2003. Fatigue of bituminous mixtures: different approaches and RILEM group contribution. In: Proceedings of the 6th International RILEM Symposium, Performance Testing and Evaluation of Bituminous Materials, Zurich, pp. 15–38. Dukatz, E.L. & Anderson, D.A. 1980. The effect of various fillers on the mechanical behaviour of asphalt and asphaltic concrete. Proceedings, AAPT, Minneapolis. General Directorate of Highways. 1992a. Norma NLT-173/90. Resistencia la deformación plástica de las mezclas bituminosas mediante la pista de ensayo de laboratorio. Ministerio de Obras Públicas y Transportes, Madrid. General Directorate of Highways. 1992b. Norma NLT-350/90. Ensayo de fatiga en flexotracción dinámica de mezclas bituminosas. Ministerio de Obras Públicas y Transportes, Madrid. General Directorate of Highways. 2002a. Pliego de Prescripciones Técnicas Generales para Obras de Carreteras y Puentes PG-3. Ministerio de Fomento. Madrid. General Directorate of Highways. 2002b. Secciones de firme de la Instrucción de Carreteras IC. Ministerio de Fomento. Madrid. Huang, Y.H. 2004. Pavement Analysis and Design. Pearson Prentice Hall. Nienelt, G. & Thamfald, H. 1988. Evaluation of the resistance to deformation on different road structures and asphalt mixtures determined the pavement rutting tester. Proceedings, Association of Asphalt Paving Technologists, 57, Minneapolis, USA, pp. 320–345.

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Thermal stresses of asphalt pavement with temperature-dependent modulus of elasticity Y. Zhong & L. Geng School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian, Liaoning, China

ABSTRACT: This paper presents an analytical study of thermal stresses of asphalt pavement with temperature-dependent modulus of elasticity. In the analysis, the asphalt pavement is regarded as a multilayered elastic half space axisymmetrical system. First, thermoelastic theory is used to describe thermal stresses of multi-layered system, while the temperaturedependent modulus of elasticity is considered. Then, Laplace transformation and Hankel transformation with respect to time and radial, respectively, are utilized for thermo-elastic equations of equilibrium. Then, the transfer matrix method is applied to derive general solutions for multi-layered problem. Finally, the resulting formulation is applied to calculate thermal stresses in the low temperature cracking problem of asphalt pavement. Thermal stress is calculated and compared with the case that modulus of elasticity supposed to be constant, to show the remarkable impact of temperature-dependent modulus of elasticity on thermal stresses of asphalt pavement. 1

INTRODUCTION

It has been recognized that the effect of temperature is important in asphalt pavement, such as high temperature rutting and low temperature cracking, etc. This damage may not only impact the external appearance of pavement, but also accelerate the deterioration of pavement structure. For example, the cracks of pavement surface may introduce unwanted moisture into base courses and the subgrade, which weakens the strength of base courses and subgrade. Therefore, it becomes one of significant topics in pavement engineering to lead a further analysis of the interaction between thermal stresses of the pavement and the influencing factors, taking into consideration the real behavior of material characteristics in asphalt pavement, to improve the thermal resistance of asphalt pavement. Although thermal cracking of asphalt pavement hasn’t been considered in pavement design specifications, many research studies have been launched on the thermal stresses problem of pavement in the past years. For example, Choubane & Tia (1995) presented the nonlinear distributions of temperature along the depth and calculated the thermal stresses of rigid pavements. Using finite-element method, Harik et al. (1994) took the research on two-dimensional issue of nonlinear temperature distributions through the thickness of rigid pavements. Wong & Zhong (2000) used transfer matrix method to derive the general solutions of asphalt pavement with variable temperature. Zhong & Geng (2007) used stiffness matrix method to calculate the solutions of thermal stresses for axisymmetric problems in multilayered elastic half-space in cooperation of vehicle load and temperature, and so on. But these research studies assumed that the modulus of elasticity was constant. Thermal cracking of asphalt pavement mainly occurs in cold weather, when asphalt mixture exhibits apparent brittleness, which is similar with elastic material, thus it is rational to analyze it based on elastic theory, but the variation of temperature still has an influence on material characteristics of asphalt mixture. Simonsen et al. (1997) show that none of the modulus of elasticity, Poisson’s ratio, the coefficient of thermal expansion and thermal conductivity of asphalt mixture is constant at different temperatures. Among the material characteristics, the 495

modulus of elasticity of asphalt mixture, which decreases at high temperature and increases at low temperature, is the most sensitive to temperature. Research findings show that changes in Poisson’s ratio and coefficient of linear thermal expansion due to variable temperature are not significant (Manson, 1952). This paper aims to present an analytical study on thermal stresses of asphalt pavement by transfer matrix method with modulus of elasticity dependent on the reference temperature. Firstly, transfer matrix for one layer is obtained by introducing relationship between the modulus of elasticity and temperature to the constitutive functions of thermoelasticity and utilizing mathematic methods of Laplace transformation and Hankel transformation. Then, the transfer matrix method is adopted to derive general solutions for multilayered problem. Finally, thermal stresses of an asphalt pavement example are calculated and compared with the case that modulus of elasticity are supposed to be temperature-independent. The results show the remarkable impact of the temperature-dependent modulus of elasticity of asphalt mixture on the thermal stresses of asphalt pavement. 2

DERIVATION OF TRANSFER MATRIX

The calculation model of an asphalt pavement is treated as an axial symmetric elastic layered half space problem. The equations of equilibrium in the cylindrical coordinates system are ∂σ r ∂τ zr σ r − σ θ + + =0 r ∂r ∂z

(1)

∂σ z ∂τ zr τ zr + + =0 r ∂z ∂r

(2)

The constitutive relations for linear thermoelastic response of an isotropic medium can be expressed as follows ∂u ⎡ ⎤ ⎛ u ∂w ⎞ σ r = β (T ) ⎢(1 − μ ) + μ ⎜ + ⎟ − (1 + μ )αT ⎥ ∂r ⎝ r ∂z ⎠ ⎣ ⎦

(3)

⎡ u ⎤ ⎛ ∂u ∂w ⎞ σ θ = β (T ) ⎢(1 − μ ) + μ ⎜ + ⎟ − (1 + μ )αT ⎥ ∂ ∂ r r z ⎝ ⎠ ⎦ ⎣

(4)

⎡

∂w

⎣

∂z

σ z = β (T ) ⎢(1 − μ )

⎤ ⎛ ∂u u ⎞ + ⎟ − (1 + μ )αT ⎥ ⎝ ∂r r ⎠ ⎦

+ μ⎜

(5)

1 ⎛ ∂u ∂w ⎞ τ zr = (1 − 2 μ )β (T ) ⎜ + ⎟ 2 ⎝ ∂z ∂ r ⎠

(6)

where u and w represent the radial and vertical displacements, respectively; σr, σθ and σz are normal stresses in the r, θ and z directions, respectively; τzr is shear stress; β(T) = E(T)/[(1 + μ) (1 – 2μ)], E(T ) denotes the temperature-dependent modulus of elasticity, μ is Poisson’s ratio, α is the coefficient of thermal expansion and T is function of temperature. The heat diffusion equation for the asphalt pavement can be expressed as follow

κ ∇ 2T =

∂T ∂t

(7)

2 2 where ∇ 2 = ∂ + 1 ∂ + ∂ and ∇ 2 denotes the Laplace operator, κ is the conductive 2 r ∂r ∂z 2 ∂r thermal diffusivity coefficient.

496

In thermodynamics, the relationship between heat quantity and temperature is Q = −λt

∂T ∂z

(8)

where Q is the heat quantity and λt is the thermal conductivity. To obtain the state-space equations, substituting equations (3) and (4) into equation (1), and differentiating equation (5) with respect to r, then combining the resulting equations, one gets ⎛ ∂2 1 ∂ 1 ⎞ ∂τ zr 2 μ − 1 ∂T μ ∂σ z (1 + μ )((1 − 2 μ ) = β (T ) ⎜⎜ 2 + αβ (T ) − 2 ⎟⎟ u − + 1− μ r r 1 r ∂z 1 − μ ∂r μ ∂ − ∂ r r ∂ ⎝ ⎠

(9)

Equations (2), (5), (6) and (8) can be rewritten as ∂σ z ⎛ ∂ 1⎞ = − ⎜ + ⎟τ zr ∂z ⎝ ∂r r ⎠

(10)

∂w 1 μ ⎛ ∂ 1⎞ α (1 + μ ) σz − = T ⎜ + ⎟u + ∂z (1 − μ )β (T ) 1 − μ ⎝ ∂r r ⎠ 1− μ

(11)

∂u 2τ zr ∂w = − ∂z (1 − 2 μ )β (T ) ∂r

(12)

∂T 1 =− Q λt ∂z

(13)

Differentiating equation (8) with respect to z and substituting the resulting equation into equation (7) results in ⎛ ∂2 1 ∂ 1 ∂ ⎞ ∂Q = λt ⎜⎜ 2 + − ⎟T ∂z r ∂r κ ∂t ⎟⎠ ⎝ ∂r

(14)

In equations (9)–(14), τzr, σz, w, u, T and Q are all functions of r, z and t. To omit the variable of time and the variable of radial, first, the Laplace transformation is utilized on both sides of equations (9)–(14). Let

and the Laplace inverse transformation is

The Hankel transformation is defined by the relation

and the Hankel inverse transformation is

497

where Jn(ξr) is the Bessel function of order n. Then upon the first order Hankel transformation of equations (9) and (12) upon the zero order Hankel transformation of equations (10), (11), (13), (14), the solution can be written in the form of a matrix as follow (15) where ⎡ 0 0 ξ ⎢ ⎢ u ⎢ ξ 0 0 ⎢ μ −1 ⎢ ⎢ 0 0 0 ⎢ A(ξ , s ) = ⎢ ⎢ 0 0 0 ⎢ 1 2 − u ⎢ β (T )ξ 2 0 0 ⎢ 1− μ ⎢ 1 ⎢ 0 0 − ⎢ λ t ⎣

0

2 (1 − 2 μ )β (T )

1 (1 − μ )β (T )

0

0

0

0 μ ξ 1− μ

−ξ

0

0

0

⎤ ⎥ ⎥ α (1 + μ ) ⎥ ⎥ 1− μ ⎥ ⎥ ⎛ 2 s⎞ −λt ⎜ ξ + ⎟ ⎥ κ⎠ ⎝ ⎥ ⎥ 0 ⎥ α (1 + μ )(1 − 2 μ )β (T ) ⎥ ξ ⎥ μ −1 ⎥ ⎥ 0 ⎥ ⎦ 0

According to modern control theory, the solution of equation (15) is (16) where M(ξ, z, s) is the transfer matrix and can be solved with the Cayley-Hamilton theorem (see Zhong et al. 1992). The elements mij of the matrix M(ξ, z, s) are given in Appendix. 3

SOLUTIONS FOR MULTILAYERED BODY

For multilayered elastic system shown in Figure 1, the boundary condition is as follows: at the top surface, τzr, σz and T are known; at the bottom surface, lim u, w, Q, σ z , τ zr , T → 0 ; and z →∞ at the interface, the stresses are equal and the displacements are continuous. For any layer equation (16) is suitable, particularly for the case z = hi, then equation (16) can be written as (17) For the case a multilayered continuous elastic body, due to the equality of interface stresses and the continuity of interface displacements, the compatibility conditions at interfaces can be expressed as (18) Using equation (17) and (18) repeatedly results in

(19) where [Mi] is the transfer matrix of the ith layer. Usually, stresses τzr, σz and temperature T of top and bottom layers are known. Using equacan be solved in Laplace and Hankel transformation domain. tion (19) repeatedly, Then utilizing Laplace and Hankel inverse transformation, stresses, displacements and temperature can be calculated. 498

r

h1

E1(T) μ1

κ1 λti

αi

κi λti

αΝ

κΝ λtN

...

.. .

α1

hi

Ei(T) μi . ..

. ..

EN(T) μN z Figure 1.

4

Multilayered elastic body.

APPLICATIONS

Consider an asphalt pavement structure consisting of three layers: asphalt mixture surfacing, semi-rigid base of cement stable gravel and soil subbase. Usually, thermal variations have little influence on semi-rigid base and soil subbase because of the overlay of asphalt concrete layer, so assume that modulus of elasticity of base and subbase are constant and only that of asphalt layer is temperature-dependent here. Considering that on the pavement surface, temperature varies with respect to time as follows (see Yan, 1984) ⎡π ⎛ ρ ⎞⎤ T0 (t ) = 20 sin ⎢ t − arctan ⎜ ⎟⎥ 12 ⎝ 1 + ρ ⎠⎦ ⎣

(20)

where ρ is the thermo-resistive coefficient, and ρ = 0.4 here. Recent research (Zha, 2002) shows that asphalt modulus-temperature curve is almost linear in semi logarithmic coordinates: E (T ) = a10 − bT

(21)

where a and b are parameters determined by experiment. Based on the experimental data of asphalt mixture (see Sha, 1998 and Wu, 1995), a = 2866 and b = 0.01984, respectively, and the correlation coefficient of linear regression equation is 0.962339. The rest of the typical material properties are indicated below: μ1 = 0.25, α1 = 2.16 × 10–5 1/°C, κ1 = 2.2 × 10–3 m2/h, λt1 = 1.0 kcal/m · h · °C, h1 = 0.15 m; E2 = 1500 MPa, μ2 = 0.25, α2 = 1.0 × 10–5 1/°C, κ2 = 2.8 × 10–3 m2/h, λt2 = 1.2 kcal/m · h · °C, h2 = 0.25 m; E3 = 50 MPa, μ3 = 0.35, α3 = 5.0 × 10–4 1/°C, κ3 = 3.0 × 10–3 m2/h, λt3 = 1.0 kcal/m · h · °C. For comparison purposes, two situations are calculated: (1) the modulus of elasticity of asphalt surface is temperature-dependent, which is E1 = E1(T). (2) the modulus of elasticity of asphalt surface is assumed constant, and let E1 = 2500 MPa. Temperature and thermal stresses are calculated at depths of 0.05 m, 0.10 m and 0.15 m, respectively, as shown in Figures 2 and 3. Figure 3 shows that magnitude and direction of thermal stresses of asphalt pavement change with time and temperature (also see Figure 2). As temperature increases, the shrinkage stress occurs, while as temperature decreases, the tensile stress occurs. Comparing thermal stresses of condition 1 with those of condition 2, thermal stresses of condition 1 are smaller when temperature increases but larger when temperature decreases than those of condition 2. The difference between the two conditions is the most remarkable at the surface, and decreases as the depth increases. In other words, the temperature-dependent modulus of elasticity has great influence on thermal stresses of asphalt pavement, especially at the surface and when temperature decreases. 499

20 z = 0.00 m z = 0.05 m z = 0.10 m z = 0.15 m

15

Temperature/°C

10 5 0 –5 –10 –15 –20

0

4

8

12

16

20

16

20

24

Time/hour

Figure 2.

Pavement temperature with time.

Thermal stress/MPa

1.5 Cond. 1 Cond. 2 z = 0.05 m z = 0.10 m z = 0.15 m

1

z = 0.05 m z = 0.10 m z = 0.15 m

0.5 0 –0.5 –1

0

4

8

12

24

Time/hour Figure 3.

5

Comparison of thermal stresses.

SUMMARY AND CONCLUSIONS

With consideration of temperature-dependent modulus of elasticity, general solutions are presented for the thermal stress problem of multi-layered elastic half-space axisymmetric system by integral transformations and transfer matrix method. These solutions are used to calculate thermal stresses in the low temperature cracking problem of asphalt pavements. The calculating results show the great impact of temperature-dependent modulus of elasticity of asphalt mixture on thermal stresses of asphalt pavement. REFERENCES Choubane B. & Tia M. 1995. Analysis and Verification of Thermal-gradient Effects on Concrete Pavement. Journal of Transportation Engineering 121(1): 75–81. Harik I.E., Jianping P. & Southgate H., et al. 1994. Temperature Effects on Rigid Pavements. Journal of Transportation Engineering 120(1): 127–143. Manson S.S. 1952. Behavior of Material Under Conditions of Thermal Stress. NACA Report, Lewis Flight Propulsion Laboratory National Advisory Committee for Aeronautics Cleveland. Sha Q.L. 1998. Asphalt Pavement on Semi-rigid Road-base for High Class Highways. In Beijing: China Communications Press. Simonsen E., Janoo V.C. & Isacsson U. 1997. Prediction of Pavement Response During Freezing and Thawing Using Finite Element Approach. Journal of Cold Regions Engineering 11(4): 308–324.

500

Wong W.G. & Zhong Y. 2000. Flexible Pavement Thermal Stresses with Variable Temperature. Journal of Transportation Engineering 126(46): 46–49. Wu G.C. 1995. Analysis of the Semi-rigid Pavement Thermal Stresses. In Beijing: Science Press. Yan Z.R. 1984. Analysis of the Temperature Field in Layered Pavement System. Journal of Tongji university (3): 76–85. Zhong Y. & Geng L.T. 2007. Analytical Solution for Thermo-stresses of Flexible Pavement. Journal of Dalian University of Technology 47(6): 858–861. Zhong Y., Wang Z.R. & Guo D.Z. 1992. The Transfer Matrix Method for Solving Axisymmetrical Problems in Multilayered Elastic Half Space. China Civil Engineering Journal 25(6): 37–43. Zha X.D. 2002. Temperature Adjustment for Back Calculation Moduli of Asphalt Pavement. Highway (6): 51–53.

APPENDIX m11 = [ 2(1− μ )chξ z + ξ zshξ z ] / 2(1− μ ); m12 = [(1 − 2 μ )shξ z + ξ zchξ z ] / 2(1− μ ); m13 = (1+ μ )ακ [ξ shqz − qshξ z ] /(1− μ )λt qs; m14 = (1+ μ )zshξ z / 2 E (T )(1 − μ ); m15 = (1 + μ )[(3 − 4 μ )shξ z + ξ zchξ z ] / 2 E (T )(1 − μ )ξ ; m16 = (1 + μ )ακξ (chξ z − chqz ) /(1 − μ )s; m21 = [(1 − 2 μ )shξ z − ξ zchξ z ] / 2(1 − μ ); m22 = [ 2(1 − μ )chξ z − ξ zshξ z ] / 2(1 − μ ); m23 = (1 + μ )ακ [chξ z − chqz ] /(1 − μ )λt s; m24 = (1 + μ )[(3 − 4 μ )shξ z − ξ zchξ z ] / 2 E (T )(1 − μ )ξ ; m25 = − m14 ; m26 = (1 + μ )ακ (qshqz − ξ shξ z ) /(1 − μ )s; m31 = m32 = 0; m33 = chqz; m34 = m35 = 0; m36 = −λt qshqz; m41 = −E (T )ξ 2 zshξ z / 2(1 − μ 2 ); m42 = E (T )ξ ( shξ z − ξ zchξ z ) / 2(1 − μ 2 ); m43 = α E (T )κξ [ qshξ z − ξ shqz ] /(1 − μ )λt qs; m44 = [ 2(1 − μ )chξ z − ξ zshξ z ] / 2(1 − μ ); m45 = −[(1 − 2 μ )shξ z + ξ zchξ z ] / 2(1 − μ ); m46 = α E (T )κξ 2 [chqz − chξ z ] /(1 − μ )s; m51 = E (T )ξ ( shξ z + ξ zchξ z ) / 2(1 − μ 2 ); m52 = −m41; m53 = α E (T )κξ [chqz − chξ z ] /(1 − μ )λt s; m54 = −m21; m55 = [ 2(1 − μ )chξ z + ξ zshξ z ] / 2(1 − μ ); m56 = α E (T )κξ [ξ shξ z − qshqz ] /(1 − μ )s; m61 = m62 = 0; m63 = − shqz/λt q; m64 = m65 = 0; m66 = m33 .

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Rigid pavement reinforcement: Modeling of structural behavior P. Domingos & M.L. Antunes National Laboratory of Civil Engineering, Lisbon, Portugal

J.M.C. Neves IST Technical University of Lisbon, Lisbon, Portugal

ABSTRACT: The use of “multi-layer” models is quite common in the calculation of the response of road and airport pavement structures to traffic loads. In order to study the reinforcement of jointed concrete pavements it is necessary to use more versatile methods, which allow for the analysis of situations that are not contemplated in the simple models. For such studies, advanced numerical methods can be used, such as the finite difference method. This study presents an application of the finite difference method to the analysis of an airport jointed concrete pavement overlaid with an asphalt layer. The model parameters are calibrated through FWD deflections measured in tests performed at different positions with respect to the concrete pavement joints. From the works developed in this study, it is possible to determine more realistic values for the stresses and strains in the asphalt overlays when the load is acting in the vicinity of a joint. These values may be quite significant for certain conditions of temperature and load transfer at joints. 1

INTRODUCTION

The current models used in structural analysis of Jointed Concrete Pavements (JCP) present limitations, because this type of pavements have specific characteristics, such as the presence of discontinuities ( joints), steel reinforcement or dowels bars. In order to solve the models limitations, and to achieve a response closer to the reality, it is necessary to use structural models based on numerical methods, which take into account the particularities mentioned above. Such methods fit into the universe of mechanical computational methods, among which are the finite difference method and the finite element method. The finite difference method is a numerical procedure for the resolution of differential equations in the field of physics and engineering, described in various publications [1], [2]. It is a very versatile numerical method, which allows the consideration of the following aspects, with relative simplicity: • • • •

use of constitutive material models, such as non-linear models, visco-elastic models, etc.; adequate simulation of boundary conditions; modelling of domains with complex geometries; dynamic analysis.

This study presents an application of the finite difference method to the analysis of a jointed airport rigid pavement overlaid with a continuous asphalt layer (Fig. 1). The model parameters are calibrated through Falling Weight Deflectometer (FWD) deflections measured in tests performed at different positions with respect to the concrete pavement joints.

503

0,05

1

0,06 0,06 0,03

0,40

0,10

0,60

2

Key: 1

Asphalt concrete wearing course

2

Asphalt concrete binder course

3

Thin asphalt concrete levelling course

4

Jointed Portland cement concrete slabs

5

Lean concrete base course

6

Subgrade

3

4

5

6

[m]

Figure 1.

2

Rigid pavement (JCP) and asphalt overlay.

METHODOLOGY

FWD tests were conducted with the aim of determining the models parameters. These parameters are essentially the following: • layers thickness and elastic moduli; • joint characteristics; • characteristics of the interface between the concrete slab and the asphalt overlay. Due the existence of the asphalt overlay the exact joint position it is not known. The test methodology adopted, takes into account this issue through performing FWD tests for two situations of load application: • load applied in the slab central area; • load applied in an area around the estimated joint position. The FLAC software (based in the finite difference method) was used for the pavement numerical modeling of the reinforced pavement in the joint area. The methodology adopted was the following: • The stiffness characteristics of the pavement and subgrade layers, and the interface conditions between the concrete and the asphalt overlay were back-analysed from FWD deflections measured at slab centre tests. • The deflections for slab centre FWD tests were calculated with a 2D numerical model using the backcalculated characteristics. This calculation allowed for the verification of the appropriateness of the FLAC model geometrical parameters (definition of number of zones in each layer and dimensions of the continuum). 504

• The characteristics of the joints between concrete slabs were backcalculated using the and 3D numerical model (FLAC 3D software) from the deflections measured at FWD tests near the joints. The stiffness characteristics for the joints were defined for different types of responses observed in the FWD near the joints. The remaining model characteristics (layer stiffness and interface conditions) were the same as in previous calculations. • After the generation and calibration of all pavement models, the critical stresses and strains calculated with different models were compared. 3

PAVEMENT DEFLECTION MEASUREMENTS WITH THE FWD

3.1 Test survey procedures Due to the pavement structure specificities, and taking into account the objectives of the FWD tests (evaluation of the joint contribution for the structural response of the reinforced pavement), it was necessary to establish a test procedure that enabled the identification of joint locations, and the characterization of the pavement structural response in the vicinity of the joints. Taking in to account the fact that the concrete slabs are covered with a continuous asphalt overlay, the test procedure was the following (see Figure 2): • FWD load applied at the slab centre; • FWD load applied in the vicinity of the joints, along a line which is perpendicular to the joint: Testing at points located 0,1 m apart, starting 0,5 m before the estimated location of the joint and ending 0,5 m after the estimated location of the joint. The objective for the slab centre tests was to evaluate the stiffness moduli for all pavement layers, trough a current back-analysis procedure [3]. Based on these tests, the interface characteristics between the concrete slab and the reinforcement layers were also estimated. The objective of the methodology used in the joint tests, was to detect the location of the joint, in order to use the results for the pavement response modelling, with the explicit consideration of the joints. This test procedure is based on the principle that, when the distance between the load and the joint decreases, the value of the deflection measured in the centre of the loaded area increases, and reaches the maximum value when the load is applied over the joint. The inverse phenomenon will occur when the distance between the load and the joint increases. The configuration of the FWD was the following: • loading plate with 0,45 m diameter; • peak load of 150 kN. These tests were conducted at dawn during winter, to ensure the most unfavorable conditions for the joint response. 3.2 Test results Figures 3 and 4 present some examples of the test results obtained near the joints. The main conclusions obtained from these tests are the following: • In general, the methodology used allows for a clear identification of the presence of the joints under the overlay. However, in some cases, the deflections obtained were almost constant, which means that the structural response obtained was similar to a continuous pavement (see Figure 3); • For the cases where the joints were detected, it was possible to identify two groups of joints, corresponding to a lower or higher load transfer between slabs, expressed by the difference between the maximum and the minimum values of the measured deflections (see Figure 4). 505

Runway center line

Longitudinal joint

Slab y

Slab x

Transversal joint

Key: Joint tests (loading plate location) Slab center tests FWD progression direction

Deflection transducers

0,1 m Joint

(D5)

(D6)

(D3) (D2) (D1)

(D4)

Test point

(D0)

Loading plate

1,0 m

Figure 2. FWD test procedure. 300

250

200

Deflection 150 (μm) 100

50

0,50 a

0,40 a

0,30 a

0,20 a

0,10 a

Joint

0,10 b

0,20 b

0,30 b

0,40 b

0,50 b

0

Distance to the joint (m) D0

Figure 3.

D1

D2

D3

D4

D5

D6

FWD test results at joints: no detection of the joint (continuous response).

506

300

a) 250

200

Deflection (μm)

150

100

50

0,50 a

0,40 a

0,30 a

0,20 a

0,10 a

Joint

0,10 b

0,20 b

0,30 b

0,40 b

0,50 b

0

Distance to the joint (m) D0

D1

D2

D3

D4

D5

D6

300

b) 250

200

Deflection 150 (μm) 100

50

0,50 a

0,40 a

0,30 a

0,20 a

0,10 a

Joint

0,10 b

0,20 b

0,30 b

0,40 b

0,50 b

0

Distance to the joint (m) D0

Figure 4. transfer.

4

D1

D2

D3

D4

D5

D6

FWD test results at joints: a) joint with lower load transfer; b) joint with higher load

PAVEMENT MODELLING BY THE FINITE DIFFERENCE METHOD

4.1 Numerical model definition Two numerical models were defined in this study, a two-dimensional pavement model (axisymmetry), and a three-dimensional pavement model. The 2D model was used to analyse the load application in the slab centre; the 3D model was used to simulate the load application in the joint. 507

The layer structure for the two numerical models is the following: • • • • •

asphalt overlay with a total thickness of 0,20 m; jointed concrete slab with 0,40 m thickness; lean concrete base course with 0,10 m thickness; subgrade upper layer with 0,60 m thickness; subgrade lower layer with 2,7 m thickness.

For the definition of the pavement structural model, it was assumed that there is partial friction between the overlay and the concrete slab. With the FLAC software, the contact between the two layers was modeled by special interfaces (defined by their stiffness properties), which allow to consider several friction conditions. The modeling of transversal and longitudinal joints was also made using the same feature. In the two-dimensional model (axisymmetric), only the horizontal interface between the overlay and the rigid pavement was considered. In this model the interface is defined by a linear element (one-dimensional). On the other hand, in the 3D model two interfaces were defined by triangular (2D) elements: a vertical interface corresponding to the joint, and a horizontal interface, corresponding to the contact plan between the concrete slab and the asphalt overlay. Each joint element is characterized by its stiffness characteristics (Kn – normal joint stiffness; Kt – shear joint stiffness). 4.2 Numerical model calibration The numerical model calibration was based on the results obtained from the FWD tests, and the layer stiffness moduli obtained through back-analysis using the BISAR model. The Root Mean Square (RMS) between measured and calculated deflections was used as the indicator for the validation process. The validation criterion was a RMS of 10% or less. ⇒

Load application in the slab centre—2D model Table 1 presents the calculated stiffness properties for all layers, and the respective RMS values.

Table 1.

Pavement response models for the load applied in the slab centre. Subgrade Asphalt layers

Concrete slab

Lean concrete

Upper

Lower

RMS Slab Software S (MPa) h (m) S (MPa) h (m) S (MPa) h (m) S (MPa) h (m) S (MPa) h (m) (%) 400

∞ 2,7

3,77 3,84

100

380

∞ 2,7

3,96 5,73

1500

100

380

∞ 2,7

3,16 6,17

20000

900

100

380

∞ 2,7

3,90 3,89

BISAR 4500 FLAC 5

30000

1200

120

380

∞ 2,7

4,98 4,50

BISAR 3000 FLAC 5

16000

800

100

360

∞ 2,7

5,00 6,32

1

BISAR 5500 FLAC 5

0,2

32000

0,4

1700

2

BISAR 5000 FLAC 5

30000

1500

3

BISAR 5000 FLAC 5

30000

4

BISAR 3000 FLAC 5

5 6

Key: S – Stiffness modulus; h – Thickness.

508

0,1

150

0,6

⇒

Load application in the joint—3D model

The characteristics derived from the 2D models were used in the 3D model. The process used to validate the three-dimensional models, was to minimize the difference between the deflection measured and calculated by FLAC 3D in the centre of the loaded area for the load applied above the joints. The stiffness values for each joint, arte presented in Table 2 together with the percent difference between the measured and calculated deflections. 4.3 Comparison between the results obtained with BISAR and FLAC 3D Figure 5 shows the strains, at the bottom of the asphalt layers due to the load applied by the FWD, calculated with the BISAR software. It is possible to conclude for all cases that the tensile strains are negligible (between 0,6 and 5,9 μm/m). Figure 6 shows the strain variations calculated with FLAC 3D for different types of joint conditions. From this Figure it is possible to conclude that the tensile strain in the asphalt overlay above the joints vary between 66 and 99 μm/m, depending on the Table 2.

Joint stiffness characteristics. Joint stiffness characteristics

Model

Kn (Pa/m)

Ks (Pa/m)

ΔD0 (%)

JT 1_1 JT 2_1 JL 1_2_1 JL 5_6_1

1,0 × 109 1,0 × 109 1,0 × 108 1,0 × 1010

1,0 × 109 1,0 × 109 1,0 × 108 1,0 × 1010

0 3 2 7

Key: ΔD0 – Difference between measured and calculated deflections. Kn, Ks – normal and shear joint stiffness, respectively.

5 0

150

0,5

0,5

–5

εx (μm/m)

100

–10 –15

50

–20 0 –2,5

–1,5

–0,5

0,5

1,5

2,5

–50

–100

–150 Distance to the loading plate centre (m) Slab 1

Figure 5.

Slab 2

Slab 3

Slab 4

Slab 5

Slab 6

Tensile strains at the bottom of the bituminous layers calculated with BISAR.

509

150

100

εx (μm/m)

50

0 –2,5

–1,5

–0,5

0,5

1,5

2,5

–50

–100

–150 Distance to the joint (m) JT 1_1

JT 2_1

JL 1_2_1

JL 5_6_1

Figure 6. Tensile strains in the bottom of the bituminous layers calculated with FLAC 3D (FWD tests at the joint). 0,8 0,6 0,4

σx (Mpa)

0,2 0,0 –2,5

–1,5

–0,5

0,5

1,5

2,5

–0,2 –0,4 –0,6 –0,8 Distance to the loading plate centre (m) Slab 1

Figure 7.

Slab 2

Slab 3

Slab 4

Slab 5

Slab 6

Horizontal stresses at the bottom of the concrete slab calculated with BISAR.

joint load transfer conditions. In the pavement models where the joints are taken into account, the tensile strains at the bottom of the asphalt overlay increase significantly, with respect to the results obtained with a continuous model (this increment is about 10 to 100 times). 510

0,8 0,6 0,4

σx (MPa)

0,2 0,0 –2,5

–1,5

–0,5

0,5

1,5

2,5

–0,2 –0,4 –0,6 –0,8 Distance to the joint (m) JT 1_1

JT 2_1

JL 1_2_1

JL 5_6_1

Figure 8. Horizontal stresses across the joint at the bottom of the concrete slab calculated with FLAC 3D due to a FWD load at the joint.

The results presented in figures 5 to 8 illustrate the importance of taking into consideration the presence of joints when calculating the response of reinforced jointed concrete pavements to loads. Figures 5 and 6 demonstrate that, depending on the load transfer at JCP joints, significant values of horizontal tensile strains are induced at the bottom of the asphalt layer above the joint. As expected, Figure 8 shows that the horizontal tensile stresses at the bottom of the concrete slab above the joint are null, due to the presence of the joint. However, these stresses must be taken into account for design purposes, when the load is applied in the slab’s central area. The horizontal stresses at the bottom of the concrete slab, calculated with the BISAR software, are presented in Figure 7. Figure 8 shows the horizontal stresss across the joint, at the bottom of the concrete slab, determined by FLAC 3D for a load applied above the joint. The figures illustrate the difference between a model where the joints are incorporated and another model where the pavement is assumed to be a continuous system in the horizontal direction.

5

CONCLUSIONS

This paper concerns the use of advanced numerical models for the analysis of a jointed concrete pavement with an asphalt overlay. It presents the results obtained with BISAR and FLAC 3D software, for comparison of pavement structural responses, due to vertical loads applied at the pavement surface in the centre of the slab (continuous horizontal layers), and in the vicinity of the joints. When the loads are applied near a joint, the finite difference model calculates tensile stresses and strains in the asphalt overlay that are not negligible. It is important to notice that the horizontal tensile strains in the bottom of the asphalt layers are a design parameter for this type of structures, which are similar to semi-rigid pavements. From the works developed in this study, it is possible to conclude that the design of asphalt overlays on rigid pavement should be made according to the following criteria: 511

• limitation of the tensile stresses in the bottom of the concrete slabs; • limitation of the tensile strains in the bottom of the bituminous layers, when the load is acting in the vicinity of the joint. The models used for the calculation of the design parameters, should be able to model the system response near the joint adequately. REFERENCES Lemos, J.V.—“Modelling and Failure Analysis in Rock Engineering”. Lisbon, Portugal, 2001. Itasca—“Fast Lagragian Analysis of Continua. Theory and Background.” Minneapolis, Minnesota, USA, 2005. Fontul, S.—“Structural Evaluation of Flexible Pavements Using Non-Destructive Tests”. Dissertation developed at Laboratório Nacional de Engenharia Civil, submitted to the Universidade de Coimbra for the Degree of Doctor of Philosophy in Civil Engineering, in the frame of the cooperation between UC and LNEC.

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Development and testing of low noise pavements in Norway J. Aksnes & R.G. Saba Norwegian Public Roads Administration, Technology Division, Trondheim, Norway

T. Berge SINTEF ICT, Department of Acoustics, Norway

ABSTRACT: A research and development project named ‘environmentally friendly pavements’ is being conducted under the auspices of the Norwegian Public Roads Administration and in close cooperation with research institutions and the road industry. The project focuses on the noise and dust properties of road surfaces. The project was started in 2004 to be completed in 2008. The project aims to optimize the environmental properties of road surfaces and thereby contribute to achieving the national targets set for levels of noise and suspended matter (road dust). A central part of the project is the development of low noise asphalt surfacing adapted to Norwegian conditions. Under the project, a wide range of test pavements have been constructed and are being monitored. The effect of reduced maximum aggregate size in ordinary pavements is investigated. Further two sections with one layer porous pavements and three sections with twin layer porous pavements have been constructed. Different types of thin layer pavements are also being tested. Description of selected test pavements and results from field measurements is presented in this paper. 1

INTRODUCTION

The Norwegian Public Roads Administration started a research and development project on environmentally friendly pavements in 2004. The objectives of the project were to reduce noise and dust originating from road-tire interaction by optimizing the acoustic properties of surfacing materials as well as improving their resistance to wear. Pavement wear caused by the use of studded tires in winter times is a major cause of rutting in asphalt pavements in Norway and other Nordic countries. The problem of pavement wear due to studded tires has been extensively studied in the 1970s and 80s. As a result of this work several measures were introduced to reduce the wear including the use of large and hard stone materials in the asphalt, development of so-called environmental studs, development of studfree winter tires and introduction of fee for using studded tires in some urban centres. The use of asphalt mixtures with relatively large maximum aggregate size as surfacing materials has however resulted in another environmental problem; namely noise. Owing to the rough surface texture resulting from the use of large aggregate sizes, these pavements generate significantly more noise compared to asphalt pavements with lower maximum aggregate sizes. Road traffic noise has become one of the major environmental problems. In Norway, about 1.4 million people are exposed to road traffic noise levels exceeding the acceptable limit of 55 dB(A). This accounts for 79% of the noise annoyance expressed in terms of noise annoyance index. In the last few decades attempts have been made, in several countries, to mitigate the problem of road traffic noise through the use of low noise pavement surfaces and noise barriers. However, noise barriers have not been effective particularly in urban setting where high rise buildings lie close to the streets. Therefore, emphasis has been placed on the development and use of low noise pavements. Several types of pavement surfaces with varying levels of desirable acoustic properties have been developed. These pavement surfaces include porous asphalt pavements, thin pavements, surface 513

treatments, poroelastic surfaces, etc. Porous asphalt was considered to be the most effective in terms of noise reduction and was tried in many countries. While some countries report to have successfully used porous asphalt pavements, many others have reported loss of noise reducing property of the porous asphalt due to clogging of the pores with dust and detritus. In Norway, a major research project was initiated 1990 by Norwegian Public Roads Administration on low noise road surfacing, particularly porous asphalt pavements. The objective was to establish mix design for low noise road surfacing under urban conditions. Field test sections were constructed in several places and their performance in terms of noise reduction and other pavement performance indicators was studied. The study concluded that it is possible to obtain noise reduction of up to 5 dB(A) by using porous asphalt compared to the conventional dense asphalt wearing course (Arnevik and Storeheier 1994). It also noted that friction levels on porous pavements are approximately the same as those on dense wearing course. The main problem identified in the study was the clogging and that the available technology did not allow effective cleaning of the pores to maintain the noise reducing properties of the porous pavement. As a result of the use of studded tires, the problem of clogging can be severe. Because of the clogging problem, the Norwegian experiment on the use of porous asphalt was considered unsuccessful and the traffic noise problem remained largely untouched. Since the end of the project however, several developments took place in other countries; including the development of low noise thin pavements and twin layer porous asphalt. These pavements have been used successfully in a number of countries (Bendtsen 2002). The current project therefore aims to evaluate these low noise pavements for use under Norwegian conditions and to come up with needed improvements to make them more suitable to prevailing road, traffic and climatic conditions in Norway. This paper gives the description of the test sections and the results of noise measurements. 2

THE TEST SECTIONS

Test sections were built at several locations and on various kinds of roads in Norway. Summary information for the test sections is provided in Table 1. Results from these locations are reported in this paper. Table 1.

Test sections.

Location

Surface name

Layer information

Binder type

Void content

Thickness (mm)

1

AC6 T8g Wa8 Da11

Dense Dense, with rubber Porous, single layer Porous, single layer

PG 64-28 PG 64-28 PG 64-28 PG 64-28

2,9 9,8 23,3 21,4

25 25 30 30

2

SMA16 SMA11 SMA8 SMA6

Dense Dense Dense Dense

70/100 70/100 70/100 70/100

3,1 3,3 3,7 3,0

45 40 25 25

3

SMA11 SMA8 SMA6 AC11 AC8 AC6

Dense Dense Dense Dense Dense Dense

70/100 70/100 70/100 70/100 70/100 70/100

3,2 2,5 3,8 2,4 3,6 3,2

30 30 30 30 30 30

4

SMA11 Da11 DaFib8/DaFib16 ViaQ11/ViaQ16 Wa8/Da16

Dense Porous, single layer Porous, twin layer Porous, twin layer Porous, twin layer

70/100 SP 60 Bitulastic with wax Cariphalte DA/70/100 Nynäs P06-311-01

3,5 19,5 17,7/17,5 15,0/20,4 14,3/9,5

40 50 30/45 35/45 40/45

514

3

MEASUREMENT OF NOISE

All measurements have been made with a CPX-trailer, owned by the Norwegian Public Roads Administration. Figure 1 shows the picture of the trailer. The trailer was built in 2005 by M + P Noise & Vibration engineering, a Dutch company. The trailer is fixed with an absorptive enclosure, with two microphones on the inside of the enclosure, close to each of the two tires fitted to the trailer. The measurements were made according to ISO/CD 11819-2, a proposed ISO standard procedure for close proximity measurements, using the reference tire A (Avon ZV1). Tire A is chosen to be representative of the passenger car traffic on the road. The method is currently under revision, including a selection of new reference tires. At three of the locations reported here, measurements have been made every year from 2005 to 2008. This means that the test surfaces on these locations have been exposed to three winter seasons. At location 4, the surfaces were laid in 2006, so they were exposed to the influence of two winter seasons only. Measurements were conducted at both 50 and 80 km/h. Since the majority of the houses exposed to traffic noise in Norway are close to roads with a speed limit less than 80 km/h, it was necessary to investigate the noise reduction potential of the road surfaces also at 50 km/h. At location 3, the speed limit is 60/70 km/h, so measurements at this location were only made at 50 km/h. The test sections at location 1 and 2 were not measured at 50 km/h in 2005 and 2006, therefore only the results at 80 km/h are reported here.

4

RESULTS OF NOISE MEASUREMENTS

This section presents the results from the noise measurements. The reported noise level is, according to the ISO-standard, the average level over the measured distance, LA + 1.0 dB(A) (CPXcars). All levels are the average of left and right wheel track, as well as the average of

Figure 1.

The CPX-trailer.

515

Location 1, 80 km/h 104

CPXcars, dB(A)

102 100 98 96 94 92 90 0

1

2

3

Year Reference

Figure 2.

AC6

T8g

Wa8

Da11

Noise measurement results at location 1 at 80 km/h.

Location 2, 80 km/h 104

CPXcars, dB(A)

102 100 98 96 94 0

1

2

3

Year SMA16

Figure 3.

SMA11

SMA8

SMA6

SMA11

Reference

Noise measurement results at location 2, at 80 km/h.

both lanes (except for location 3, where measurements were made in one lane only). At all locations, the measurements were repeated two times and the results are averaged. All levels have been temperature corrected to +20°C, using the correction formula of –0.06 dB/°C. The air temperature during the measurements was in the range of +17 to +25°C. This temperature range gives a correction in the order of 0.2–0.3 dB(A). Figures 2 to 6 show the measurements results at the 4 locations reported here. At location 1 and 2, measurements have only been made at 80 km/h and at location 3, only at 50 km/h. 516

Location 3, 50 km/h 96.0

CPXcars, dB(A)

94.0 92.0 90.0 88.0 86.0 84.0 0

1

2

3

Year AC8

Figure 4.

SMA8

AC11

SMA11

AC6

SMA6

Reference

Noise measurement results at location 3 at 50 km/h.

Location 4, 50 km/h 96.0

CPXcars, dB(A)

94.0 92.0 90.0 88.0 86.0 84.0 82.0 0

1

2

Year SMA11

Figure 5.

DaFib8/16

ViaQ11/16

Wa8/Da16

Da11

Reference

Noise measurement results at location 4 at 50 km/h.

As a reference value, an average level of a range of measurements on dense surfaces with maximum aggregate size of 16 mm has been chosen. Based on the reference tire A, this reference value is 94.1 dB(A) at 50 km/h and 101.7 dB(A) at 80 km/h. The results are influenced by the repeatability of the measurements. To investigate this, 5 consecutive runs were made on the pavements at location 4 in year 2. Table 2 shows the results on the Da11-surface. Figure 7 and 8 show the variations in each of the runs for right and left side of the trailer. 517

Location 4, 80 km/h 104.0

CPXcars, dB(A)

102.0 100.0 98.0 96.0 94.0 92.0 90.0 0

1

2

Year SMA11

Figure 6.

Table 2.

DaFib8/16

ViaQ11/16

Wa8/Da16

Da11

Reference

Noise measurement results at location 4 at 80 km/h.

Repeatability test at location 4, Da11, 80 km/h. Lane 1

Lane 2

Right side

Left side

Right side

Left side

Run

Level

St. dev

Level

St. dev

Level

St. dev

Level

St. dev

1 2 3 4 5

100.1 99.8 100.0 99.7 100.1

0.47 0.53 0.35 0.58 0.41

99.9 99.8 99.5 99.6 99.5

0.34 0.34 0.24 0.24 0.35

99.4 99.3 99.4 99.1 99.2

0.49 0.44 0.43 0.42 0.42

99.6 99.5 99.4 99.5 99.7

0.44 0.23 0.21 0.23 0.29

CPX-level, dB(A)

Da11, Lane 2, Right side

102.0 101.5 101.0 100.5 100.0 99.5 99.0 98.5 98.0 40

100

Run 1 Figure 7.

160

Run 2

220 280 340 Distance, m Run 3

Da11: repeatability of 5 runs. Right side, 80 km/h.

518

Run 4

400

460

Run 5

CPX-level, dB(A)

Da11. Lane 2, Left side

102.0 101.5 101.0 100.5 100.0 99.5 99.0 98.5 98.0 40

100

160

220

280

340

400

460

Distance, m Run 1 Figure 8.

Run 2

Run 3

Run 4

Run 5

Da11: repeatability of 5 runs. Left side, 80 km/h.

The results of this test show a good repeatability for the CPX-measurements concerning the average noise level. The standard deviation for this pavement is in the range of 0.2–0.6 dB(A). The maximum difference is 0.4 dB(A) for the left side. The results of the other pavements at this location show similar results.

5

DISCUSSION OF NOISE MEASUREMENT RESULTS

The noise measurement results show that reduced maximum aggregate size in dense asphalt mixes gives a significant noise reducing effect. However, with a few exceptions, there is a considerable increase in the noise levels over time. Most of the change comes during the first winter, and later on it seems to stabilize somewhat. On average, the noise levels have increased by approximately 2–4 dB(A) after three winter seasons. The change is biggest for the mixes with the smallest maximum aggregate size. The observed increase in noise levels is probably due to use of studded tires during the winter times in Norway. At the locations presented in this paper, the percentage of cars using studded tires was approximately 50%. The best double layer porous asphalt layer seems to give a reduction of about 2.5–3 dB(A) after two winter seasons, compared to the chosen reference. At location 4, it is interesting to observe that one of the twin layer porous asphalt surfaces, the ViaQ11/ViaQ16 has retained its initial noise level at 50 km/h and almost also at 80 km/h after the first winter season. This twin layer porous asphalt surface with 11 mm maximum aggregate size in the top layer seem to perform acoustically very well, also after being exposed to one winter season. However, after the second winter, the clogging effect seems to have reduced most of the sound absorbing effects of all the porous surfaces. One of the other twin layer surfaces (DaFib8/DaFib16), has changed considerably with an increase in noise of more than 6 dB(A) and this is probably due to some adhesion problem causing stripping of the surface. It should be noted that these reduction estimates are related to passenger cars only, due to the measuring method described in section 4. It is likely that the overall traffic noise reduction will be somewhat lower, because truck tires/truck noise is less influenced by a porous surface than light vehicles. Measurements according to the statistical pass-by method (ISO 1997) have been performed at location 4 and will be used for further analysis of the acoustical performances of the test surfaces. 519

6

CONCLUSIONS AND RECOMMENDATION

Noise measurement results presented in this paper show that pavements with reduced maximum aggregate size can reduce noise by about 1–2 dB(A) in the speed range of 50 to 80 km/h compared to the reference surface. The best performing twin layer porous asphalt gave a reduction in noise of about 4 dB(A) after the first winter season, but reduced to approximately 2.5–3 dB(A) after the second. A noise reduction of about 3 dB(A) is obtained from a single layer porous asphalt after one winter, but reduced to approximately 1 dB(A) after the second, compared to the reference. The performance of the tested pavements in terms of noise reduction appears to diminish quite fast after exposure to winter and the use of studded tires. The challenge, therefore, is to find ways of making the low noise pavements durable in terms of their acoustic performance. Currently further monitoring of the test pavements is underway to draw firm conclusions with regard to their acoustic performance. REFERENCES Arnevik, A. & Storeheier, S.Å. 1994. Low noise road surfacings: summary report. Oslo: Norwegian Public Roads Administration. Bendtsen, H., Larsen, L.E. & Griebe, P. 2002. Development of noise reducing road pavements for urban streets: status report after 3 years of measurement (in Danish). Copenhagen: Danish transport research. ISO 11819-1. 1997. Acoustics—Measurement of the influence of road surfaces on traffic noise—Part 1: Statistical Pass-By Method. ISO/CD 11819-2.2000. Acoustics—Measurement of the influence of road surfaces on traffic noise— Part 2: The Close Proximity Method. (Under preparation/revision)

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Roughness progression models by regression and artificial neural network techniques E. Taddesse & H. Mork Norwegian University of Science and Technology (NTNU), Trondheim, Norway

ABSTRACT: Pavement deterioration models are crucial components of a Pavement Management System (PMS). As a matter of fact most empirical deterioration progression models developed to date have had limited success, especially outside the location they were developed. This paper deals with the development of flexible pavement roughness progression models, expressed in terms of International Roughness Index, from PMS data of the Ethiopian road network, using Multi-Linear Regression (MLR) and Artificial Neural Network (ANN) techniques. The possible use of Light Weight Deflectometer surface deflection modulus variable in the models instead of the uncertain pavement base course thickness is investigated and verified. A comparative study was also made between the MLR and ANN models, and the results from this research effort demonstrated that the ANN models outperform the MLR models. 1

INTRODUCTION

Due to the increasing challenges in pavement maintenance and rehabilitation, a Pavement Management System (PMS) has become a very beneficial management tool for highway agencies. Quality pavement performance models have been recognized to be critical for successful application of a PMS around the world. As a result, an increasing research interest thrives in improving performance of pavement deterioration models. The inventory database established in the initial stage of a PMS provides researchers an indispensable data resource for the development of the quality pavement performance models (Yang 2004). In this study pavement roughness models for the Ethiopian road network, expressed in terms of the International Roughness Index (IRI) are developed, using statistical Multi-Linear Regressions (MLR) and Artificial Neural Network (ANN) techniques. The models relate IRI with the widely accepted variables on which pavement deterioration mainly depends, i.e. traffic, pavement thickness, climatic condition and structural capacity. A preliminary study based on a limited amount of Norwegian measurements showed rather promising results with regard to relating LWD ‘surface deflection modulus’ (LWD_E) to overall pavement condition (Taddesse 2007). As part of a work to develop deterioration models for Ethiopian conditions, it was therefore decided to carry out LWD measurements on selected roads included in the Ethiopian PMS database, where variables as traffic, environment, layer thicknesses etc. were known, and with more or less complete time series of IRI measurements. The hypothesis was that the surface deflection modulus derived from the LWD measurements would significantly enhance the prediction of IRI on these roads, or at least that the LWD modulus, without a significant loss of accuracy, could replace the layer thicknesses in the prediction models. 2

ROUGHNESS AND POSSIBLE INFLUENCING FACTORS

From analyses of performance models in the literature, it is evident that the pavement deterioration over time mainly depends on four global variables, i.e. traffic, pavement, climatic condition and structural capacity. These variables help to define the pavement roughness progression (Thube et al. 2007). 521

Roughness is a measure of the ride quality of pavements. It is expressed in terms of International Roughness Index, which is the outcome of a World Bank’s experiment in Brazil in 1982 (Paterson 1987). Usually IRI varies from 0 to 10 for paved roads, 0 being an absolute perfect surface (Sayers et al. 1986). Pavement age—As a fact, pavements deteriorate with time. Hence, age is considered in the developed model, computed from the day the road was opened to traffic after construction or the most recent major rehabilitation. Pavement layer thicknesses—Variation in layer thickness can result in variations in the structural characteristics and in-service performance of pavements (Attoh-Okine et al. 1994). Hence, the top two layers in the pavement structure are considered in the model, i.e. AC thickness and base course thickness. For Ethiopian conditions, the asphalt thicknesses are relatively accurately known, which is not the case for base course thicknesses, which show quite significant variation and uncertainty in their values. To account for this uncertainty, an attempt was made to check if the surface deflection modulus from LWD (refer paragraph below) could successfully replace the base thickness in the prediction models. Pavement strength—Nondestructive testing methods such as Falling Weight Deflectometer, Light Weight Deflectometer, Benkelman beam etc. complemented with other evaluation techniques are commonly used to determine the structural adequacy and condition of pavements. In the Ethiopian road databank no such data is found, except very few Benkelman beam measurements. As mentioned earlier, LWD ‘surface deflection modulus’ can reasonably well tell the overall pavement strength, and the equipment is easy to operate, versatile and affordable. Traffic loading—Pavements deteriorate mainly from traffic and environmental factors; hence traffic loading is an important variable in predictions models. Environmental factors—Environmental data collected from the Ethiopian Meteorological Agency used in the model are, monthly max temperature and precipitation along the selected roads.

3

DATA COLLECTION AND FIELD TESTING

Data was collected from many sources during a field work in the spring of 2008. They are from Ethiopian Roads Authority (ERA) Pavement Management Branch, which now runs the PMS, Environmental data from the Ethiopian Meteorological Agency and field tests at six selected roads using LWD. The Ethiopian road network consists of about 36500 km of Federal and Regional roads (from which about 5000 km are asphalt roads) and 30000 km of unclassified roads. The PMS was established in 1997 with the assistance of the World Bank (BCEOM 1997). After a thorough study of the whole database, six AC paved roads with sufficient IRI data, located in different parts of Ethiopia, are selected for the model development. In ERA PMS, IRI is measured using TRL bumper integrators along the whole length of the roads, and readings are summarized for each 500 m section (BCEOM 1997). IRI should steadily increase with time unless there is some external interference. This rationale was used to check any abnormal breaks in the time sequence of the IRI data. Using this criterion, 322 sections with complete time series of IRI measurements are selected from these six roads. From the 322 sections, 73 sections are randomly selected for LWD measurements. Typical IRI data from the Mojo-Nazareth road are shown in Figure 1 (14 sections). The traffic data collected is in terms of Average Annual Daily Traffic (AADT) for nine vehicle categories. A further simplification was made with only four categories to fit in the axel load configurations used by ERA: Car, Buses, Trucks, Truck and Trailer. The AADT data are converted to Equivalent Standard Axle Loads (ESALs), the variable used in the models, using the procedure outlined in (TRL 2004). 522

Mojo-Nazareth A1-2

6.00 5.00 04.12.2006 02.10.2006 3.00 17.02.2006 2.00 10.12.2004

Time

IRI (m/km)

4.00

1.00 12.04.2003 0.00 500

1500

2500

4500

5500

9500

12000

Station

12.04.2003

Figure 1.

4

10.12.2004

17.02.2006

02.10.2006

04.12.2006

Typical IRI measurement data from ERA databank.

MODEL DEVELOPMENT

In order to test the hypothesis that the LWD_E enhances the models predictions, the following cases are considered: Case 1—model without LWD_E and with base thickness (73 sections) Case 2—model with LWD_E and without base thickness (73 sections) Case 3—model using the whole dataset (no LWD_E; 322 sections) Statistical MLR and ANN methods are used for the model development, and a comparison between them is also made. 4.1 Statistical multi-linear regression analysis Results from MLR analysis using SPSS software are explained here. Table 1 shows the coefficients of the regression models for each case together with the models summary results. It reports the strength of the relationship in the variables. R, the multiple correlation coefficient, Table 1. MLR model coefficients and model summary. Variable

Case 1

Case 2

Case 3

(Constant) Age (years) AC thickness (cm) ESAL (msa) Max temp (oC) Precip (mm) Base thickness (cm) LWD_E (MPa) R R Square

2.422 0.445 –0.056 0.014 0.018 0.001 –0.055 – 0.764 0.584

0.936 0.449 –0.046 0.013 0.039 0.002 – –6.51E-4 0.788 0.621

2.291 0.384 –0.105 0.019 0.020 9.3E-4 –0.019 – 0.742 0.613

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is the linear correlation between the observed and model-predicted IRI values. Its large value of above 0.74 in all the models indicates a strong relationship. The ANOVA (Analysis of Variance) table tests the acceptability of the model from a statistical perspective (Table 2). The regression and residual sums of squares and R Square, the coefficient of determination, show that 58.4%, 62.1% and 55.1% of the variation in IRI is explained by the models in cases 1, 2 and 3, respectively. A histogram plot of the residuals helps to check the assumption of normality of the error term. Its shape should approximately follow the shape of the normal curve. The histograms for the dependent variable (IRI) shown in Figure 2, Figure 3 and Figure 4 are acceptably close to the normal curve, which indicates that the normality assumption is not violated. 4.2 Artificial neural networks Neural Networks (NN) are named after the cells in the human brain that perform intelligent operations. They are recently becoming the preferred tool for many predictive applications because of their power, flexibility and ease of use. They are particularly useful in applications where the underlying process is complex, like in pavement deterioration, as reported in the literature, among others (Carlos et al. 1999; Saltan et al. 2002; Ceylan et al. 2004; Choi et al. 2004; Bayrak et al. 2005).

Table 2. ANOVA—sum of squares error. Case 1

Case 2

Case 3

Regression 173.568 184.698 637.222 Residual 123.875 112.744 519.363 Total 297.442 297.442 1156.585

Figure 2. Histogram of residuals of IRI from regression CASE 1.

Figure 3. Histogram of residuals of IRI from regression CASE 2.

Figure 4. Histogram of residuals of IRI from regression CASE 3.

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4.2.1 Introduction An Artificial Neural Network (ANN) consists of three key components, the Architecture, the Neuron Activation Function and the Learning Algorithm which should be determined before solving any particular problem (Fausett 1994). Architecture refers to the specification of the number of layers in a neural network and the number of neurons per layer, along with activation functions and network error function. A typical three layered neural network with one output neuron is shown in Figure 5. The input layer contains the predictors, the hidden layer contains unobservable nodes or units, and the output layer contains the responses. Neural Activation Function—NNs are known to be of the kind “distributed parallel computation” algorithm because of the independence property of neurons (Fausett 1994). A typical neuron (PE) on a hidden layer is shown in Figure 6. As can be noticed, the processing of each neuron simply involves a weighted summation (Linear Map) given by: For a hidden layer

For an output layer m

n

netk = ∑ y j w jk

net j = ∑ xi wij

(1)

j =1

i =1

In addition, it involves an instantaneous nonlinear map that transforms the weighted summation values (netj and netk) to the output variable (yj or ok), given by: For a hidden layer

For an output layer

⎛ n ⎞ y j = f ( net j ) = f ⎜ ∑ xi wij ⎟ ⎝ i =1 ⎠

⎛m ⎞ ok = f ( netk ) = f ⎜ ∑ y j w jk ⎟ ⎜ j =1 ⎟ ⎝ ⎠

(2)

where, i = number of units in the input layer (i = 1 … n), j = number of units in the hidden layer (j = 1 … m), k = number of units in the output layer (k = 1 … l), xi = ith element in the input vector, and, wij = weight for the ith input to the jth unit in the hidden layer, yj = jth neuron output in the hidden layer, ok = kth neuron output in the output layer, netj or k = input to the transfer functions.

Input layer

Hidden layer

Output layer

y1

x1

y2 x2

xn

. . .

. . .

ok

ym

Figure 5. A typical three layered feed-forward neural network.

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Figure 6. Typical artificial neuron (PE) on hidden layer.

A number of neuron activation functions are used depending on the problem under study. The most common ones are Identity, Hyperbolic tangent and Sigmoid functions. Learning Algorithms—The learning capability of ANN is achieved by adjusting the signs and magnitudes of their weights according to learning rules that seek to minimize a cost or error function. The Back-propagation (BP) of errors is the most widely used learning method in neural network modeling (Lippmann 1987). Inputs from the mapping examples are propagated forward through each layer to emerge as outputs. The differences between those outputs (actual response) and the correct answers (desired responses) are then propagated backwards through the network, and the connection weights are individually adjusted so as to reduce the error. During the training of the neural network, two error types (Sum of Squares and Relative Error) are calculated, which are the measures that the neural network tries to minimize to acceptable levels by iterations. The Sum of Squares error is calculated using the formula: s

ET (w ) = ∑ Er (w ) ;

E r (w ) =

r =1

1 l ∑ Tk(r ) − ok(r ) 2 k =1

(

)

2

(3)

where ET(w) = sum of squares of the output error for all training cases, Er(w) = square of output error for a single input case, s = number of cases in the data sample, l = number of neurons in the output layer; Tk(r) = target value of neuron k for case r; and ok(r) = output of neuron k for case r The Relative Error (RE) is computed using the formula: s

RE =

l

∑ ∑ (Tk(r ) − ok(r ) ) r =1 k =1 s l

_ ⎞ ⎛ ∑ ∑ ⎜⎝Tk(r ) − ο k ⎟⎠ r =1 k =1

2

2

(4)

where ōk is the mean of ok(r) over all cases (patterns). Optimization Algorithm is the method used to estimate and adjust the connection (synaptic) weights (wij). The most widely used supervised learning algorithms are the Gradient Decent and Scaled Conjugate Gradient algorithms. In this research, Scaled Conjugate Gradient (SCG) algorithm is adopted for the optimization process. As opposed to gradient decent method where learning rate and momentum term has to be decided by the user (Attoh-Okine 1999), SCG is fully automated including no user dependent parameters, and avoids a time consuming line search, which the gradient decent algorithm uses in each iteration in order to determine an appropriate step size (Møller 1990). 4.2.2 ANN modeling In building ANNs, it is not clear as to how many hidden layers and nodes are needed, however it was proved from several studies that one hidden layer with sufficient nodes is capable of representing any mapping (Choi et al. 2004). The SPSS Neural Network software is adopted for the ANN model development (SPSS 2007). For all our modeling cases, all possible combinations of activation functions between hidden and output layers were tested, and the hyperbolic tangent function for hidden layer neurons and the sigmoid function for the output layer neuron give the least amount of errors. After choosing the activation functions, the optimum number of units in the hidden layer was found by simply running the NN training program varying the number of units in the hidden layer from one to 20. The results of this task are depicted in figures 7, 8 and 9. As can be noticed, the errors and goodness-of-fit values after 9 units (neurons) in the hidden layers show very little difference. Hence the following architectures are selected for the respective cases: Case 1: 6-14-1, case 2: 6-12-1 and case 3: 6-13-1. In this research, a random selection of 70% of the dataset is used for training, 20% for testing and 10% for validation. 526

Training

Training

1.8

0.5

0.85

Testing

Testing

0.8

validation

1.6 1.4

0.75

1.2 1

R-squared

0.4 Error

Error

Goodness-of-fit

Relative error

Sum of squares error 2

0.3

0.7 0.65

0.8 0.6

0.6

0.2 0.55

0.4 0.2 0

2

4

6

0.5

0.1

8 10 12 14 16 18 20

0

2

No. of units in hidden layer

Figure 7.

0

4 6 8 10 12 14 16 18 20 No of units in hidden layer

2

4 6 8 10 12 14 16 18 20 No. of units in hidden layer

Plots of errors and goodness-of-fit graphed with no. of units on hidden layer for case 1.

Sum of squares error

Relative error

1.6

0.6

Testing

1.4

Goodness-of-fit 0.85

Training Testing validation

Training 0.5

0.8

R-Squared

0.4

1 Error

Error

1.2

0.8

0.3

0.75

0.7

0.6 0.2

0.65

0.4 0.2

0.1

0

2

4

6

8 10 12 14 16 18 20

0.6

0

No. of units in hidden layer

Figure 8.

2

4

6

8 10 12 14 16 18 20

2

4

6

8 10 12 14 16 18 20

No. of units in hidden layer

Plots of errors and goodness-of-fit graphed with no. of units on hidden layer for case 2.

Sum of squares error

Goodness-of-fit

Relative error

7 Testing

0.85

Training Testing validation

Training 6

0

No. of units in hidden layer

0.45

0.8 0.75 R-Squared

5

0.35

Error

Error

4

3

0.65 0.6

0.25

2

0.7

0.55

1

0.5

0.15

0 0

2

Figure 9.

4 6 8 10 12 14 16 18 20 No. of units in hidden layer

0

2

4

6

8

10 12 14 16 18 20

No. of units in hidden layer

0

2 4

6 8 10 12 14 16 18 20

No. of units in hidden layer

Plots of errors and goodness-of-fit graphed with no. of units on hidden layer for case 3.

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4.2.3 Validation of the ANN models After training and testing the ANN, the last step is to verify the performance of the network with an out-of-sample dataset. For this purpose a validation dataset of 10%, as explained in section 4.2.2, was set aside during the training and testing phases. IRI predictions were carried out using this dataset, the results of which are depicted in Figure 10 for cases 1, 2 and 3. It can easily be seen that the ANN models predictions correlate very well with the actual measurements. 4.3 Discussion of results The first two cases were meant to investigate the possibility of using LWD_E values instead of base thicknesses. The results actually verify that, this replacement enhances the prediction in the regression models, where the R-squared value increased from 0.584 to 0.621 (cases 1 and 2), refer Figure 11a and Figure 12a. However, in the ANN models they are almost equal (0.847 and 0.839), as shown in Figure 11b and Figure 12b. The same set of data was utilized during the model development in both MLR and ANN methods. Figures 11, 12, and 13 show scatter plots of actual versus predicted IRI values using regression and ANN models for the three cases. Evidently, the ANN models have produced results that are much better than those from MLR. The coefficients of correlation indicate that the ANN models have better generalization capability than the MLR (R-squared for case 1, 2 and 3 using MLR are 0.584, 0.621 and 0.613, and using ANNs they are 0.847, 0.839 and 0.821, respectively). The results clearly show that the ANN models outperform the MLR models.

Actual versus predicted IRI using validation dataset - case 1

6

5

Predicted IRI

5

Predicted IRI

Actual versus predicted IRI using validation dataset - case 2

6

4

3

2

4

3

2 R Sq Linear = 0.761

R Sq Linear = 0.725

1

1 1

2

3 4 Actual IRI (m/km)

5

6

1

2

3 4 Actual IRI (m/km)

Actual versus predicted IRI using validation dataset - case 3 6

Predicted IRI (m/km)

5

4

3

2 R Sq Linear = 0.538 1 1

Figure 10.

2

3 4 Actual IRI (m/km)

5

Actual versus predicted IRI using validation dataset.

528

6

5

6

Actual versus predicted IRI by regression - Case 1

Actual versus predicted IRI by ANN - Case 1

6

6 A1-1

A1-1

A1-2

A1-2

A7-1

A7-1

5

A3-1

5

A3-1

A1-5

A1-5

A1-6

Predicted IRI (m/km)

Predicted IRI (m/km)

A1-6

4

3

4

3

2

2

R Sq Linear = 0.584

R Sq Linear = 0.847 1

1 1

2

3

4

5

1

6

2

3

a)

Figure 11.

5

6

b)

Scatter plots of actual versus predicted IRI values for case 1; a) by regression, b) by ANN.

Actual versus predicted IRI by regression - Case 2

Actual versus predicted IRI by ANN - Case 2 6

6

A1-1

A1-1

A1-2

A1-2

A7-1

A7-1

5

5

A3-1

A3-1 A1-5

A1-5

A1-6

A1-6

Predicted IRI (m/km)

Predicted IRI (m/km)

4

Actual IRI (m/km)

Actual IRI (m/km)

4

3

4

3

2

2

R Sq Linear = 0.839 R Sq Linear = 0.839

R Sq Linear = 0.621 R Sq Linear = 0.621 1

1 1

2

3

4

5

1

6

2

3

a) Figure 12.

4

5

6

Actual IRI (m/km)

Actual IRI (m/km)

b)

Scatter plots of actual versus predicted IRI values for case 2; a) by regression, b) by ANN. Actual versus predicted IRI by ANN - case 3 Actual versus predicted IRI by regression - case 3 A1-1 A1-1

6

A1-2

6

A1-2

A7-1

A7-1

A3-1

A3-1

Predicted IRI (m/km)

Predicted IRI (m/km)

5

A1-5

5

A1-5 A1-6

4

3

A1-6

4

3

R Sq Linear = 0.613

R Sq Linear = 0.821

2

2

R Sq Linear = 0.613

R Sq Linear = 0.821

1

1 1

2

3

4 Actual IRI (m/km)

5

6

1

a) Figure 13.

2

3

4 5 Actual IRI (m/km)

6

b)

Scatter plots of actual versus predicted IRI values for case 3; a) by regression, b) by ANN.

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5

SUMMARY AND CONCLUSION

Flexible pavement deterioration models, expressed in terms of International Roughness Index, were developed from Pavement Management System data of the Ethiopian road network, using Multi-linear Regression (MLR) and Artificial Neural network (ANN) techniques. Neural networks are recently becoming the preferred tool for many predictive applications because of their power, flexibility, and ease of use. They are particularly useful in applications where the underlying process is complex, like in pavement deterioration. The widely accepted four global variables on which pavement deterioration mainly depends are included in the model, i.e. traffic, pavement, climatic condition and structural capacity. From this research it is concluded that the Light Weight Deflectometer ‘surface deflection modulus’ can successfully replace the base thickness values in the performance models. Comparison of the results between the developed MLR & ANN models showed that the ANN models produced results that are much better than the results from MLR models. The coefficients of correlation indicate that the ANN models have better generalization capability than the MLR (for three different cases of modeling, R-squared using MLR are around 0.6, and using ANNs are around 0.8). This clearly shows that, in this research, the ANN models outperform the regression models. REFERENCES Attoh-Okine, N.O. 1999. Analysis of learning rate and momentum term in backpropagation neural network algorithm trained to predict pavement performance. Advances in Engineering Software 30. Attoh-Okine, N.O., et al. 1994. Pavement thickness variability and its effect on determination of moduli and remaining life Transportation Research Record No. 1449. Bayrak, M.B., et al. 2005. Rapid Pavement Backcalculation Technique for evaluating Flexible Pavement Systems. Mid-Continent Transportaion Research Syposium, Ames, Iwoa. BCEOM 1997. Pavement Management System, Manual for procedures. Addis Ababa. Carlos, F., et al. 1999. Artificial Neural Network-Based Methodologies for Rational Assessment of Remaining Life of Existing Pavements, Texas Department of Transportation. Ceylan, H., et al. 2004. Neural network-based structural models for rapid analysis of flexible pavements with unbound aggregate layers. Sixth International Symposium on Pavements Unbound (UNBAR 6), Nottingham, England. Choi, J.-h., et al. 2004. Pavement roughness modeling using back—propagation neural networks. Computer aided civil and infrastructure engineering (19): 295–303. Fausett, L. 1994. Fundamentals of Neural Networks, Prentice-Hall, Inc. Lippmann, R.P. 1987. An Introduction’ to Computing with Neural Nets. IEEE ASSP MAGAZINE. Møller, M.F. 1990. Scaled Conjugate Gradient Algorithm for fast supervised learning, Computer Science Department, University of Aarhus, Denmark. Paterson, W.D. 1987. Road Deterioration and Maintenance Effects Models for Planning and Management, World Bank. Saltan, M., et al. 2002. Artificial Neural Network Application for Flexible Pavement Thickness Modeling. Turkish J. Eng. Env. Sci. 26. Sayers, M.W., et al. 1986. Guidelines for conducting and calibrating road roughness measurements, World Bank Technical Paper Number 46. SPSS 2007. SPSS Neural Networks 16 Users Manual, SPSS Inc. Taddesse, E. 2007. Comparison of field measurements on Low-Volume Roads in Norway, Norwegian University of Science and Technology (NTNU). Thube, et al. 2007. An Alternative Approach for Modeling and Simulation of Pavement Deterioration Models: Artificial Neural Networks. TRB 2007 Annual Meeting CD-ROM. TRL 2004. Overseas Road Note 40—A guide to axle load surveys and traffic counts for determining traffic loading on pavements. Yang, J. 2004. Road Crack Condition Performance Modeling Using Recurrent Markov Chains And Artificial Neural Networks. Department of Civil and Environmental Engineering, College of Engineering, University of South Florida. PhD.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Joint modeling for JPCP: Successes and pending problems E.H. Guo SRA International, Inc., New Jersey, USA

ABSTRACT: The studies for modeling the load transfer behavior of jointed plain concrete pavements (JPCP) made under Federal Aviation of Administration sponsorship since 1992 and a few earlier works are summarized. Four criteria were used to evaluate joint mechanistic models and to discover deficiencies in the models before improving them. Detailed examples are provided to show how the problems were discovered. Some mechanism related joint behaviors were observed in full scale tests first at the FAA’s National Airport Pavement Test Facility (NAPTF). Then verifications and valid conditions were determined by mechanistic analysis. The combination of the full-scale tests and mechanistic analysis is an effective approach to develop and improve the joint models that have been adopted by the FAA for its new rigid airport pavement design and evaluation procedures. Pending problems in joint modeling and future needs are also discussed. 1

INTRODUCTION

Both empirical and mechanistic joint models are necessary in analyzing the response of concrete pavements with multiple slabs. This paper reviews the development of the mechanistic models in following steps: 1. Separately simulating the behavior for each type of joint, such as saw-cut and doweled; 2. Verifying the validity of each of the models for both saw-cut and doweled joints; 3. Developing a realistic procedure for evaluating joint quality in the field using the results from Falling Weight Deflectometer (FWD) tests; 4. Investigating and proving relationships among three responses at a joint: critical deflections (or stresses) at the loaded side, unloaded side and free edge (zero load transfer); 5. Extending the application of the relationships in (4) from a flat to a curled concrete pavement, and defining the conditions under which the models are valid; 6. A new project under FAA sponsorship has been started to investigate the differences in load transfer under FWD and full-scale aircraft loads. No models exist that are unconditionally valid for all cases. Therefore, it is necessary to find the conditions under which a particular model is valid. Potential deficiencies, even errors, may be present in existing models. If deficiencies or errors are found to be present it is necessary to minimize their effects. Finite element method have now been popularly accepted by pavement engineers, but after the mechanistic joint models are installed in computer programs it is difficult and time consuming to evaluate the accuracy of the models directly using analytical methods. A series of projects on joint modeling have been conducted under FAA sponsorship since 1992. Four criteria were used for detecting potential problems in 2D and 3D models before making detailed modifications to the models. The major objective of this paper is to demonstrate that it is necessary to minimize the deficiencies in existing models before they are applied in pavement design procedures. Also, it is not difficult to find the deficiencies if the four criteria are appropriately used, especially the one concerning the logical examination of results.

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2

FOUR MODEL EVALUATION CRITERIA

Joint modeling is a necessary step to conduct analysis for a concrete pavement with multiple slabs. The model should be capable of simulating the joint behavior under load and environmental variations. The following four criteria have been used to evaluate models during research projects under the FAA’s NAPTF testing program in the past ten years. 2.1 Logical criterion Any result obtained using a model in a computer program must satisfy a logical examination of the result using common knowledge. Otherwise, the accuracy of the model is questionable. 2.2 Theoretical criterion Many theoretically proved closed-form solutions can be easily found in handbooks or text books. These available solutions are usually in a very simple form. All results calculated using a model installed in a program must pass the check by the theoretical solution if the input data are used appropriately. 2.3 Experimental criterion All mechanistic models are developed following four steps: (a) clearly define all parameters used in the model; (b) establish assumptions for the relationship between the parameters, such as linear or nonlinear, recoverable or non-recoverable; (c) mathematically derive the desired relationship between the known input data and the unknown output data; (d) check by comparing the output with experimental results. Full scale test data is the best source to check the validity and reliability of the model. 2.4 Practical criterion Some well developed models rely on many input data defined by the model developer. It is not true that the more complicated a model is, the more reliable it is. A successful model should have a clear procedure for determining the value of the input data rather than leaving the user to derive the procedure. It is acceptable to get the data from laboratory tests or quickly and easily from field tests before using the model in practical applications. This is extremely important for the input data that the calculated responses are sensitive to. Much effort is still needed to develop a procedure for determining the input data for existing models satisfying the first three criteria. 3

APPLICATIONS OF THE FOUR CRITERIA IN JOINT MODEL DEVELOPMENT

There are two types of load transfer in common joints: (a) loads are directly transferred through aggregate interlock or shear forces such as in saw-cut and key joints; (b) in addition to the interlock, a portion of the loads may be transferred through embedded steel bars such as in doweled and tied joints. Therefore, two types of models have been developed and improved over time. The relationship between the two types of models has been theoretically studied and numerically verified. The joint models implemented in current 2D and 3D programs were gradually improved by all investigators who were involved in the development of the models since 1973. Also, all improvements were started from the discovery of existing problems and even errors in the previous models. How those problems were discovered and solved step by step by all contributors is summarized below. 3.1 First model for analyzing multiple-slab pavement The first model capable of analyzing a pavement with multiple slabs under arbitrary loads was presented by Huang et al., in 1973. Deflection ratios have to be given (assumed) at each 532

node at the joint. The model satisfies the first three criteria if the ratios used for prediction are assumed to be the same as the true ones under any load. The easy and realistic application of the model is to assume the ratio to be constant along a joint. However, the deflection ratios always vary along the joint and they are unknown before analysis. The model requires knowing the answers before prediction. Therefore, it cannot pass the practical criterion (4). 3.2 Shear model for load transfer by interlock, the simplest and most popular model It has been recognized for a long time that all types of joint transfer load mainly through shear force and that moment transfer is negligible (Ioannides et al., 2005). Only one parameter, the shear stiffness K of the joint, is used to define the model. The pavement displacements are discontinuous, including deflections and rotations, at the joint. The first shear model used for finite element analysis was published by Tabatabai et al., 1978. The model has been widely used not only in 2D but also in 3D programs (FAA 2008). It never fails to pass the first two criteria (Guo et al., 2003(I)) and partially passes the third criterion—predicted and measured strains match well for most responses except those perpendicular to and near longitudinal joints (Guo et al., 2007). The remaining problems are how to reasonably and quickly determine the joint stiffness K by non-destructive test in the field and how to improve the response prediction near a joint. 3.3 Beam model used for load transfer by dowels An example of a model that fails to pass the logical and theoretical criteria and how it was corrected and finalized is presented in this section. Versions of Jslab earlier than 1992 (Tayabji et al., 1986) and versions of Illislab earlier than 2000 (Tabatabaie, 1978) contained models that failed the logic. Jslab was run to conduct a numerical calculation for a logical check. A single heavy wheel load is applied on the left side of a joint with load transfer efficiencies selected as any value in a range often used by engineers. The critical transverse stress at the loaded side of the joint was frequently lower than the stress on the unloaded side. The results conflict with the common knowledge of engineers: the loaded side maximum stress should always be more critical. Therefore, there must be some problems in the two programs. Further study (Guo et al., 1995) found that the dowel bars are assumed to be embedded in the concrete slab so a beam element was selected for the earliest version of Illislab (Tabatabai et al., 1978). The authors correctly recognized that the beam model being fixed on the two vertical surfaces of a joint was too stiff, and four lower element values in the element stiffness matrix were proposed for considering the “interaction” between the dowel and the surrounding concrete. The early version of Jslab (Tayabji et al., 1986) adopted the same idea except that eight values in the element stiffness matrix were made lower instead of four. The positive contribution of the above studies was to consider the “interaction” between dowels and the surrounding concrete. However, it was executed by an “empirical” procedure: manually using the lower values obtained from a separate mechanistic model (Timoshenko, 1925) to replace the original elements in the classical beam stiffness matrix. The modification led to the logical problem shown in Figure 1. It also breaks the equilibrium law required in any static analysis.

σ(L)

σ(U)

A heavy SingleWheel Load

Figure 1.

Calculated results: σ(U) > σ(L) A joint with LTE > 0

The logical problem of Dowel model in earlier versions of Illislab and Jslab..

533

Fixed End A

P

C

B D

Figure 2.

Rigid body movement and deformation of an element.

The four nodal forces at two ends of the beam were forced into an in-equilibrium set, and non-zero nodal forces were introduced by a rigid body movement, as shown in Figure 2. A rectangular element identified by symbol “A” is located in a cantilever beam before the load P is applied. After the load is applied, the element has been deformed and moved to location “D” (solid). Three steps are needed to complete the process: step one, “A” to “B” is rigid parallel movement, and step two, “B” to “C” is rigid rotation. These two rigid movements should not lead to any non-zero nodal forces on the element. Only in the third step, “C” (dashed, original shape) to “D”, the deformed shape is related to the non-zero nodal forces. However, the element stiffness matrices in the old versions of Illislab and Jslab produce nonzero nodal forces. Therefore, the proposed modifications satisfy neither the logical nor the theoretical criteria ((1) and (2)). The detailed proof can be found in Guo et al., 1995. A “comprehensive” mechanistic dowel model that passes the first two criteria was published by Nishizawa et al., 1989. It appropriately considers the interaction between the dowels and the surrounding concrete. Unfortunately, it had a mathematical error in the inverse matrix derivation. The product of the original matrix and its inverse does not equal the unit matrix. Also, the dowel section between the two vertical surfaces of the joint was incorrectly simulated by a bending beam whose behavior is governed by a fourth order differential equation. Since the ratio of the length of a dowel segment within the joint opening and the dowel diameter is much less than 3, the beam should be modeled by a shear beam whose behavior is governed by a second order differential equation. Detailed discussions are available in Guo et al., 1995. After correcting the above two deficiencies, the beam model for doweled joints in 2-D finite element analysis was finalized by Guo et al., in 1992 in his PhD study (Guo et al., 1995). In 2000, the model was evaluated under the support of the FHWA and installed into Islab 2000 (Khazanovich 2000 & 2005) as the default selection for doweled joint analysis. The final dowel model was approached by all investigators step-by-step learning from previous models. All previous works have significant contributions to the finalized one. The learned lesson is that: although an empirical procedure might be the most important tool in pavement researches, it should not be used to improve a mechanistic model without following the basic requirements from theory. 3.4 Equivalency of the shear and beam models, unique theory in joint modeling The earliest attempt at finding the relationship between the shear and beam models was published by Ioannides et al., in 1992. If the equivalent conditions can be discovered and proved in modeling, only one model is needed to represent both saw-cut and doweled joints if it is assumed that the dowel bars are uniformly distributed along the joint, as is normally the case in most airport pavements. Therefore, for a given doweled joint with multiple input parameters (dowel diameter, spacing, joint opening, material properties, etc.), a single input parameter value (shear stiffness) can be calculated for pavement response analysis, and the response difference using the beam and shear models is negligible. Unfortunately, an error existed in deriving the equivalency. The error might be caused by a missing numerical value “2” in the final division. After cutting a jointed pavement at the dowel middle point into two parts, the forces at the two ends are the same based on Newton’s third law so a single 534

value of force is needed. However, the length of the dowel segment in each part is only one half of the dowel segment length within the joint opening. One half of the entire length was used in the derivation and that led to the dowel stiffness being doubled. Further, it led to the shear stiffness of a doweled joint to be twice the correct value. The correct equivalency equations were derived and presented by Huang in 1993. Some later published papers used the incorrect equation rather than the correct one. In the middle of the nineteen nineties, the FAA needed to answer two questions before finalizing its model for analysis and design: 1. Should the saw-cut and dowel joints be represented by two separate models or by a single model? 2. A literature review indicated that two results were published as mentioned above, but which one should be used? The discrepancy of the above two equivalency equations was evaluated and published by Brill et al., 2000(II). The numerical verifications of the two models are presented by Guo et al., 2003(I). Since most doweled joints used for airport pavements have uniformly distributed dowels, the model in Huang’s book has been adopted in FAA related programs for analysis, FEAFAA (FAA 2009(II)), and design, FAARFIELD (FAA 2008), as the single model for both saw-cut and doweled joints. The beam model is still necessary for joints using non-uniformly distributed dowels in highway pavements. The impact of the above basic studies on practice: The basic study not only helps us to appropriately understand the dowel contributions in transferring load, but also supports the observations at the FAA’s test section at Denver airport. Based on the incorrect equation, pavement engineers might favor the dowels by overestimating their load transfer capability. In fact, dowels should only transfer a load as indicated by Huang’s equation, about 50% of the value predicted by the incorrect equation. Many experienced pavement engineers favor the use of dowels because they transfer loads more evenly during the year (winter and summer). This has been verified by many years of survey at FAA’s test section at Denver International airport (Dong et al., 2002). The Denver data repeatedly show that the doweled joint load transfer capability is much better than the saw-cut joint in winter, but worse than the saw-cut joint in summer. The basic study verifies that the engineer’s experience and observations in the field are reliable and fundamentally correct. 3.5 Relationship between the responses on the loaded and unloaded sides at a joint In PCC pavement analysis and evaluation, the following assumptions have been extensively used (Crovetti 1994 & 1996, Hammons 1995): RL + RU = R( LTE = 0 ) = RE

(1)

where LTE is the load transfer efficiency defined by the ratio of two responses (deflections or stresses) on the two sides of a joint. LTE = 0 defines that the joint has no load transfer capability so it is equivalent to a free edge. RL and RU are the critical response at the loaded and the unloaded sides of the joint respectively. Equation (1) assumes, without proof, that only two of the three parameters are independent. Equation (1) has been extensively used in PCC pavement analysis and evaluation because: 1. The deflection ratio δU /δL has been extensively used by most pavement engineers to evaluate the joint load transfer capability since both δU and δL can be directly measured by the FWD. However, δE cannot be directly measured for a jointed pavement. 2. Some pavement design specifications such as FAA 2008 use a single slab model to simplify the analysis procedure and stress ratio σU /σE is used to define the joint load transfer capability. However, none of σU, σL or σE can be easily measured in the field. 3. As stated above, the relationship between σU /σE and δU /δL is of special interest. Equation (1) provides an additional equation among the three variables (σU, σL, σE and δU, δL, δE) so that the number of unknowns can be reduced and the analysis and evaluation may be simplified. 535

P

P

δ δ

1

2

Figure 3.

Conceptual proof that equation (1) is invalid for curled pavement.

Therefore, that equation (1) is always true, or only true under specific conditions, is worthy of investigation. It has been theoretically proven by Guo 2003(II) that only two, rather than the three responses in equation (1) are independent. The major conditions to derive equation (1) include that the pavement must be flat, and that the shapes and sizes of the two slabs are the same. Equation (1) is precisely satisfied by any 2D finite element model for pavement response analysis if a shear model is used for the joint and approximately satisfied if a beam model is used for the doweled joint since it has been proven to be equivalent to the shear model. The significance of equation (1) includes: 1. For mechanistic modeling: It can be used as the theoretical criterion (the second of the criteria listed previously) to evaluate the accuracy of any 2D program for pavement response analysis—the sum of the predicted responses should be independent of any selected value of LTE; 2. For engineering practice: Since the deflection at the free edge is not available in field evaluations of JPCP pavements, the sum of the measured deflections on the two sides of the joint can be used to calculate the LTE for engineering practice. 3.6 Equation (1) is not valid for a curled up pavement Crovetti 1994 & 1996 is probably the earliest investigator who intended to take advantage of not only the ratio, but also the sum of the two responses on the two sides of a joint using FWD test data. This idea helps all the later investigators. However, equation (1) was not only used by him for a flat but also for a curled pavement for curling analysis. The extension of Equation (1) from flat to the curled up pavements can be easily evaluated using the logical criterion (1). To prove an equation invalid is usually easier than to prove an equation valid because it only requires a special case that the equation does not satisfy. Assume that two equalsize curled up slabs are connected by a shear joint with infinitely high load transfer capability as shown in Figure 3. A load 2P applied on the left side should be logically equivalent to two loads of P applied on the two sides of the joint since the load transfer capability is set infinitely high. Let us analyze the special case: the load P produces such a deflection δ1 that makes the slab just touch the subgrade. The deflection of the free-edge single slab under 2P is δ1 + δ2 and must be logically smaller than the sum of the deflections on the two sides of the joint δ1 + δ1 since δ1(without subgrade support) > δ2 (with subgrade support). Therefore, equation (1) has been logically proven invalid for analysis of curled slabs. 3.7 Curling indicator of a JCPC Further, it has also been found by full scale tests at the FAA’s NAPTF (Guo et al., 2001(II)) that the sum of two deflections δU + δL (SUM) on the two sides of a joint is correlated to the degree of curling of a JPCP without cracks. Three test items were built on three subgrades with CBR = 3–4, 7–8 and higher than 30. Each of the items had fifteen slabs in three lanes, five slabs in each lane. All twelve of the saw-cut transverse joints in each item 536

were tested in winter and summer. The LTE(D) (load transfer efficiency defined by the ratio of deflections on the two sides of a joint,) were measured on the two sides of each joint so twenty four data were received for each test item. The values of LTE(D) depend on the FWD load location corresponding to traffic direction in the field so the values measured on the two sides were sometime significantly different. The average values of LTE(D) on the high side were about 38% to 62% higher than those on the low side as shown in Figure 4. The right columns of Figure 4 present the ratio of SUM (δU + δL) in the same two groups with high and low LTE(D). It is interesting to see that the values of SUM are independent of the traffic direction. Or, the SUM was independent of the LTE(D) of the joints. Figure 5 shows that the values of SUM were low in summer and high in winter. And the curling of test item HRS built on the strong subgrade, CBR > 30, was much higher than that of LRS built on the weak subgrade, CBR between 3 and 4. Elevation surveys for the three test items clearly verified that the curling in winter was much higher than in the summer. This was true for all three PCC test items and has been repeatedly verified by later tests. The two findings suggest that the “SUM” from the FWD test data may be considered as an indicator of curling of a JPCP. The benefit of the finding includes that

Figure 4.

Different characteristics of LTD and SUM.

Figure 5.

Sum may be used as an indicator of JPCP curling.

537

when LTE(D) is measured at a joint, the SUM can be calculated using the obtained test data without additional cost. The numerical analysis using a 2D FEM program (Guo, E 2001(I)) verified that the above findings in full scale tests are conditionally rather than unconditionally true. The values of SUM remain constant for joints with K value greater than 69 MPa (10,000 psi). Many well performing joints of airport pavements in service fall in the above range. Values of 414 to 690 MPa (60,000 to 100,000 psi) have been used in many published papers for analysis. Summary: supported by modeling analysis, the mechanism related findings from empirical full-scale tests may have additional practical applications. Future work is needed to quantify the SUM to the degree of curling for different field conditions. And the results should also be compared to the slab curling (and/or warping) determined by other techniques, such as using profile measurements (Byrum 2001, Vandenbossche 2007). 3.8 Joint modeling in 3D FEM analysis—problem discovered by the logical criterion EverFe is a user-friendly 3D finite-element analysis tool for simulating the response of jointed plain concrete pavement (JPCP) systems to axle loads and environmental effects. It offers both multiple layer and dense liquid models for simulating the foundation. Numerical comparisons are presented in Figure 6 for criterion checking. Logically, if the load transfer capability is close to zero, such as K = 6.9 kPa (1 psi) is used in the analysis and a load is applied on the left side of the two slabs in Figure 6, only the loaded side slab will be deformed and the unloaded side slab should remain un-deformed when the dense liquid model is used for the foundation. The above statement is verified by both the 3D program EverFe, 2002 (square) and the 2D program Jslab2004 (dashed) in Figure 6. This also indicates that the thin-plate 2D model is acceptable since the results of the 2D and 3D programs are the same. The above logical statement should also be true when multiple layer foundation and frictionless interface models are used between the slabs and the foundation in any 3D program. Unfortunately, significant deformations were still received in EverFe results (solid curve, Figure 6) though the load is applied only on the loaded side, k is taken as 6.9 kPa (1 psi), and self-weight of the slab is set to zero. A similar error was also found a few years ago when FAA decided to adopt NIKE (Maker 1995) as its design engine. The comparison between the LTE(D) analyzed using NIKE and the full scale data received at the Denver airport verifies the problem: the old model overestimated the load transfer

Load Induced Deflections Along The Pavement Center Line (k = 6.9 Kpa, 1 psi) –0.050

0.000

Deflections in mm

0.050

0.100 EverFe, Multiple Layer Foundation

0.150

EverFe, Dense Liquid Foundation Jslab, Dense Liquid Foundation

0.200

0.250 –6

–4

–2

0

2

0.300 Offset Form the Joint, meter

Figure 6.

Comparison of longitudinal deflections by 3D and 2D models.

538

4

6

capability (Brill 2000(1)). Or, the deficiency of the model fails to pass the experimental criterion (3). It was quite easy, as shown above, to discover the failure to pass the logical criterion several years ago in NIKE. However, the problem remained unsolved until recently when it was corrected along with other discovered problems in NIKE. The solution to the problem will be reported in a separate paper. Now, the 3D NIKE program can calculate results which are the same as the two curves in Figure 6 using a dense liquid model if appropriate layer modules values are selected.

4

SUCCESSES AND PENDING PROBLEMS

4.1 Summary of successes 1. It is important to use appropriate criteria to evaluate a mechanistic model before application to practice. No model can be properly evaluated without appropriate criteria. 2. Both empirical and mechanistic procedures are important in pavement research. However, they have essentially different requirements so empirical equations should not be used to modify a mechanistic procedure without theoretical proof; 3. The logical criterion is the basic tool to evaluate and discover problems in existing models. It can be done by any experienced pavement engineer with logical thinking. It does not need advanced mathematical derivations. 4. New mechanism related pavement behavior can be found in reliable full scale tests. The mechanistic analysis can evaluate, verify, and improve the findings into theory. After that, application of the findings to practice can be more reliable. 4.2 Pending problems in joint modeling and applications The load transfer capability of a JPCP joint can be easily measured using parameter LTE(D) (deflection ratio) but LTE(S) (stresses ratio) is needed for design such as adopted in the new FAA design procedure. However, it is unrealistic to measure LTE(S) in the field. Therefore, the relationship between LTE(D) and LTE(S) becomes a necessary research topic. The popularly used LTE(S) vs. LTE(D) curves were obtained using a 2D finite element program and were first published in non-dimensional format by Ioannides et al., 1992. Similar curves in dimensional form have been adopted by the FAA in Advisory Circular 150/5370 = 11A (FAA, 2004). It must be recognized that the accuracy of the relationship depends on how good the match is between the predicted and the true load transfer behavior in the field. The following questions need to be answered. 1. How different are the load-type effects on the critical responses? FWD equipment and a moving wheel provide two types of loads: impulse vs. slow rolling, with shorter and longer loading periods respectively. They may have different effects on the load transfer behavior. 2. How different are the effects of foot print shape and its center distance to the joint between the FWD and wheel loads? The shapes of the footprint are different: ellipse for a wheel vs. circular for FWD equipment. The distance between the FWD load center and the joint is fixed at 15 cm (5.9 in), but the distance between the load center of a wheel is variable and usually larger than 30 cm (11.8 in) for most heavy aircraft. The analysis of Denver data (Brill 2000(1)) assumed that the critical stress under a moving wheel always occurs when the wheel is completely on one side and tangential at the joint edge. This assumption can only be verified using the strains, rather then deflections, measured on the two sides of a joint. Now, sufficient data are available in a database (FAA 2009(1)). 3. How does a joint transfer the load under a multiple-wheel gear? Is the load transfer capability evaluated by FWD data underestimated or overestimated compared to that under a multiple-wheel heavy aircraft? 539

4. Should the joint load transfer capability be defined by a unique value or by two values depending on traffic direction? This information is needed for airport runways because the takeoff and landing direction depends on the wind direction. A sufficient number of LTE tests at the FAA’s NAPTF verifies that the values of LTE(D) from FWD data are direction sensitive as discussed above. However, primary data analysis shows that it is not so sensitive under an aircraft gear load. Further studies are needed. ACKNOWLEDGEMENT This work was supported by the FAA Airport Technology Research and Development Branch, Manager, Dr. Satish K. Agrawal. Special thanks are given to Dr. Gordon F. Hayhoe for his technical leadership in test planning, organization and review of this paper, to Mr. Chuck Teubert for his test management, and to Ms. Mingyao Dong for independently checking the models and for her advice on getting data from the FAA database. The contents of the paper reflect the views of the author, who is responsible for the facts and accuracy of the data presented within. The contents do not necessarily reflect the official views and policies of the FAA. The paper does not constitute a standard, specification, or regulation. REFERENCES Brill, D. 2000(I), “Field Verification of A 3D Finite Element Rigid Airport Pavement Model,” DOT/ FAA/AR-00/33, July 2000, pages 35–59. Brill, D. and E. Guo, 2000(II). “Load Transfer in Rigid Airport Pavement Joints”, Proceedings of the 26th International Air Transportation Conference, San Francisco, June 18–21, 2000. Byrum, C.R. 2001, “Analysis of LTPP JCP Slab Curvatures Using High Speed Profiles”. Crovetti, James A. and Crovetti, M.R.T., (1994) “Evaluation of Support Conditions Under Jointed Concrete Pavement Slabs,” Nondestructive Testing of Pavements and Backtcalculation of Moduli, ASTM STP 1198. Crovetti, James A. (1996) “Field Evaluation of Support Uniformity Under Jointed Concrete Slabs”, Presented in TRB 75th Annual Meeting, January 7–11, 1996, Washington D.C. Dong, M. and G. Hayhoe, 2002. “Analysis of Falling Weight Deflectometer Tests at Denver International Airport,” FAA 2002 Technical Transfer Conference. EverFe, 2002, “Software for the 3D Finite Element Analysis of Jointed Plain Concrete Pavements” copied from http://www.civil.umaine.edu/EverFE/ in 2002. FAA, 2009(I), http://www.airporttech.tc.faa.gov/naptf/ FAA, 2009(II), FEAFAA—3D Finite Element Based Pavement Analysis Procedure, website: http:// www.airporttech.tc.faa.gov/pavement/3dfem.asp FAA, 2008, FAA Advisory Circular AC150/5320 6E, “Airport Pavement Design and Evaluation.” FAA, 2004, FAA Advisory Circular AC 150/5370–11A, “Use of Nondestructive Testing in the Evaluation of Airport Pavements”, website: http://www1.airweb.faa.gov/ Guo, E.H., J.M. Sherwood and M.B. Snyder, (1995). “Component Dowel-Bar Model for Load-Transfer Systems in PCC Pavements,” ASCE Journal of Transportation Engineering, Vol. 121, No. 3, May/June 1995. Guo, E. 2001(I) “Back-estimation of Slab Curling and Joint Stiffness”, Proceeding of 7th International Conference on Concrete Pavements, Sep. 9–13, 2001, pages 39–53. Guo, E. and W. Marsey, 2001(II). “Verification of Curling in PCC Slabs at the National Airport Pavement Test Facility,” 2001 ASCE Airfield Pavement Specialty Conference, Chicago, August 5–8. Guo, E. and M. Dong, 2003(I) “Evaluation Criteria of a Computer Program for Pavement Response Analysis,” Proceedings of International Conference on Highway Pavement Data, Analysis and Mechanistic Design Application, Columbus, Ohio, September 7–9, 2003. Guo, E. 2003(II). “Proof and Comments on Extensively Used Assumptions in PCC Pavement Analysis and Evaluation,” ASCE Journal of Transportation Engineering, Vol. 129, No. 2, March/April, 2003. Guo, E. and F. Pecht, 2007. “Application Of Surface Strain Gages At The FAA’s NAPTF,” 2007 FAA Worldwide Airport Technology Transfer Conference, Atlantic City, NJ USA, April, 2007. Hammons, M.I., D. Pittman and D. Mathews, (1995). “Effectiveness of Load Transfer Devices,” DOT/FAA/AR-95/80.

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Huang, Y.H. and S.T. Wang, 1973. “Finite-element Analysis of Concrete Slabs and Its Implications for Rigid Pavement Design,” HRB, Highway Research Record 466, 1973, pp. 55–79. Huang, Y.H. 1993. “Pavement Analysis and Design”, Prentice Hall, 1993. Khazanovich, Lev, T. Yu and C. Beckemeyer, 2000. “Application of ISLAB2000 for Forensic Studies,” Proceedings of the Second International Symposium on 3D Finite Element for Pavement Analysis, Design and Research, Edited by Samir N. Shoukry, Oct. 11–13, 2000. Ioannides, A.M. and G. Korovesis, 1992. “Analysis and Design of Doweled Slab-on-Grade Pavement System,” ASCE Transportation Journal, Vol. 118, Nov/Dec, 1992. Ioannides, A.M. 2005. “Stress Prediction for Cracking of Jointed Plain Concrete Pavements, 1925–2000: An Overview,” TRB 84th Annual Meeting, January, 2005. Maker, B.M., (1995), NIKE3D–An Nonlinear, Implicit, Three-Dimensional Finite Element Code for Solid and Structural Mechanics—User’s Manual Report UCRL-MA-105268, Rev. 1, Livermore, California, Lawrence Livermore National Laboratory, 1995. Nishizawa, T., T. Fukuda and S. Matsuno, 1989. “A Refined Model of Doweled Joints For Concrete Pavement Using FEM Analysis,” Proceeding of 4th International Conference on Concrete Pavement Design, April 18–20, 1989. Tabatabaie, A.M., E.J. Barenberg and R.E. Smith, (1978). “Analysis of Load Transfer System for Concrete Pavements,” Technical Report FAA-RD-79–4. Tayabji, S.D and B.E. Colley, (1986). “Improved Rigid Pavement Joints,” FHWA/RD 86/040. Timoshenko, S., and J.M. Lessels, 1925, “Applied Elasticity.” Westinghouse Technical Night School Press, Pittsburgh, PA, 1925. Transportation Research Board, Transportation Research Record 1719. National, Academy Press, Washington DC, 2001. Vandenbossche, J.M., 2007. “Effects of Slab Temperature Profiles on the Use of Falling Weight Deflectometer Data to Monitor Joint Performance and Detect Voids,” Transportation Research Record: Journal of the Transportation Research Board, No. 2005, TRB, National Research Council, Washington, DC, 2007.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Mechanistic modelling of potential interlayer slip at base sub-base level E. Horak & J.W. Maina Built Environment, CSIR, (University of Pretoria) Pretoria, Gauteng, South Africa

S.E. Emery University of the Witwatersrand and Kubu International (Pty) Ltd, Johannesburg, Gauteng, South Africa

B. Walker Bing Walker and Associates Consultants Pty Ltd, Cape Town, South Africa

ABSTRACT: A new airport pavement under construction in Africa is experiencing severe salt crystallization problems. The local material with high salt content was used up to sub base level. The sub base was thus covered with a prime and bitumen rubber vapour cut off layer. On top of this layer a dry bound macadam (DBM) layer was constructed The DBM was sealed off with a 50 mm asphalt surfacing and a bitumen rubber seal as final surface seal. The concern was that the horizontal forces, due to braking and turning of the design aircraft, would cause interlayer slip at such positions where the bitumen rubber vapor seals are placed in the pavement as well as on the top. A mechanistic analysis was done to evaluate this pavement slip potential. The concept of strain energy of distortion (SED) is used to analyze the pavement to quantify and benchmark the effect of the horizontal forces. 1

INTRODUCTION

Walvis Bay International Airport (WBIA), on the Namibian west coast, is currently being upgraded to meet ICAO 4F specifications, suitable for Airbus A380 operations. The work involves the lengthening and widening of the current runway and a new apron and connecting taxiway. As work progressed, salt crystal manifestation occurred due to the presence of Gypcrete, a known high salt content material with severe salt crystallization problems. Such material is known to cause severe salt related problems with long term implications (Weinert, 1980, Obika et al. 1992 & Rollings et al. 1994). Kubu International (Pty) Ltd was requested to do a technical audit on the airport and was subsequently appointed to provide an alternative design to help protect the asphalt surfacing layers against salt crystallization problems. The revised pavement structure proposed at WBIA has a bitumen rubber (BR) seal as a moisture barrier between the sub-base and base, and on top of the asphalt surfacing to reduce the surfacing permeability and improve macro-texture of the surface layer. The base was constructed with a dry-bound macadam (DBM) base to reduce construction moisture and therefore limit any possible salt migration from the salt in the sub-base and subgrade materials (Weinert, 1980). The problem of surfacing slippage on airports due to horizontal forces from braking and turning aircraft is known (Shanin, 2004 & Harvey et al. 1996). In most cases slippage between the upper asphalt layers tended to be the problem. Therefore the proposed bitumen-rubber seal as surface friction course on top of the asphalt layer may pose such a problem. However, in the case of WBIA, a concern was also expressed that interlayer slip may occur at the interfaces deeper in the pavement structure where the bitumen-rubber seal is placed as a moisture barrier. The concern was that the horizontal forces, due to braking and turning of 543

the design aircraft, the Boeing 747-400, would cause interlayer slip at such positions deeper in the pavement. A mechanistic analysis was done to evaluate this perceived deep pavement slip potential. 2

MECHANISTIC MODELING

Until recently, vertical load only was used in most analyses of pavements (Maina & Matsui, 2004). However the tire/pavement interface results in very complex contact stresses (De Beer et al. 1997). It is possible to model this complex interaction of wheel and surface force transfer in the vertical and horizontal direction in a pavement structure in a number of ways. A brief look at horizontal shear stress in the pavement and specifically at the interface of a thin asphalt overlay are discussed to help benchmark the effect of such horizontal forces exerted. Thereafter the concept of strain energy of distortion (SED) is used to analyze the WBIA pavement to quantify and benchmark the effect of the horizontal forces. 2.1 Shear stress in depth Shear stress at the interface between the top layers is normally an indication of the potential for shear failure of the top layer due to horizontal forces applied additionally to vertical loading. In Figure 1 the shear stress is shown in depth of a pavement structure analyzed with the GAMES software (Matsui et al. 2005) and compared with the results from the well known BISAR software analysis. The pavement structure analyzed and the loading condition, are shown on the right hand side. Loadings horizontally and vertically were uniformly distributed via a circular area of radius 150 mm. This is a realistic assumption for aircraft tires (de Beer et al. 1997). The results of the comparative analyses on the left hand side shows that shear stress is clearly maximum at the surface where after it diminishes to virtually zero at a depth of 100 mm in the pavement. This rapid diminishing effect was also illustrated by Tayebali et al. (2004) in similar calculations of horizontal shear at the interface of an asphalt overlay by varying the asphalt overlay thicknesses from 37 mm to about 80 mm. At 80 mm thickness the interlayer shear stress had virtually diminished to zero. It can therefore be concluded that shear stress due to horizontal forces on an asphalt surface is a phenomenon which is largely restricted to the top of the pavement where the tire and surface interact and diminishes rapidly in depth of the pavement. Farias (1997) also demonstrated this diminishing effect of shear stress in depth for horizontal force only using finite element analysis methods.

49 kN Vertical 24.5 kN Horizontal 100 mm

500 mm

Asphalt base 5000 MPa Base 250 MPa

Subgrade 60 MPa

Figure 1.

Shear stress in depth of a typical pavement structure (Matsui et al. 2005).

544

3

STRAIN ENERGY OF DISTORTION

Maina & Matsui (2004) developed solutions for boundary conditions for five different types of airport pavement surface loading namely; vertical, horizontal (shear), torsion, moment and centripetal forces incorporated in the elastic analysis freeware known as GAMES. Maina et al. (2007) used the concept of quantity of strain energy stored per unit volume (V0) of the material as originally developed by Thimoshenko & Goodier (1951) as basis for determining the limiting stress at which failure occurs. In short Hooke’s law is applied to calculate the strain energy due to distortion (SED) which can be reduced from a rather complex equation to be expressed as follows for these specific boundary conditions: SED = V0 −

1 − 2ν σx +σ y +σz 6E

(

)

2

(1)

This equation is basically a function of the bulk (sum of principal) stresses, the elastic modulus (E) and Poisson’s ratio (ν). Using the above equation it is possible to benchmark points within the pavement structure in that points having higher values of SED (a scalar quantity) will potentially fail first before points with relatively lower SED values (Maina et al. 2007). This is therefore a benchmark type analysis, which has the benefit that it will identify areas which are more likely to fail than others, but does not necessarily mean that that point will fail in shear or compression. It only highlights likely areas of potential failure and may need further detailed analysis for failure type and mechanism identification and description. The pavement structure mentioned earlier was analyzed with material parameters and values as summarized in Table 1. As mentioned before the design aircraft is the Boeing 747-400. One bogey with four wheels of the main gear of the Boeing 747-400 was used as the loading situation. The wheel contact footprint diameter is 458 mm and the loading of maximum 225 kN for vertical force per wheel. The horizontal force was varied from zero to 0.7 of vertical force. The maximum value of 0.68 of vertical force (Tayebali et al. 2004), described before in the shear stress analysis, is based on the surface friction coefficient representing the maximum horizontal force at approximately 50 kph. In the analysis to follow the bitumen-rubber seal as surfacing layer on top and on top of the sub-base were consecutively modeled for the following slip conditions the strain energy at distortion (SED) was calculated at all the layer boundaries: – No slip (zero value) – Full slip (0.99 value)

Table 1.

HKIA pavement structure input values.

Layer description Bitumen-rubber (BR) seal Asphalt overlay Drybound Macadam (DBM) Base Bitumen-rubber seal barrier C4 sub-base G6 imported subgrade

Layer number

Thickness (mm)

Modulus (MPa)

Poisson’s ratio

1 2

10 50

3000 3000

0.44 0.44

3

150

2000

0.35

4 5 6

10 425 300

3000 300 150

0.44 0.35 0.35

545

3.1 SED with full friction with vertical and horizontal forces applied separately The SED calculation for the situation where there is no slip between any layer and the vertical force is applied alone or the horizontal force is applied alone in multiples of the vertical force is shown in Figure 2. The situation where vertical force is applied alone (shown in the left hand side of Figure 2) clearly shows that the highest SED will occur at the top of the DBM base layer. The form of the potential distress in such a case would be to deform or densify this layer. The good history of macadam bases on airport pavements rule against the possibility of failure of this layer though (Horak and Triebel, 1986). On the right hand side the horizontal force application is shown. In this case the top of the BR surface seal and asphalt layer underneath attract the highest SED. The quantum of the SED is however relatively small in comparison to the situations still to be analyzed as they all have the same vertical scale for the SED to facilitate direct benchmarking. Therefore, the probability of shear and cracking in these upper layers are seen as remote. This perception is strengthened by the knowledge that a BR in practice has not yet shown any such shear or slip distress. Normal shear tests on asphalt tended to be higher than this shear value induced (Tayebali et al. 2004 and Romanoschi & Metcalf, 2004) enhancing the position that failure is unlikely to occur in the asphalt layer. The SED calculated on top of the DBM base is third largest and the same argument of unlikely distress occurring as for the vertical force is used. 3.2 SED with full friction and vertical and horizontal forces applied simultaneously In Figure 3 the calculated SED is shown for the situation where applied vertical force and horizontal force are combined, but with zero interlayer slip, therefore with full friction. This shows that the vertical load effect on SED dominates as illustrated in the previous section and Figure 3. This relatively low SED value at the top of the DBM base can at best be an indication of a potential to densify or deform in shear. As stated before, the inherent shear force coefficients (C and Ø) are larger in macadam type materials due to the larger aggregate size (75 mm max) (Horak & Triebel, 1986) . The observation of SED being relatively high at the top of the pavement structure is in line with the previous analyses of Matsui et al. (2005) and Tayebali et al. (2004) which indicated that the highest horizontal shear stress tend to appear at the top of the pavement structure and rapid shear stress diminishing occurs in depth of the pavement structure.

Figure 2.

Vertical and horizontal forces separately at zero slip.

546

Figure 3.

Combined vertical and horizontal forces with no interlayer slip.

3.3 SED when there is slip between the bitumen-rubber surface seal and the asphalt layer with separate application of horizontal and vertical force In Figure 4, full slip is simulated between the bottom of the bitumen-rubber surface seal and the top of the asphalt layer underneath. This is considered unlikely to occur in reality because it is known from practice that the bitumen rubber seal will adhere to the asphalt. Some stone embedment is expected which will further reduce slip potential. The vertical force and the varying horizontal forces are again applied separately to isolate the relative contribution by vertical and horizontal forces. For the vertical force applied alone the highest SED occurs at the top of the DBM base layer. The relative quantum of the calculated SED forces the same argument of unlikely distress occurring as given before in the preceding section. The quantum of the SED in the case of only vertical force application is not dissimilar to that with no slip as shown in the right hand side of Figure 3. However, when the horizontal force is applied (in increasing multiples of vertical force) alone the SED on top and bottom of the bitumen-rubber surface seal is significantly higher (approximately seven times higher) than the maximum SED calculated for the no slip situation shown in Figure 3. The most probable form of distress in the bitumen-rubber seal layer here would be slip on the asphalt layer below. Hypothetically the seal could crack due to shear, but the inherent toughness/tenacity of the bitumen-rubber binder makes this less likely. There is also extensive experience of seals overlying asphalt indicating this type of slip is extremely rare. 3.4 SED with full slip between the bitumen-rubber surface seal and the asphalt layer with simultaneous application of horizontal and vertical force In Figure 5, the major contribution of the horizontal force is shown when slip is induced between the bitumen-rubber surface seal and the asphalt layer underneath. This is in line with the conclusion made from Figure 3 where the horizontal and vertical forces were applied separately. This is again in line with the Tayebali et al. (2004) analysis showing that horizontal shear stress is highest at the top of the pavement structure and tend to dissipate fast in depth of the pavement structure. 3.5 SED with full slip between the bitumen-rubber damp seal and the sub-base layer with separate application of horizontal and vertical force In Figure 6, the vertical and horizontal forces are again applied separately with full slip between the lower bitumen rubber damp seal barrier on top of the sub-base and the sub-base 547

Figure 4. Vertical and horizontal forces separately with full slip between the BR surface seal and the asphalt layer.

Figure 5. Vertical and horizontal forces simultaneously with full slip between BR surface seal and asphalt layer.

Figure 6. Separate vertical and horizontal forces with full slip between the bitumen rubber seal moisture barrier and sub-base layer.

548

Figure 7. Vertical and horizontal forces combined with full slip between bitumen rubber seal barrier and sub-base layers.

top. The effect of the vertical force dominates with the highest SED occurring at the top and bottom of the bitumen-rubber moisture barrier seal. This seal is most likely in compression as the vertical force alone is applied and therefore is not seen as a likely distress occurring. The contribution due to horizontal force only, even at 0.7 of vertical force, is insignificant in comparison. It is significant that even under such conditions that the highest potential for failure tends to stay in the top two layers probably for low potential shearing and not where the slip is simulated below the base layer. 3.6 SED when there is slip between the bitumen-rubber damp seal and the sub-base layer with simultaneous application of horizontal and vertical force In Figure 7, the combined horizontal and vertical forces with full slip between the lower bitumen-rubber damp seal barrier and the sub-base situation is modeled. It is significant, as shown in Figure 6, that the highest SED occurs at the bottom of the asphalt layer due to the vertical force contribution. It is also significant that the next highest SED values are also in those top two layers. There is virtually no SED value which occurs at the interface which is currently modeled to slip above the sub-base. 4

CONCLUSION

Analyses by various researchers have shown that horizontal shear stress dissipates relatively quickly from the maximum under the edge of a load at the surface with horizontal and vertical force applied to zero at a depth of approximately 100 mm. In the region of the asphalt surface horizontal stress contribution, due to horizontal force, is dominated by the contribution due to the vertical force when there is full friction between all interfaces. When full slip is induced between the bitumen-rubber surface seal and the asphalt layer underneath, the increasing horizontal forces tend to dominate when expressed in terms of the strain energy of distortion (SED). It clearly shows that the bitumen-rubber surface seal will be the most likely to crack and shear and comparatively virtually zero SED occurs deeper in the pavement. However, there is extensive experience of bitumen-rubber seals overlying asphalt layers resisting this type of distress with ease due to the good tenacity and elastic properties of bitumen-rubber. If slip is modeled at the interface between the sub-base and the bitumen-rubber moisture barrier on top of it, it clearly shows that vertical force effect dominates. The bitumen-rubber moisture barrier seal tend to be under compression which will not constitute a problem of 549

distress at that level. The influence of horizontal forces on SED is not only much less than those, due to vertical force, but also limited to the upper layers. Therefore when horizontal and vertical forces are combined for the slip induced between the bitumen-rubber and subbase layers the SED calculated maximizes again at the top and bottom of the bitumen-rubber moisture barrier seal and the DBM base layer. The most likely form of distress can be densification and shear deformation of the DBM layer. The inherent good shear force coefficients (C and Ø) are larger in macadam type materials due to the large single sized aggregate (75 mm max) than even in high quality granular bases (normally in southern Africa with a continuous grading and maximum aggregate size of 37 mm) and therefore this DBM base is deemed safe from any form of distress in this loading situation. No SED calculation of any significant quantum occurs below the interface where slip is induced deeper in the pavement though. This clearly points to the unlikely possibility of distress occurring at that level in the pavement, even if there was slip induced at that deeper interface, due to the introduction of a moisture barrier such as in this case. Therefore the premise that horizontal shear stress dissipates quickly to zero at a depth of approximately 100 mm measured under the edge of a wheel load at the surface when horizontal and vertical forces are applied means that the base and sub-base layers and their inter-layers are not likely to fail due to slip failure. REFERENCES De Beer, M. et al. 1997. Determination of Pneumatic Tyre/Pavement Interface Contact Stresses under Moving Loads and some Effects on Pavements with Thin Asphalt Surface Layers. 8th International Conference on Asphalt Pavements, Seattle, Washington: USA. Vol 1, pp. 179–227. Farias, M.M. 1997. The Influence of Horizontal Loads on the Fatigue of Pavements. University of Brasilia, Brazil, Recent Developments in Soil and pavement Mechanics, Almeida (ed) Balkema, Rotterdam: The Netherlands. ISBN 940 5410 8851. Harvey, J.T. et al. 2002. Rutting Evaluation of Asphalt Pavements using Full-scale Accelerated Load and Laboratory Performance Tests. Federal Aviation Administration Airport Technology Transfer Conference, New Jersey: USA. Horak, E. & Triebel, R.H.H. 1986. Waterbound Macadam as base and as drainage layer. Research Report 446. NITRR, CSIR, Pretoria and published in Transportation Research Board publication, Washington DC: USA. International Civil Aviation Organization (ICAO). 2004. Standards and Recommended Practices for Aerodromes. Annex 14 to the Convention on International Civil Aviation, Volume I: Aerodrome Design and Operations, Fourth Edition. Maina, J.W. & Matsui, K. 2004. Developing Software for Elastic Analysis of Pavement Structure Response to Vertical and Horizontal Surface Loading. Transportation Research Record. 1896, pp. 107–118. Washington: USA. Maina, J.W. et al. 2007. Effects of Layer Interface Slip on the Response and Performance of Elastic MultiLayered Flexible Airport Pavement Systems. Proc. 5th Int. Conf. on Maintenance and Rehabilitation of Pavements and Technological Control, pp. 145–150, Park City, Utah: USA. Matsui, K. et al. 2005. Development of Analysis of Multi-Layered Elastic Systems Toward MechanisticEmpirical Design of Pavement Structures. China—Japan 3rd Workshop on Pavement Technologies, Nanjing PR: China. Obika, B. et al. 1992. Physico-Chemical Aspects of Soluble Salt Damage of Thin Bituminous Surfacing. Proceedings of the International Conference on the Implications of Ground Chemistry and Microbiology for Construction, University of Bristol, 29 June–1 July 1992. Also as Report PA 1285/1992, Overseas Centre of the Transport Research Laboratory, Crowthorn, Berkshire: UK. Rollings, R.S. et al. 2003. Tropical pavement materials. 21st ARRB and 11th REAAA Conference, Cairns: Australia. Shanin, M.Y. 2004 Pavement Management for Airports and Parking Lots. Chapman and Hall, New York. Tayebali, A.A. et al. 2004. A Mechanistic Approach to Evaluate Contribution of Prime and Tack Coat in Composite Asphalt Pavements. Research Report 2001–04, Department of Civil Engineering, North Carolina State University, USA. Timoshenko, S. & Goodier, J.N. 1951.Theory of Elasticity. McGraw-Hill Book Company, New York. Weinert, H.H. 1980. The natural road construction materials of Southern Africa. Human and Rousseau. Cape Town, South. Africa, p. 298.

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PFC2D simulation research on vibrating compaction test of soil and rock aggregate mixture X. Jia Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, China

H. Chai & Z. Yan Chongqing Communications Research & Design Institute, China

Y. Zheng Department of Architecture & Civil Engineering EU, Chongqing, China

ABSTRACT: PFC2D discrete element modeling program is applied to simulate the vibrating compaction process of soil and rock aggregate mixtures. Different gradations of soil and rock aggregate mixtures are considered; and the porosity and dry density values of the soil and rock aggregate mixtures are tracked during the simulation. The compaction curve is consistent to the physical test. The particle motion pattern and density formation mechanism are investigated during the vibrating compaction simulation. The particle flow behavior and the structural properties of the particles of different gradations are discussed. 1

INTRODUCTION

Soil and rock aggregate mixtures are composed of different grain sizes and often produced by mountain excavation, blasting etc. They are used more and more in mountainous highway as embankment filling materials (Guo, 1991). As a new type of filling material, a typical soil and rock mixture differs from traditional homogeneous fine-grained soil because of its complex structure and coarse particles. There is no one systemic method for recognizing and detecting its compaction quality because the research on the density change process during vibrating compaction and on the mechanism of the greatest dry density of the soil and rock aggregate mixture is not satisfactory. Often analytical research has been undertaken on this new filling material because of lower cost and test equipment limitations, hence information to date cannot provide a quantitative understanding of the issue. Further, because of the complex properties of the material, numerical analysis methods are needed to conduct research; such conventional means of numerical analysis does not reflect the unique change of soil and rock aggregate mixture in micro level. For more understanding of soil and rock aggregate mixture, PFC2D (Two-dimensional Particle Flow Code) discrete element modeling type numerical simulation is adopted in the vibration compaction test study in order to investigate the microscopic particle motion and the formation of the structure. 2

PFC2D BASIC PRINCIPLES

PFC2D (Two-dimensional Particle Flow Code) models the movement and interaction of stressed assemblies of rigid circular particles using the distinct-element method (DEM). The DEM was introduced by Cundall (1971) for the analysis of rock-mechanics problems and then applied to soils by Cundall and Strack (1979). A thorough description of the method is given in the two-part paper of Cundall (1988) and Hart et al. (1988) and in the UDEC manual (Itasca, 2000). PFC2D is classified as a discrete element code based on the definition in the review of Cundall and Hart (1992) since it allows finite displacements and rotations of 551

Figure 1.

Calculation cycle in PFC2D.

discrete bodies, including complete detachment, and recognizes new contacts automatically as the calculation progresses. The contact forces and displacements of a stressed assembly of particles are found by tracing the movements of the individual particles. Movements result from the propagation through the particle system of disturbances caused by specified wall and particle motion and/or body forces. The calculation cycle in PFC2D is a time stepping algorithm that consists of the repeated application of the law of motion to each particle, a force-displacement law to each contact, and a constant updating of wall positions. Contacts, which may exist between two balls or between a ball and a wall, are formed and broken automatically during the course of a simulation. The calculation cycle is illustrated in Figure 1. At the start of each time step, the set of contacts is updated from the known particle and wall positions. The force-displacement law is then applied to each contact to update the contact forces based on the relative motion between the two entities at the contact and the contact constitutive model. Next, the law of motion is applied to each particle to update its velocity and position based on the resultant force and moment arising from the contact forces and any body forces acting on the particle. Also, the wall positions are updated based on the specified wall velocities. The forcedisplacement law is described first, followed by a description of the law of motion. The following simplifications apply to the PFC2D model. 2.1 Force displacement law The force-displacement law derives the contact force acting on two entities in contact to the relative displacement between the entities. For both ball-ball and ball-wall contacts, this contact force arises from contact occurring at a point. 2.2 Law of motion The motion of a single rigid particle is determined by the resultant force and moment vectors acting upon it, and can be described in terms of the translational motion of a point in the particle and the rotational motion of the particle. The equations of motion can be expressed as two vector equations: one relates the resultant force to the translational motion; the other relates the resultant moment to the rotational motion.

3

PARTICLE FLOW CODE SIMULATION OF SOIL AND ROCK AGGREGATE MIXTURE VIBRATING COMPACTION TEST

Different grade soil and rock aggregate mixture specimens can be established with PFC2D, and a certain distribution can be carried out accurately with the embedded Fish language 552

in PFC2D. Using the PFC2D analysis, the intent was to develop a preliminary understanding of the compaction law, adjust the gradation of soil and rock aggregate mixture, and draw some useful conclusion. Through the particle flow code simulation, one can keep track of the location of particles of soil and rock aggregate mixture; and monitor the porosity change during compaction; and establish a relationship between the maximum density and the soil and rock aggregate mixture gradation. With this simulation, some preliminary research can be conducted on investigating on the structural strength formation of soil and rock aggregate mixtures. 3.1 Numerical simulation test steps For particle flow simulation test, the particle sample should be first generated; through its own balance and the balance under the conditions of gravity, particles receive a pressure of the initial state; then the sample is compacted under the alternating vibrating load in the simulation process. The soil and rock aggregate mixture sample is compacted with three same thickness layers during the whole simulation. Through a series of tests, the porosity of the particles, the sample’s density as well as the entire compaction process and the particles movement can be observed in the simulation test. In the simulation process, the soil and rock aggregate mixture is simplified as rigid balls; rectangular walls, at the bottom and on both side are used for compaction tube wall; and the parallel connection the circular particles are used as the loading surface, alternating vibrating load acting on it. The soil and rock aggregate mixture is simulated with certain grade particles. It is suggested that the diameter of compaction tube can not be less than 5 to 6 times of maximal grain size. The compaction tube size is 300 mm × 500 mm so the maximal grain is 60 mm which accords with the related criterion. The grain size is divided into five groups, namely 40∼60 mm, 20∼40 mm, 10∼20 mm, 5∼10 mm and below 5 mm grains in order to simulate the influence of grain size and grain gradation in the compaction test. The grain size obeys uniform distribution within a certain group, such as the 20∼40 mm group, particles generated from a diameter of Dmin in 20 mm to Dmax 40 mm in uniform distribution and the average diameter Davg = (Dmin + Dmax)/2 = 30 mm. Through the built-in fish language in PFC2D, the final gradation of particles can be calculated, and final designed gradation can be matched in the end. For the particles below 5 mm, the smallest grain size is restricted to 0.075 mm in order to reduce the particle numbers. Compared with other grain size, the particles generated can fill the pores freely so that the compaction result will not be much affected. The net density of the particles is 2.6 g/cm3 in this simulation. First the walls are generated, a total of four, the rectangle is surrounded by 300 × 180 mm (single-layer height), see Figure 2a. Considering the efficiency of particles generation, in order to prevent particles overlapping, the particles are generated in half size, then the actual size of particles are rehabilitated, and sample internal stress are eliminated with certain stress elimination procedure. The number of particles and particle gradations are dealt with in the compaction simulation. First of all, the particle total weight per layer is determined with the porosity 24%, the porosity is calculated as follows: e = 1 − ρd ρ s

(1)

where ρd is the dry density, ρs the net density of the grain. As the simulation did not consider the content of water, thus the dry density of the sample would be equal to the density of the sample ρ. The sample density is calculated as follows with the porosity of 24%: ρ = ρs × (1 − e) = 1.976 g/cm3

(2)

The result of the calculation is a little greater than that under normal circumstances because the porosity of two-dimensional problem is lower than the corresponding threedimensional case. The minimum porosity in three-dimensions is 25.95%; hence the value will be a little higher. The real soil and rock aggregate mixture particles are in three-dimensional form, but comparing with the three-dimensional case, the movement of particles can be more easily observed within the same plane. 553

According to the percentage of the total weight in each group, the particles are generated with built-in Fish language. The final result is given in Table 1. The actual weights of particles for each group and the design are nearly identical, and the maximum error is within 5%, which is acceptable in this simulation. 3.2 Compaction process simulation The compaction simulation is illustrated for the soil and rock ratio 40:60. The simulation is undertaken in three layers as same as the physical compaction test. The compaction simulation process is shown in Figure 2a to Figure 2f. Table 1.

Particle weight ratio of different gradations. Gradation composition Weight ratio passing through the sieve pore (%)

Ratio of rock and soil

60 mm

40 mm

20 mm

10 mm

5 mm

20:80 40:60 60:40 80:20 100:0

100 100 100 100 100

94.5 94.0 87.7 81.3 77.8

88.2 83.5 72.5 64.9 54.5

84.0 74.4 60.6 44.5 29.2

80.5 63.5 42.2 21.5 0

Figure 2a.

Pre-compaction of first layer.

Figure 2c.

Pre-compaction of second layer.

Figure 2b.

Figure 2d.

554

After compaction of first layer.

After compaction of second layer.

Figure 2e.

Pre-compaction of third layer.

Figure 2f.

After compaction of third layer.

The first stage of the compaction process can be defined as vibrating compacting stage, and then the next process is filling pores, followed by the resilient stage after the unloading process, and then the mixture reaches a stable dense state. The soil and rock aggregate mixture is a loose medium in the initial state; the particles are under compression with a downward movement to reach a certain density status (see Figure 3a). Then the particles are in a state of mutual contacts, and the particles are forced to interact, then the particles are squeezed to fill the pores under contact force. The velocity of particles at this time is no longer downward, but relates to the near pores. The fine particles fill the pores “automatically” with contact force, and the coarse particles because of their greater weight and larger resistance, there will be no significant change in position in this process (Figure 3b). When all the particles achieve their balanced position, this process will stop. The soil and rock aggregate mixture will absorb some energy and generate a certain degree of distortion, and finally the particles will make a certain degree of resilience after unloading (Figure 3c). The compaction process finishes after the release of elastic energy, and then the dry density and porosity can be calculated out. The compaction process is therefore divided into three stages in the simulation (see Figure 4). These stages are not independent of each other, the process may be simultaneous, but it can be roughly divided into three stages because of its dominant position. Figures 5 and 6 show the particle movement histories in x and y direction, the corresponding process also can be seen in the tracks of the particles. 3.3 Dry density and porosity of soil and rock aggregate mixture The dry density and porosity of the sample can be calculated through the sample’s final size and the total weight. The results are shown in Table 2, Figures 7 and 8. It can be seen from Figure 7 that the dry density of sample appears to decrease after increasing trend with the increase of the ratio of rock and soil. On the contrary, the porosity appears to increase after declining trend. The dry density increases with the increase of rock content before the ratio of rock reaches 80%. The density of the sample increases slowly with ratio of rock under 40% because the coarse particles does not form the skeleton, but the dry density of the sample has improved because of the coarse particles. The dry density increases rapidly with the increase of rock content when the ratio of rock is between 40% to 80%, and 555

Figure 3a.

Vibrating compacting stage.

Figure 3c.

Vibrating resilient stage.

Figure 5.

Vertical motion of the particles.

Figure 3b.

Figure 4.

Vibrating compaction curve.

Figure 6.

556

Vibrating filling pores stage.

Horizontal motion of the particles.

Table 2.

Dry densities and porosities after compaction.

Ratio of rock and soil

Dry density (g/cm3)

Porosity

20:80 40:60 60:40 80:20 100:0

2.234 2.251 2.291 2.310 2.232

0.1404 0.1341 0.1262 0.1117 0.1411

Figure 7.

Maximum (greatest) dry density graphed with ratio of rock and soil.

Figure 8.

Relationship between the porosity and ratio of rock and soil.

the coarse and fine particles filling, cementing each other, thus density increasing, porosity declining. When the ratio of rock approaches to 100%, the coarse particles from the skeleton obviously but there are not enough fine particles to fill the pores, thus the porosity increases and the dry density decreases. The porosity and density are inversely proportional as seen in Figure 8. They all effectively reflect the compactness. High density, low porosity means good compactness, and on the 557

contrary, low density, high porosity means low compactness. From the density curve one can draw a conclusion that the soil and rock aggregate mixtures are better than a fine soil filling material, which has a good compactness, low porosity, and the skeleton at the same time has a good capacity. In practical engineering applications, as long as the appropriate choice of gradation (usually the ratio of rock of 60% to 80%), the soil and rock aggregate mixture will be able to have good road performance. 3.4 Structural properties of soil and rock aggregate mixture The structural properties of different gradations of soil and rock aggregate mixture are not the same after compaction. Figure 9 shows the contact force distribution of soil and rock

(a)

rock and soil ratio 40:60

(c)

rock and soil ratio 80:20

Figure 9.

(b)

(d)

rock and soil ratio 60:40

rock and soil ratio 100:0

Contact force chains predicted for different ratios of rock and soil.

558

aggregate mixture with different rock content. With the increase of rock content, the skeleton effect is increasingly obvious. The soil and rock aggregate mixture is similar with the pure soil, and the contact force distribution is relatively uniform when the ratio of rock is under 40%. When the ratio of rock reaches to 60%, it can be seen that the soil and rock aggregate mixture has the initial role of the skeleton, and the contact forces between the coarse particles are relatively significant, but not dominating. The skeleton of coarse particles has been formed when the rock content is 80%, and the mixture of coarse particles mainly resist the pressure; fine particles in the meantime play a filling, cementing role. When the ratio of rock is 100%, the mixture forms an entirely skeleton in the absence of the fine particles, the skeleton resist the full pressure. In order to give full play of coarse particles making the skeleton, and also give full play of the fine particles in filling and cementing, the ratio of rock is suitable in 60% to 80%. At this gradation, the soil and rock aggregate mixture has a high density, but also a good condition for structural capacity. That is, playing the role of the fine particles, and also playing the skeleton effect of coarse particles make a good material for the road construction. 4

CONCLUSIONS

Through the soil and rock aggregate mixture compaction test simulation, the following conclusions were reached: (1) It is confirmed that the soil and rock aggregate mixture is a good road construction material from PFC2D particle flow simulation, and which is abounding in the mountainous areas. The soil and rock aggregate mixture will have good road performance with small settlement, efficient construction advantages as long as a suitable gradation is chosen with reasonable compaction standards. (2) The compaction process in general can be divided into three stages in the simulation. The first stage could be defined as vibration compacting stage, and then the next process is filling pores, followed by the resilient stage after the unloading process, and then the mixture reaches a stable dense state. (3) The soil and rock aggregate mixtures are better than a fine soil filling material, which has a good compactness, low porosity, and the skeleton at the same time has a good structural capacity. In practical engineering applications, the soil and rock aggregate mixtures will be able to have a good performance as long as the appropriate choice of gradation (usually the ratio of rock 60% to 80%). Some useful conclusions have been drawn with the particle flow code compaction simulation, but it should be pointed out that the study uses the two dimensional particle simulation and the soil and rock aggregate mixture is three-dimensional material. Through the simulation reflects the compaction lows to some extent, but the porosity of the sample is lower than that in three- dimensional case and the water content is not considered in the study. Three-dimensional simulation should be carried out to get the more satisfactory results for further research. ACKNOWLEDGEMENTS This work was supported by the Key Scientific Foundation of Chongqing Science and Technology Commission (Project No. cstc 2008ac6047). REFERENCES Cundall, P.A. 1971 A Computer Model for Simulating Progressive Large Scale Movements in Blocky Rock Systems, in Proceedings of the Symposium of the International Society of Rock Mechanics. (Nancy, France, 1971), Vol. 1, Paper No. II-8. Cundall, P.A. and Strack, O.D.L. 1979 A Discrete Numerical Model for Granular Assemblies, Geotechnique, 29(1), 47–65.

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Cundall, P.A. 1987 Distinct Element Models of Rock and Soil Structure, Analytical and Computational Methods in Engineering Rock Mechanics, Ch. 4, 129–163, E.T. Brown, Ed. London: Allen & Unwin. Cundall, P.A. 1988 Formulation of a Three-Dimensional Distinct Element Model—Part I. A Scheme to Detect and Represent Contacts in a System Composed of Many Polyhedral Blocks, Int. J. Rock Mech., Min. Sci. & Geomech. Abstr., 25(3), 107–116. Cundall, P.A. and Hart, R. 1992 Numerical Modeling of Discontinua, J. Engr. Comp., 9, 101–113. Hart, R., Cundall P.A. and Lemos, J. 1988 Formulation of a Three-Dimensional Distinct Element Model—Part II. Mechanical Calculations for Motion and Interaction of a System Composed of Many Polyhedral Blocks, Int. J. Rock Mech., Min. Sci. & Geomech. Abstr., 25(3), 117–125. Itasca Consulting Group, Inc. 2000 UDEC (Universal Distinct Element Code), Version 3.1. Minneapolis. Qingguo Guo, 1991 Engineering Porperties and applications of coarse soils [M] Zhengzhou, China: Yellow River Conservancy Press.

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Axi-symmetric analyses of vertically inhomogeneous elastic multilayered systems J.W. Maina CSIR Built Environment, Pretoria, South Africa

Y. Ozawa & K. Matsui Tokyo Denki University, Saitama, Japan

ABSTRACT: The importance of accounting for material nonlinearity and anisotropic behavior in order to improve the resilient models for pavement materials and numerical analysis is presented in this paper. Effects of material inhomogeneity on the pavement primary resilient responses are investigated by way of worked examples of hypothetical three-layer system, which was analyzed by considering homogenous and inhomogeneous material properties in each of the three layers. Effect of an inhomogeneity parameter that is used in the z-dependent exponential model on the resilient responses in the pavement structure was also investigated. This paper reports on the formulation as well as the findings from detailed analyses that were conducted. 1

INTRODUCTION

1.1 General Methods for structural design of pavements have been shifting from empirical to mechanisticempirical based approach. Several software based on multilayer linear elastic (MLLE) theory have already been developed for this purpose. For example, the AASHTO Pavement design guide for flexible pavements is shifting from an experience (or purely empirical) based design method to a mechanistic-empirical (M-E) design method. The latter approach requires an elastic MLLE analysis engine to compute responses of interest and use empirically established models to determine airport and road pavement distresses like fatigue cracking of asphalt concrete layer or rutting (plastic deformation) of the pavement system. In Europe, a study was commissioned to evaluate a number of widely used software for MLLE analysis and a report was released on the Advanced Models for Analytical Design of European Pavement Structures (AMADEUS, 2000). In Japan, Japanese Society of Civil Engineers (JSCE) published a third library—an introduction to pavement structural analysis. All these indicate that MLLE method play an important part in pavement design and analysis. 1.2 Material inhomogeneity Majority of the standard methods for MLLE analysis and evaluation of road and airport pavements were developed based on the assumption that each layer within the pavement structure is linear elastic, homogeneous and isotropic. However, in the recent past, several researchers have shown the importance of accounting for non-linearity and anisotropic material properties in order to improve the resilient models for pavement materials and numerical analysis (Gazetas, 1982, Graham and Houslby, 1983, and Correia, 1999, Adu-Osei et al. 2001, Kim et al. 2004, 2005). These behaviors can be attributed to pavement material physical properties and the way they are constructed by way of compaction, which results in variable 561

elastic modulus with depth. Moreover, for the case of asphalt concrete layer, its behavior is also temperature sensitive and varies with depth as well. All the these facts call for numerical analysis methods to be developed in such a way as to take into consideration the variation of elastic modulus of pavement layer materials with depth. Tanigawa et al. (1997) assumed the following function to express the depth dependent of elastic shear modulus for a semi-infinite layer: m

⎛z ⎞ G ( z ) = G0 ⎜ + 1⎟ , m ≥ 0, z ≥ 0 ⎝a ⎠

(1)

where G0 is a characteristic value of G; m is a numerical parameter representing inhomogeneity of G; a is a typical length defined (radius of uniformly distributed load ) and z is axial coordinate. From Eq. (1), it is found that G = G0 (≠0) when z = 0. Wang et al. (2003, 2006) presented extensive summary of numerous existing analytical/ numerical solutions for inhomogeneous isotropic media due to a circular load. They presented solutions for the displacements and stresses along the axi-symmetric axis due to uniformly distributed circular load. Their findings indicated that vertical displacement and vertical normal stress are greatly influenced by the material inhomogeneity and degree of anisotropy. In this study, authors applied Hankel transform directly to the governing equations of a multilayered system and derived solutions for the case where the system comprises of an inhomogeneous layer. Further, the influence of material inhomogeneity on the resilient responses (surface displacement, normal and horizontal strains) was evaluated. Since the objective of this study was to look at the effect of material inhomogeneity, cross-anisotropic material behavior (Ozawa et al. 2008) is not considered in this paper. 2

THEORETICAL DEVELOPMENT

2.1 Z-dependent model In this research, elastic modulus of a material is assumed to be constant in the horizontal direction but inhomogeneous in the vertical direction, where it varies exponentially with depth. Materials that behave in this manner have been named z-dependent materials while layers containing these kinds of materials are called z-dependent layers. Displacements due to body forces are different in vertical but uniform in horizontal direction. The interest in this research is to determine responses in addition to body force. Therefore, by ignoring body forces, equilibrium equations in cylindrical coordinate system are formulated as follows: ∂σ r ∂τ rz σ r − σ θ + + =0 r ∂r ∂z

(2a)

∂τ rz ∂σ z τ rz + + =0 r ∂r ∂z

(2b)

where σr is normal stress in the r-axis direction, τrz is shear stress along r–z-plane, σθ is normal stress in the circumferential (θ ) direction and finally, σz is normal stress in the z-axis direction. Displacement in the r-axis direction can be represented as u = u (r, z) and displacement in the z-axis direction can be represented as w = w (r, z). For axi-symmetric case, displacement in the circumferential direction is zero, while strains related to the listed stresses are represented as εr, εθ , εz, and γrz. Similar to the homogeneous case, strain-displacement relationship is as follows:

εr =

u ∂u ∂w ∂u ∂w + , εθ = , ε z = , γ rz = r ∂r ∂z ∂z ∂r 562

(3)

The difference between homogeneous and inhomogeneous materials is on the formulation of stress-strain relationship, whereby in this study, variation of elastic modulus with depth is represented in an exponential form as follows: E ( z ) = E0 e − bz

(4)

where Ε0 is the characteristic value of Ε; b is the inhomogeneity parameter. Strain-stress relationship can then be written in a matrix form as: ⎧ ε r ⎫ ⎡ 1 E ( z ) −ν E ( z ) −ν E ( z ) ⎪ ε ⎪ ⎢ −ν E ( z ) 1 E ( z ) −ν E ( z ) ⎪ θ⎪ ⎢ ⎨ ⎬= ⎪ ε z ⎪ ⎢ −ν E ( z ) −ν E ( z ) 1 E ( z ) ⎪⎩γ rz ⎪⎭ ⎢⎣ 0 0 0 1

0 ⎤ ⎧σ r ⎫ 0 ⎥⎥ ⎪⎪σ θ ⎪⎪ ⎨ ⎬ 0 ⎥ ⎪σ z ⎪ ⎥⎪ ⎪ μ ( z ) ⎦ ⎩τ rz ⎭

(5)

Utilizing Lame’s constants λ (z) and μ (z), where:

λ(z) =

ν E (z) E (z) , μ (z) = (1 + ν )(1 − 2ν ) 2(1 + ν )

Stress-strain relationship is represented as: ⎧σ r ⎫ ⎡ λ + 2 μ ⎪σ ⎪ ⎢ λ ⎪ θ⎪ ⎢ ⎨ ⎬= ⎪σ z ⎪ ⎢ λ ⎪⎩τ rz ⎪⎭ ⎢⎣ 0

λ λ λ + 2μ λ λ λ + 2μ 0 0

0 ⎤ ⎧ εr ⎫ 0 ⎥⎥ ⎪⎪ εθ ⎪⎪ ⎨ ⎬ 0 ⎥ ⎪εz ⎪ ⎥⎪ ⎪ μ ⎦ ⎩γ rz ⎭

(6)

Substituting equation (3) into equation (6) and rearrange, yields: u ∂u ∂w +λ +λ r ∂r ∂z

(7a)

σθ = λ

∂u u ∂w + (λ + μ ) + λ ∂r r ∂z

(7b)

σz = λ

u ∂u ∂w + λ + (λ + μ ) r ∂r ∂z

(7c)

σ r = (λ + μ )

⎛ ∂u ∂w ⎞ τ rz = μ ⎜ + ⎟ ⎝ ∂z ∂r ⎠

(7d)

Further substitution of equation (7) into equation (2) and rearrange, gives: ⎛ ∂2 ∂ ⎛ 1 ∂ ⎞ ∂ ⎞ μ ⎛ ∂ ⎞ ∂u ⎞ ∂ ⎛ (λ + 2 μ ) ⎜⎜ 2 + ⎜ ⎟+ ⎜ −b + ⎟ ⎟⎟ − ⎜ bμ − (λ + μ ) ⎟ w = 0 r r r z z ∂ ∂ λ μ r z⎠ ∂ ∂ ∂ + ∂ 2 ⎝ ⎝ ⎠ ⎝ ⎠ ⎠ ⎝ ∂r

(8a)

⎛ ∂2 1 ∂ ∂ λ + 2μ ∂ λ + 2μ ∂2 ⎞ ⎛ ⎞⎛ ∂ 1 ⎞ −b + ⎟w = 0 ⎜ (λ + μ ) − bλ ⎟ ⎜ + ⎟ u + μ ⎜⎜ 2 + μ ∂z 2 ⎟⎠ ∂z μ ∂z r ∂r ⎝ ⎠ ⎝ ∂r r ⎠ ⎝ ∂r

(8b)

Boundary conditions considering a uniformly distributed surface (z = 0) load, p over an area of radius, a are such that; z = 0, r ≤ a, σ z = − p 563

r > a, σ z = 0 (9) r ≥ 0, τ rz = 0 Resilient response solutions may be obtained through Hankel transform and then Hankel inverse transforms. The general procedure is thoroughly explained in Maina and Matsui (2004).

3

VALIDATION AND ACCURACY OF Z-DEPENDENT ALGORITHM

An algorithm for z-dependent multilayered structure was developed based on the approach explained in the previous section. And in order to validate and confirm accuracy of this algorithm, its results were compared with results from GAMES software, which deals with homogeneous materials (Maina and Matsui, 2004). The GAMES software was developed using closed form solutions based on MLLE theory and is capable of analyzing pavement resilient responses due to five different types of surface loads, namely; vertical, horizontal (shear), torsion, moment (shear and vertical) and centripetal. Since GAMES software cannot perform analysis for z-dependent materials, the z-dependent layer of interest (in this case, first layer) was subdivided into several layers of homogeneous material. An approximate analysis was, thereafter, performed using GAMES and results were compared with those from a z-dependent algorithm. The hypothetical pavement model used is shown in Figure 1. Only the first layer is assumed to be z-dependent layer. In equation (4), b and Ε0 were determined such that elastic modulus of the upper part (z = 0 m) of the first layer would be 2500 MPa and the bottom part would to be 10,000 MPa. The right hand side of Figure 1 shows the elastic moduli for two discrete models (No. 1 and No. 2) together with the values determined from Equation (4). The procedure to generate the discrete layers for the two models shown in Figure 1 was as follows: • The first pavement layer, which was 0.15 m thick, was subdivided into 15 layers, 0.01 m thick each. • For model No. 1, each layer was assigned an elastic modulus value, which was similar to the value determined at its top position using Equation (4). • For model No. 2, each layer was assigned an elastic modulus value, which was similar to the value determined at its bottom position using Equation (4).

Vertical load P = 49 kN a = 15 cm

E(z) = 2500 × Exp(9.242 × z) No.1

h 1 = 0.15 m

h 1 = 0.01 h 2 = 0.01

Young’s modulus Poisson’s ration

h 3 = 0.01

ν1 = 0.35

h 4 = 0.01 Young’s modulus E = 1000 MPa 2

h 2 = 0.35 m

Poisson’s ration ν2 = 0.35

Young’s modulus E3 = 60 MPa P oi s s on’s rati on

Figure 1.

ν3 =0.35

No.2

E1 = 2500

E1 = 2742

E2 = 2742

E2 = 3008

E3 = 3008

E3 = 3299

E4 = 3299

E4 = 3618

E13 = 7579

E13 = 8312

15

∑ i =1

E1 (0) = 2500 E1 (0.01) = 2742 E1 (0.02) = 3008 E1 (0.03) = 3299 E1 (0.04) = 3618

h i = 0.15 h 13 = 0.01 h 14 = 0.01

E14 = 8312

E14 = 9117

h 15 = 0.01

E15 = 9117

E15 = 10000

Unit: m

Hypothetical pavement model.

564

Unit: MPa

Unit: MPa

E1 (0.12) = 7579 E1 (0.13) = 8312 E1 (0.14) = 9117 E1 (0.15) = 10000 Unit: MPa

0.038 Discrete model (No.1) Z-dependent model Discrete model (No. 2)

w (cm)

0.034

0.03

0.026

0.022

0

Figure 2. Table 1.

20

40

Z (cm)

60

80

100

Analytical results for the three models. Stiffness parameters for z-dependent models. Layer 1

Layer 2

Layer 3

Unit Type 1 Type 2 Type 3 Type 4 Type 5 Type 6 Type 7 Type 8 Type 9 Type 10 Type 11 Type 12 Stiffness b 1/m –9.24 –5.00 5.00 9.24 –0.10 –0.50 –0.10 –0.50 –1.00 –2.00 Parameter E0 MPa 2500.0 3436.4 7275.0 10000.0 500.0 2000.0 60.0 60.0 60.0 60.0

–5.00 60.0

–10.00 60.0

The analytical results are shown in Figure 2. This figure shows displacement with depth below the centre of the load (r = 0). Displacements determined from z-dependent model were in between the displacements determined using the two discrete models. There was a good agreement between displacements determined from the z-dependent algorithm and displacements from discrete models which validates the theory developed and confirmation of the accuracy of z-dependent algorithm. 4

ANALYSIS FOR Z-DEPENDENT MATERIALS

4.1 Development of analytical model In order to evaluate how variation of elastic modulus with depth within a particular pavement layer can affect resilient responses when compared to responses for homogenous materials, a three layer pavement model was selected. For each analytical case considered, material in only one layer was assumed to be z-dependent. Analyses for surface displacement, normal and horizontal strains were performed and compared to the case where all the layers were assumed to be homogeneous. Table 1 lists parameters Ε0 and b for different types of z-dependent models that were considered, while Figure 3 shows the isotropic and homogenous pavement model that was used for benchmarking and called Type 0. External uniformly distributed load was 49 kN, which was assumed to act over an area of radius 0.15 m. Since this was hypothetical exercise, it should be noted that stiffness parameters Ε0 and b shown in Table 1 were determined in such a way that, for each model discussed in the following sub-sections, the median value of elastic modulus in the inhomogeneous layer would be similar to the value used in its corresponding benchmark (homogeneous) model. Therefore, giving the inhomogeneous layer a higher elastic modulus value at the top and lower value at the bottom or vice versa would, theoretically, make it a layer softening or stiffening. In practical problems, stiffness parameters would be determined from such procedures as backcalculation analysis. 565

4.2 Z-dependent model (first layer only) Figure 4 shows pavement model that was used for analysis considering z-dependent material in the first layer. Elastic modulus of the first layer is assumed to be a function of z, whereby Ε0 is the elastic modulus at the top position of the first layer and a positive parameter b represents a softening layer, while a negative parameter b represents a stiffening layer. By varying the values of Ε0 and b, four different models were developed, namely (Type 1∼Type 4) and analyses using values from each of the four models were performed. Layer moduli values for the different models are graphically presented in Figure 5. Figure 6(a) shows results of surface displacements for models Type 0, Type 1, and Type 4. Below the load centre, deflections from a model depicting a softening top layer (Type 4) were smaller compared to those from a stiffening layer (Type 1). For the three models considered, the difference in displacements was evident in the vicinity of the loaded region and insignificant at points beyond 3 times the load radius. Figure 6(b) shows variation of normal vertical strain (εz) at points along the z-axis and below the load centre (r = 0). These are analytical results for all the 5 models (Type 0∼Type 4). For each model, a discontinuity of strain is observed at layer interfaces. In the first layer where z-dependent material was assumed, differences are observed in strain (εz) trends among the five models. Type 0 shows tensile strain on pavement surface although a compressive stress σz = −0.707 MPa is acting. The reason for this phenomenon could be attributed to relatively higher horizontal compressive stresses σx = σy = −1.280 MPa when combined with Poisson’s ratio may result in tensile strain in the z-direction. Compared with model Type 0, layer softening models (Type 3 and Type 4) had higher tensile strains on the surface and higher compressive strain at the bottom of the first layer. Layer stiffening models had relatively lower results. Type 1 layer stiffening model resulted in compressive normal strain (εz) on the surface. All the five models (Type 0∼Type 4) were set in such a way that the median elastic modulus would be the same. However, strain results were similar at about 0.05 m from the surface. Material inhomogeneity in the first layer had higher influence on normal vertical strain results in the third layer than in the second layer. Figure 6(c) shows variation of normal horizontal strain (εr) at points along the z-axis and below the load centre (r = 0). Again, these are analytical results for all the 5 models (Type 0∼ Type 4) and they all show very comparable compressive strains at the surface. At the bottom of the layer the results show tensile strains whose trends are opposite to the layer moduli. Type 4 had the highest value and Type 1, the smallest. The influence of material inhomogeneity in the first layer on horizontal normal strain results in the third layer was insignificant.

Vertical load

Vertical load P = 49 kN a = 15 cm

h1 = 0.15 m

P = 49 kN a = 15 cm

Young’s modulus E1= 5000 MPa Poisson’s ration ν1 = 0.35

h1 = 0.15 m

Young’s modulus E2 = 1000 MPa h2 = 0.35 m Poisson’s ration ν = 0.35 2

Poisson’s ration ν1 = 0.35

Young’s modulus E2 = 1000 MPa h2 = 0.35 m Poisson’s ration ν = 0.35 2

Young’s modulus E3 = 60 MPa Poisson’s ration ν3 = 0.35

Figure 3.

Young’s modulus E1= E0 exp(−bz)

Young’s modulus E3 = 60 MPa Poisson’s ration ν3 = 0.35

Homogeneous pavement model.

Figure 4.

566

Inhomogeneous (first layer) model.

Elastic modulus (MPa)

10000

Type 0 Type 1 Type 2 Type 3 Type 4

1000

100

10 0

20

40

60

80

100

Z (cm)

Figure 5.

Distribution of layer moduli with depth.

0.0001

0.04

(a)

0.035 0.03

Type 0

0.00005

Type 1

0

(b)

–0.00005

0.025

εz

w (cm)

Type 4

Type 0 Type 1 Type 2 Type 3 Type 4

–0.0001

0.02 –0.00015

0.015 –0.0002

0.01 –0.00025

0.005 0

50

100

150

200

250

–0.0003

300

0

r (cm)

20

40

z (cm)

60

80

100

0.00015

(c)

0.0001

εr

0.00005

Type 0 Type 1 Type 2 Type 3 Type 4

0

–0.00005

–0.0001

–0.00015 0

10

20

30

40

50

60

70

80

90

100

z (cm)

Figure 6.

Results for displacements and strains considering inhomogeneous first layer.

4.3 Z-dependent model (second layer only) Figure 7 shows pavement model that was used for analysis considering z-dependent material in the second layer. Values of Ε0 and b were varied to form two models (Type 5 and Type 6) and analyses were performed. Ε0 and b values were selected such that, for each model, the median value of elastic modulus in the second layer would be 1000 MPa. Figure 9(a) shows surface displacements using the two models. The effect of material inhomogeneity is evident between the load edge to 10 times the load radius (i.e. r = 15 cm∼150 cm). Compared to Type 0, surface displacement results from layer stiffening model (Type 5) were smaller and those from layer softening model (Type 6) were bigger. Figure 9(b) shows variation of normal vertical strain (εz) at points along the z-axis and below the load centre (r = 0). Similar to the previous case of material inhomogeneity in the first layer, a discontinuity of normal vertical strain (εz) is observed at layer interfaces. Further, the effect of material inhomogeneity on the normal vertical strain within the second layer is considerable. Figure 9(c) shows variation of normal horizontal strain (εr) at points along the z-axis and below the load centre (r = 0). There is continuity of normal horizontal strain at layer 567

Vertical load P = 49 kN a = 15 cm

h 1 = 0.15 m

h 2 = 0.35 m

Young’s modulus

E1 = 5000 MPa

Poisson’s ration

ν1 = 0.35

Young’s modulus

E2 = 2000 × Exp(−3.961 × z) MPa

Poisson’s ration

ν2 = 0.35

Young’s modulus

E3 = 60 MPa

Poisson’s ration

ν1 = 0.35

Elastic modulus (MPa)j

10000

Type 0 Type 5

1000

Type 6

100

10 0

20

40

60

80

100

Z (cm)

Figure 7. Inhomogeneous (second layer) model. Figure 8.

0.04

(a)

0.0001

0.035

Type 0

(b)

0

Type 5

0.03

-0.0001

Type 6 0.025

-0.0002

εz

w (cm)

Distribution of layer moduli with depth.

0.02

Type 0 -0.0003

0.015

Type 5 Type 6

-0.0004

0.01

-0.0005

0.005 0

50

100

150

200

250

0

300

20

40

r (cm)

60

80

100

z (cm)

0.00015

(c)

0.0001

εr

0.00005

Type 0

0

Type 5 Type 6

-0.00005

-0.0001

-0.00015 0

10

20

30

40

50

60

70

80

90

100

z (cm)

Figure 9.

Results for displacements and strains considering inhomogeneous second layer.

interfaces. Because of this continuity at layer interfaces, the effect of material inhomogeneity on the normal horizontal strain (εr) in the lower part of the first layer, within the second layer and upper part of the bottom layer is considerable. 4.4 Z-dependent model (third layer only) Figure 10 shows pavement model that was used for analysis considering z-dependent material in the third layer. Ε0 was held constant and parameter b was varied to form six models (Type 7∼Type 12) and analyses were performed. As z → ∞, layer softening model for semiinfinite subgrade layer would result in zero elastic modulus and infinity displacement, hence only layer stiffening models were used. Elastic moduli for different z-dependent models are graphically presented in Figure 11. Figure 12(a) shows surface displacements for four of the models used. As parameter b increases, surface displacements decrease, which is an indication that material inhomogeneity in the subgrade layer significantly affect pavement surface displacements. 568

Vertical load P = 49 kN a = 15 cm

h1 = 0.15 m

Young’s modulus E = 5000 MPa 1 Poisson’s ration

h2 = 0.35 m

Elastic modulus (MPa)

10000

ν1 = 0.35

Young’s modulus E2 = 1000 MPa Poisson’s ration

ν2 = 0.35

Young’s modulus E3 = E0 × Exp(− b × z) Poisson’s ration

1000

Type 0 Type 7 Type 8 Type 9 Type 10 Type 11 Type 12

100

10

ν3 = 0.35

0

20

40

60

80

100

Z (cm)

Figure 10. Inhomogeneous (third layer) model.

(a)

Figure 11.

0.04

Distribution of layer moduli with depth.

0.0001

(b)

0.035 0

0.03 –0.0001

Type 0 –0.0002

0.02

Type 7

εz

w (cm)

0.025

Type 0

0.015

Type 8

–0.0003

Type 9

Type 7

0.01

–0.0004

Type 8 Type 12

0.005

Type 10 Type 11

–0.0005

Type 12 0

–0.0006

0

50

100

150

200

250

300

0

r (cm)

10

20

30

40

50

60

70

80

90

100

z (cm)

0.00015

(c) 0.0001

Type 0 Type 7 Type 8 Type 9 Type 10 Type 11 Type 12

εr

0.00005

0

–0.00005

–0.0001

–0.00015 0

10

20

30

40

50

60

70

80

90

100

z (cm)

Figure 12.

Results for displacements and strains considering inhomogeneous third layer.

Figure 12(b) shows variation of normal vertical strain (εz) at points along the z-axis and below the load centre (r = 0). The effect of material inhomogeneity in the subgrade layer on normal vertical strain in the first and second layer was found to be insignificant. However, (εz) in the third layer was highly influenced by material property within the layer. Figure 12(c) shows variation of normal horizontal strain (εr) at points along the z-axis and below the load centre (r = 0). Due to continuity of the normal horizontal strain at layer interfaces, the effect of material inhomogeneity in the third layer on the normal horizontal strain (εr) is significant within the lower part of the second layer and the whole of the third layer. 5

OBSERVATIONS AND CONCLUDING REMARKS

Algorithm for multilayered linear elastic analysis considering z-dependent materials has been developed based on the approach presented in this paper. 569

1. Analytical results for z-dependent algorithm agreed well with GAMES results when layer discretization was performed. This confirms accuracy of the algorithm developed. 2. When the top pavement layer is considered to be z-dependent, surface displacements for layer stiffening models were bigger than for layer softening models. The effect of z-dependent top layer was smaller for layer stiffening models than for layer softening models. 3. The effect of z-dependent second layer on the surface displacement was negligible. 4. There were significant effects of the magnitude of parameter b for z-dependent subgrade on surface displacements. 5. Because of discontinuity at layer interfaces, normal vertical strain (εz) was only affected in the layer that was considered to be z-dependent. 6. Because of continuity at layer interfaces, normal horizontal strain (εr) in the layer that was considered to be z-dependent as well as in parts of adjacent layers closer to the interface with z-dependent layer was affected. REFERENCES Adu-Osei, A., Little, D.N. and Lytton, R.L. 2001. Cross-Anisotropic Characterization of Unbound Granular Materials. Transportation Research Records, No. 1757. pp. 82–91. Correia, A.G.(ed). 1999. Unbound Granular Materials, Laboratory Testing, in-situ testing and modelling, Proceedings of an International Workshop on Modelling and Advanced Testing for Unbound Granular Materials. Lisbon. Gazetas, G. 1982. Stresses and Displacements in Cross-Anisotropic Soils. Journal of Geotechnical Engineering, ASCE, Vol. 108, No. GT4. pp. 532–554. Graham, J. and Houlsby, G.T. 1983. Anisotropic Elasticity of Natural Clay, Geotechnique, Vol. 33, No. 2, pp. 164–181. Kim, S.H., Little, D.N., Masad, E. and Lytton, R.L. 2005. Estimation of level of anisotropy in unbound granula layers considering aggragate physical properties. International Journal of Pavement Engineering. Vol. 6. No. 4. pp. 217–227. Kim, S.H., Little, D.N., Masad, E. and Lytton, R.L. 2004. Prediction of anisotropic resilient responses for unbound granular layer considering aggregate physical properties and moving wheel load. International Center for Aggregate Research. Maina, J.W. and Matsui, K. 2004. Developing Software for Elastic Analysis of Pavement Structure Responses to Vertical and Horizontal Surface Loadings. Transportation Research Records, No. 1896. pp. 107–118. Ozawa, Y., Maina, J.W. and Matsui, K. 2008. Influence of Cross-Anisotropy Material behavior on Back-calculation Analysis of Multi-layered System. ICPT. Sapporo Japan. Tanigawa, Y., Jeon, S. and Hata, T. 1997. Analytical Development of Axisymmetrical Elastic Problem for Semi-Infinite Body with Kassir’s Nonhomogeneous Material Property. Japan Society of Mechanical Engineers. Vol. 63. No. 608. pp. 86–93. The Committee on Pavement Engineering, JSCE. 2005. Introduction to Pavement Structural Analysis Based on Multi-layered Elastic Systems—Application with GAMES (General Analysis of Multilayered Elastic Systems). Pavement Library 3. Maruzen. Tokyo, Japan. Wang, D.C., Pan, E., Tzeng, C.S., Feng H. and Liao, J.J. 2006. Displacements and Stresses due to a uniform vertical circular load in an inhomogeneous cross-anisotropic half space. International Journal of Geomechanics, Vol. 6, No. 1, 1–10. Wang, D.C., Tzeng, C.S., Pan, E. and Liao, J.J. 2003. Displacements and Stresses due to a vertical point in a inhomogeneous transversely isotropic half space. International Journal of Rock Mechanics and Mining Sciences, 40(5), 667–685.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Models to estimate k subgrade reaction modulus values based on deflection basin parameters C.Y. Suzuki University of São Paulo, São Paulo, SP, Brazil

C.R.G. Santos, S. Ferri, F.M. Lopes, R.T.G. Cruz & A.M. Azevedo Planservi Engenharia Ltda., São Paulo, SP, Brazil

ABSTRACT: The structural design of concrete pavements according to AASHTO and PCA methods makes use of modulus of reaction (k) from the subgrade and subbase/subgrade system as parameter to calculate slab thickness. Conventionally, the k-values must be determined through NDT testing that is expensive and lengthy. The objective of this paper is to present a correlation between k-values and deflection measurements, which are easier and cheaper to obtain; thereby giving the inspector a faster method to determine and check the desired k-values. The correlations are results of a computer simulation with the ELSYM-5 software program. The resulting models from the maximum deflection and area parameter had good results, unlike the radius of curvature. These models provide improved ability and agility in the evaluation of subgrade layers and the subbase of concrete pavement, when compared to the plate bearing test. 1

INTRODUCTION

Traditionally in Brazil jointed concrete pavement has been used for heavy traffic loads. Loadtransfer devices, such as dowel bars are commonly used in Brazilian concrete pavements. The Portland Cement Association design method, translated by ABCP (Associação Brasileira de Cimento Portland ), is regularly used and accepted for rigid pavement design. In the structural design, one of the parameters is the value of modulus of reaction (k) from the subgrade or subbase/subgrade system, which is conventionally determined through nondestructive (NDT) testing. As in other countries, in Brazil, these tests must conform to ASTM-D-1196 and AASHTO T-222, using metallic plates with a 76-cm (30-in.) diameter to measure the required pressure to produce a 1.3-cm (0.5-in.) vertical displacement. Due to practical and economic difficulties to carry out this test, the values of modulus of reaction (k) can be estimated according to the subgrade CBR (California Bearing Ratio) values. This method is in compliance with ABCP, which is an important organization in Brazil to represent the cement industry and currently develops studies about Portland cement structures, such as highway pavements. The subbase layers improve the k-values of the foundation system. Beyond the correlation between subgrade CBR and the k-value, in this paper k-values are used on the top of subbases, due to granular or cemented materials utilization. The quality of lower layers and the foundation support has an important influence on the long term performance of concrete pavement. The maximum deflection measurement has been employed to obtain on-site field results that are faster to obtain than CBR, which requires four days for results and do not reproduce the real behavior of untreated and cement treated layers. Different types of equipments measure the deflections and technological advances have allowed better and precise measurements.

571

The purpose of this paper is to present guidelines to provide improved ability and agility in the evaluation of subgrade layers and the subbase of concrete pavement using the measurements of FWD (Falling Weight Deflectometer) equipment, rather than the plate bearing test. 2

MODULUS OF SUBGRADE REACTION

The values of modulus of reaction from the subgrade or subbase/subbgrade system are used as parameters on the rigid pavement design procedure to determine the necessary slab thickness, based on AASHTO (American Association of State Highways and Transportation Officials) and PCA (Portland Cement Association) design procedures. These methods are based on Westergaard theory to define the foundation modeling where the concrete slab will be supported. In this theory, a concrete slab was treated as a homogeneous and an elastic solid, supported by the subgrade that is considered a dense liquid, according to Winkler modeling. In accordance with AASHTO (1993), the effective modulus of subgrade reaction (k-value) must be determined for the design procedure to calculate the slab thickness, which depends on the subgrade characteristics and the weather variation, which affect the subgrade resilient modulus. The k-value, which indicates the foundation’s structural capacity, is obtained through field testing using a static load. However, this is too expensive and demands a lot of work and time. These tests could be replaced by correlations of easier tests, as CBR testing. In Brazil, the PCA concrete design method is recommended and used. Its translation, edited by ABCP, presents a correlation between k-value and the subgrade CBR value. The modulus of reaction must be determined on the top of the foundation, and an increase on the k-value is obtained due to the use of untreated or cement treated subbases. Therefore, the ELSYM-5 (Elastic Layered System) software is used to obtain deflection parameters of FWD equipment through computer simulations for different types of pavement structures. This computer program applies the finite difference model to determine stresses, strains and displacements produced by a static loading. 3

DEFLECTION PARAMETERS

The deflection parameters that are considered in this study are: maximum deflection, radius of curvature and area parameter. They were simulated using a load plate as well as FWD equipment system. Assuming that the subgrade analysis is an elastic system in a homogenous and isotropic environment, it is possible to use Boussinesq–Love’s equation to calculate the maximum deflection. The following expression (1) is used to estimate deflection beneath load point application. D=

(

)

2 ⋅ 1− μ2 ⋅ p ⋅ r E

(1)

where D = maximum deflection on the load point application, cm; μ = Poisson´s ratio; p = pressure of contact tire/pavement, kgf/cm2; r = radius of contact area cm; and E = elasticity modulus, kgf/cm2. Usually, the resilient modulus (MR) is determined through correlations with the CBR value. For soils, the following equation (2) is frequently used and recommended by AASHTO. MR(MPa ) = 10 ⋅ CBR(%)

(2)

where MR = resilient modulus; and CBR = Subgrade California Bearing Ratio. Another parameter that can be used to characterize the structural condition of a pavement is the radius of curvature, which is a parameter that indicates the curvature of the deflection basin 572

in a critical portion, generally considered to be 25 cm from the center of the load. Figure 1 shows the parabolic arc. A low value of radius of curvature indicates a severe deformation in the deflection basin, indicating a critical structural condition. The expression used to determine the radius of curvature was the one adopted by the Brazilian National Highway Department (Departamento Nacional de Estradas de Rodagem— DNER), contained in DNER ME-024/94: R=

6250 2 × ( D0 − D25 )

(3)

where R = radius of curvature of the deformation basin, m; D0 = deflection beneath of load application point, 10−2 mm; and D25 = deflection to 25 cm from the load application point, 10−2 mm. Other parameter widely used to determine the structural pavement condition, also recommended by AASHTO is the area parameter (A) of deformation basin calculated using expression (4) presented below. Deflections D30, D60 and D90 were obtained through ELSYM-5 software, which simulated deflection measurements from the point of load application with geophones offset from 30, 60 and 90 cm. ⎡ D D D ⎤ A = 15 ⎢1 + 2 30 + 2 60 + 90 ⎥ D D D0 ⎦ 0 0 ⎣

(4)

where A = Area parameter, cm; D0, D30, D60 and D90 = deflection offset from 0, 30, 60 and 90 cm respectively, from the point of load application 10–2 mm. 4

DETERMINING THE REACTION MODULUS (K)

This research makes use of correlations between k-values and subgrade CBR proposed by PCA and according to ABCP, despite the lack of information about the field conditions and characteristics of the tested materials for the research establishment. k = 1.26 + 20.67 ⋅ ln(CBR )

(5)

where k = modulus of subgrade reaction, MPa/m; and CBR = Subgrade California Bearing Ratio, %. This expression was determined through values presented in ABCP (1998). In this study k-values are presented contemplating different types of materials and thicknesses for the subbase layer. These values are an adaptation from the abacus used by PCA (1984) design method.

Figure 1.

Radius of curvature.

573

Table 1 below presents the increase on the values of the modulus of reaction (k) with the usage of subbase layers, untreated or cement-treated materials. For granular subbases the increase of k-values of the system in relation to k-values of the subgrade is lower than that of cement-treated materials, as shown below. From the values presented, correlations were determined between subgrade k-values and subbase system, for both granular and cement-treated layers. In all of these cases, high R2 coefficients were obtained, denoting a good fit of the models as shown below in Table 2. 5

DEFLECTIONS ON TOP OF THE SUBBASE

To estimate deflections on the top of the subbase layer, an elastic system constituted of two layers and a typical load for a simple wheel with FWD equipment were used. The maximum deflections could be calculated using Burmister equations or the ELSYM-5 Table 1. Increase of k-values in relation to different materials and thicknesses (ABCP, 1998). Values of modulus of reaction on the top of subbase/subgrade system (MPa/m), Thickness of subbase (cm) Cement-treated subbase

Subgrade suport value

Granular subbase

CBR (%)

k (MPa/m)

10 cm

15 cm

20 cm

10 cm

15 cm

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

16 24 30 34 38 41 44 47 49 51 53 54 56 57 59 60 61 62 63

19 27 34 38 42 45 48 52 54 56 58 59 61 62 64 65 66 67 68

22 31 38 42 46 50 53 56 58 60 62 63 65 66 68 69 70 71 73

27 37 44 49 53 56 60 63 65 67 69 70 72 73 75 76 77 78 79

65 87 101 111 120 127 133 140 144 148 152 154 158 160 164 166 168 170 172

98 126 145 158 169 177 186 194 199 204 209 211 216 219 224 226 229 231 233

Table 2.

Correlations between k-values and subgrade CBR.

Layers

h (cm)

Equation

R2

Subgrade

–

k = 1.26 + 20.67 × ln (CBR)

0.9997

Granular subbase

10 15 20

k = 3.61 + 21.65 × ln (CBR) k = 7.18 + 21.89 × ln (CBR) k = 12.57 + 22.47 × ln (CBR)

0.9980 0.9984 0.9992

Cement subbase

10 15

k = 36.81 + 45.84 × ln (CBR) k = 63.57 + 57.78 × ln (CBR)

0.9976 0.9963

574

software, which assumes a linear elasticity for the employed materials used on the analysis. In this paper, simulations with ELSYM-5 software were used to determine the deflections. Resilient modulus of 300 MPa were considered for granular subbase and a resilient modulus of 15.000 MPa, considered for cement-treated material. Additionally, these parameters, for the illustrative simulation were presented in Table 3. Replacing equation (1) for maximum deflections by equation (5), it is possible to determine the correlation between the modulus of reaction and the maximum deflection using FWD equipment simulations. Equation 6 below presents this model. k = 150.81 − 20.67 ⋅ ln( D )

(6)

where k = modulus of subgrade reaction, MPa/m; D = maximum deflection obtained with FWD on the top of the subgrade, 10–2 mm. With the results of the simulations, correlations between subgrade CBR and deflectometric parameters of several thickness and subbase materials were determined. Table 4 below presents these correlations and the respective R2 coefficients. The radius of curvature equation used to determined the CBR of cement-treated subbase presents the lowest R2 coefficients. All the other models present higher R2 values, which are very close to 1. Below, for each one of the three studied deflectometric parameters, the models were determined by the modulus of reaction. According to each type of subbase and thicknesses, the equations from Table 4 were replaced by the equations of Table 2, resulting in the correlations presented in Tables 5 through 7 below. For each parameter, the correlations from ELSYM-5 simulations were replaced in Equation 5 of the modulus of reaction. Table 8 presents the correlation between maximum deflection, radius of curvature and area parameter measured through FWD equipment and the values of modulus of reaction. Table 3.

Parameters used on ELSYM-5 software simulation.

Layers

Resilent modulus (MPa)

Untreated subbase Cement-treated subbase Subgrade

Table 4.

300 15,000 10 × CBR

Poisson coefficient 0.40 0.25 0.45

Equipment

Radius (cm)

Load (kgf)

Deflection

FWD

15

4100

D0, D25, D30, D60 e D90

Expressions of correlations between deflectometer parameters and subgrade’s CBR.

Parameters

R2

h (cm) Granular subbase

CBR = f (D) 10 15 20 CBR = f (A) 10 15 20 CBR = f (R) 10 15 20

CBR = 4202.93 × D–1.279 CBR = 8354.42 × D–1.468 CBR = 16,129.28 × D–1.648 CBR = 1.678 × 1012 × A–7.484 CBR = 1.000 × 109 × A–5.212 CBR = 6.216 × 107 × A–4.360 CBR = 1.345 × 10–2 × R1.698 CBR = 2.805 × 10-4 × R2.541 CBR = 8.506 × 10-7 × R3.806

0.9999 0.9997 0.9989 0.9988 0.9997 0.9982 0.9989 0.9994 0.9998

h Cement-treated (cm) subbase

R2

10 15

CBR = 2301.92 × D–1.449 CBR = 1616.40 × D–1.503

10 15

CBR = 1.068 × 1013 × A–6.873 0.9981 CBR = 8.548 × 1015 × A–8.219 0.9874

10 15

CBR = 2.366 × 10-10 × R4.094 0.9453 CBR = 2.672 × 10–20 × R6.953 0.6005

0.9998 0.9999

where CBR = Subgrade California Bearing Ratio, %; D = Maximum Deflection, 10–2 mm; A = Area Parameter, cm; and R = Radius of curvature, m.

575

Table 5.

Maximum value of allowable maximum deflections on top of subbase. Values of deflection on the top of the subbase/ subgrade system (10–2 mm) Granular material

Subgrade values

Cement-treated material

CBR (%)

D (10–2 mm)

10 cm

15 cm

30 cm

10 cm

15 cm

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

680 462 345 285 235 203 175 152 138 125 114 108 98 94 85 81 77 73 70

391 293 228 197 171 153 137 119 111 103 96 92 86 83 77 74 72 69 67

296 224 180 159 140 124 113 103 97 91 85 83 78 75 71 69 66 64 61

177 142 120 109 98 91 86 80 75 73 69 67 65 64 60 59 58 57 55

136 98 79 68 60 54 49 44 42 39 37 36 34 33 31 30 29 28 27

92 66 53 46 40 37 33 30 29 27 26 25 24 23 21 21 20 20 19

Table 6.

Maxium value of area parameter on top of the subbase. Values of area parameter on the top of the subbase/ subgrade system (cm)

Subgrade support value

Granular material

CBR (%)

10 cm

15 cm

20 cm

10 cm

15 cm

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

40 37 36 35 34 33 32 32 32 31 31 31 30 30 30 30 29 29 29

46 43 41 39 38 37 36 35 34 34 33 33 32 32 31 31 31 30 30

51 47 45 43 41 39 38 37 36 36 35 34 33 33 32 32 31 31 31

71 67 64 62 61 59 58 57 56 55 55 54 54 53 53 52 52 51 51

80 76 73 71 70 68 67 66 66 65 64 64 63 62 62 61 61 61 60

Cement-treated material

576

Table 7.

Minimum radius of curvature on top of the subbase. Values of radius of curvature on the top of subbase/subgrade system (m)

Subgrade support value

Granular material

Cement-treated material

CBR (%)

10 cm

15 cm

20 cm

10 cm

15 cm

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

19 24 28 32 36 39 42 46 48 51 54 57 59 61 64 66 68 71 73

32 38 42 46 50 53 56 58 61 63 65 67 69 71 73 75 77 78 80

46 52 56 59 62 65 67 69 71 73 74 76 77 79 80 82 83 84 85

266 294 315 333 348 361 373 384 394 403 412 420 428 435 442 449 455 461 467

722 765 797 823 845 864 881 896 910 922 934 945 955 964 973 982 990 998 1005

Table 8. Correlations between modulus of reaction and deflectometer parameters on top of the subbase. Parameters

h (cm)

Granular subbase

h (cm)

Cement-treated subbase

k = f(D)

10 15 20

k =184.28 – 27.686 × ln (D) k = 204.82 – 32.128 × ln (D) k = 230.25 – 37.043 × ln (D)

10 15

k = 391.66 – 66.459 × ln (D) k = 490.44 – 86.849 × ln (D)

k = f(A)

10 15 20

k = 612.94 – 162.011 × ln (A) k = 460.74 – 114.077 × ln (A) k = 415.761 – 97.97 × ln (A)

10 15

k = 1411.894 – 315.035 × ln (A) k = 2183.198 – 474.895 × ln (A)

k = f(R)

10 15 20

k = 36.753 × ln (R) – 89.666 k = 55.602 × ln (R) – 171.826 k = 85.503 × ln (R) – 301.475

10 15

k = 187.658 × ln (R) – 979.142 k = 401.726 × ln (R) – 2540.506

6

PRACTICAL EXAMPLE

The following example illustrates how deflectometer measurements obtained in the field (using FWD equipament) can be used to determine k values. Ensure that the modulus of reaction is higher than or equal to 53 MPa/m at the top of a 15 cm granular base located over a subgrade with a CBR value equal to 8%. In order to obtain an allowable deflectometric measurement using the proposed models, the maximum observed field values of deflection must be 114 × 10–2 mm, the radius of curvature must be higher than 56 m and the area parameter must not exceed 36 cm, as presented in Table 9 and shown in Figures 2, 3 and 4, respectively. 577

Table 9.

Example of a deflectometer measurement using FWD equipment.

Layers

Thickness (cm)

k (MPa/m)

D (10–2mm)

Area parameter (cm)

Radius of curvature (m)

Subgrade CBR = 8% Granular subbase

– 15

44 53

173 114

– 36

– 56

80 Subgrade Granular Subbase h = 10 cm 70

Granular Subbase h = 15 cm Granular Subbase h = 20 cm Example Subgrade Example Granular Subbase

60

Modu lus of Reaction, k (MPa/m)

50

8

1

10

40

30

20

10 20

114

100

CBR (%)

173

100 0

−2

D0 FWD (10 mm)

Figure 2. Example to determine allowable maximum deflection to control the finished layer using FWD.

100 Granular Subbase h = 10 cm 90 Granular Subbase h = 15 cm Granular Subbase h = 20 cm

80

Example Granular Subbase 70

60

Modulus of Reaction, k (MPa/m)

50

40

30

20

10

0 8

1

10

CBR (%)

20

36

10 0 Area Parameter (cm)

Figure 3. Example to determine the maximum value of area parameter to control the finished layer using FWD.

7

CONCLUSIONS AND RECOMMENDATIONS

The theoretical analysis developed in this study has shown that deflectometer criteria can be used to estimate the values of modulus of reaction from subgrade and subbase/subgrade system, replacing static load plate tests by maximum deflection measures, radius of curvature and area parameter. 578

100 Granular Subbase h = 10 cm

90

Granular Subbase h = 15 cm Granular Subbase h = 20 cm

80

Example Granular Subbase 70

60

Modulus of Reaction, k (MPa/m)

50

40

30

20

10

0 8

1

10

CBR (%)

20

56 Radius of Curvature (m)

100

Figure 4. Example to determine the minimum value of radius of curvature to control the finished layer using FWD.

Based on the correlation models from the tables and/or figures presented, it is possible to obtain the necessary field measurements to allow a faster release/approval of the foundationlayers of the concrete pavements, through the determination of FWD subgrade deflections as well as basin parameters on the surface of the subbase. This allows the inspector to identify the real values of the modulus of reaction (k) and compare with those adopted in the structural design. It should be mentioned that correlations for radius of curvature of cement treated bases did not present good results. It is suggested that static load plate tests be conducted in the field in conjunction with deflection measurements using the FWD in order to calibrate the proposed theoretical models presented in this paper. REFERENCES AASHTO, 1993. American Association of State Highway and Transportation Officials. AASHTO Guide for Pavement Structures. AASHTO, ISBN: 1-56051-055-2. Washington, D.C. ABCP, 1998. Associação Brasileira de Cimento Portland. Estudo Técnico 97: Dimensionamento dos pavimentos rodoviários e urbanos de concreto pelo método da PCA/1984. ABCP, ISBN: 85-8702404-3. São Paulo, Brasil. Huang, Y.H. 1993. Pavement analysis and design. Prentice Hall, ISBN: 0-13-655275-7. Englewood Cliffs, New Jersey, USA. Pinto, S. & Preussler, 2002. E. Pavimentação rodoviária: conceitos fundamentais sobre pavimentos flexíveis. Editora Copiarte, ISBN: 85-902537-1-6. Rio de Janeiro, Brasil. Preussler, L.A. 2007. Contribuição ao estudo da deformabilidade de camadas de pavimento. 129 f. Dissertação. (Mestrado em Engenharia de Transportes)—Escola Politécnica da Universidade de São Paulo, Universidade de São Paulo, São Paulo, Brasil.

579

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Application of gray theory in settlement forecast of rock-fill highway embankment X. Wang & W. Qin School of Civil Engineering and Architecture, Centre South University, Changsha, Hunan, P.R. China

M.C. Wang Department of Civil and Environment Engineering, College of Engineering, the Pennsylvania State University, University Park, USA

Z. Wang China Communications Construction Company Ltd, Beijing, P.R. China

ABSTRACT: The gray theory was used to forecast the future settlement of a rock-fill highway embankment based on the current settlement data. The monitored embankment settlement data were first compiled and analyzed with regard to their relation with time. The results of analysis showed strong relation between the two, and the relation fitted a negative exponential function fairly well. The unambiguous trend of settlement increase with time made it possible to use the gray system theory together with the current settlement data to forecast the future embankment settlement. The monitored settlement database was then used to develop an equal time interval GM(1,1) model of the gray system theory. Later, the model parameters were optimized by means of the least-square method. The results of study showed that the optimized model was able to forecast the settlement of the rock-fill highway embankment under study reasonably well. 1

INTRODUCTION

Roadway embankment settlement is an important parameter influencing the riding quality and stability of the roadway structure. There are many factors that affect the embankment settlement. Some of the more important factors are the embankment materials and properties, embankment dimensions and geometry, loading conditions especially traffic loading, supporting foundation, and environmental influences such as temperature and moisture conditions. Because it is difficulty to obtain and also to quantify most of these factors accurately, to determine the embankment settlement at any desired time is by no means an easy task (2nd Highway Engineering Co. Ltd., 2003). Moreover, the intricate interactions among the various influence factors, such as material properties change with time coupled with varying loading, temperature, and moisture conditions, make it more difficult to forecast future embankment settlement. Therefore, a method that can effectively forecast roadway embankment settlement is not yet available (Cao & Zhao 2004, Wei & Liu 2004). In an attempt to develop such a method, this study was undertaken. The study utilized the theory of gray system developed by Deng in 1982 together with the monitored roadway settlement data of a newly constructed rock-fill embankment. The theory was developed based on the notion that the future relation between any two variables can be forecasted if the current data show strong relation between the two variables (Liu et al. 2004). The rationale is that, no matter how dispersed the data points are, there must be an inherent pattern, though not obvious, that dictates the current relation between the two variables. In application, the original database is subjected to serial transformation; and throughout the transformation process, serial gray differential coefficients are defined. After transformation, an approximate differential equation of GM model was established. The GM model provides the basis for 581

forecasting the future relation between the two variables (Feng et al. 2004). The results of the study are presented in this paper. 2

EMBANKMENT SETTLEMENT DATABASE

The embankment settlement database was obtained from the rock-fill embankment located between Fen Shui Ling and Nan Yan on the Lou Yang to Nan Yang Highway in Hunan Province, China. The embankment was constructed of the mixture of soil, detritus, scree, and disintegrated rock blocks derived from quaternary rock formation. The mixture was compacted in layers strictly following the required construction specifications. The supporting foundation was a relatively un-weathered rock formation with a gentle slope. The embankment had a height of about 8.6 m and was built in March, 2006; the section of roadway embankment under observation was approximately 2.5 km in length. For monitoring, settlement plates were embedded at stations K14+000, K14+600, K15+200, K15+800, and K16+400 during construction. The embankment settlement was monitored during March 27, 2006 through Dec. 3, 2006. The monitored settlement data at station K15+200 are tabulated in Tables 1 and 2. Table 1. Comparison of forecasted data with monitored data of roadway center settlement at station K15+200. Total time of observation/d Item Monitored settlement/mm Forecasted settlement by GM(1,1)/mm Forecasted error of GM(1,1)/% Forecasted value of optimizing GM(1,1)/mm Forecasted error of optimizing GM(1,1)/%

20

50

80

110

140

170

200

230

19.9

24.8

26.5

27.6

28.4

28.8

29.1

30.2

19.9

22.28

23.94

25.09

25.89

26.45

26.84

27.11

10.16

9.66

9.09

8.84

8.16

7.77

11.4

23.3

25.67

27.32

28.47

29.27

29.83

30.22

3.13

1.01

–0.25

–1.63

–2.51

–0.06

19.9

6.05

Table 2. Comparison of forecasted data with monitored data of roadway right shoulder settlement at station K15+200. Total time of observation/d Item Monitored settlement/mm Forecasted settlement by GM(1,1)/mm Forecasted error of/% Forecasted value of optimizing /mm Forecasted error of optimizing GM(1,1)/%

20

50

80

110

140

170

200

230

12.5

18.0

20.5

22.6

24.2

25.4

26.2

26.9

12.5

15.71

18.25

20.26

21.85

23.1

24.09

24.87

12.72

10.97

10.35

9.71

9.06

4.96

7.55

16.56

19.77

22.31

24.31

25.89

27.14

28.13

8.00

3.56

1.28

–0.45

–2.32

–3.59

–4.57

12.5

582

The embankment settlement data in Tables 1 and 2 were subjected to statistical regression analysis. The results of analysis show that the trend of settlement variation with time fits very well with the following negative exponential function: S = S0 + K1e −(T −T0 ) /K2 where S = Settlement at time T S0 = Settlement at time T0 K1, K2 = constants

Figure 1.

Settlement vs time of roadway center at station K15+200.

Figure 2.

Settlement vs time of right road shoulder at station K15+200.

583

(1)

The fitted curves and the data points are shown graphically in Figures 1 and 2. Based on the exponential relation between settlement and time, the equal time interval constitutive GM(1,1) model of grey system theory was developed below.

3

CONSTITUTIVE GM(1,1) MODEL

GM(1,1) model is the basic mathematical model of the gray system theory. It describes a new data serial established through summation, combination, and refinement of the original data serials. The new serial possesses an improved relation between the two variables, and is successively upgraded by fitting the database using the approach of differential increment as described below (Feng et al. 2004). Suppose that there are n data serials of isochronous observations: S ( 0 ) = ( s ( 0 ) (1), s ( 0 ) (2 ),…, s ( 0 ) ( n ))

(2)

0 where s ( ) ( k ) ≥ 0 , k = 1, 2,…, n

The observed data within a time period are then summed together to form the following new data serial, S (1) = ( s (1) (1), s (1) (2 ),…, s (1) ( n ))

(3)

k

1 where s ( ) ( k ) = ∑ s ( 0 ) (i ), k = 1, 2,…, n; i =1

The average values of the summed data serial within each time period form a new data serial below: Z ( 0 ) = ( z (1) (1), z (1) (2 ),…, z (1) ( n ))

(4)

1 where z (1) ( k ) = ( s (1) ( k ) + s (1) ( k − 1)), k = 2,3,…, n; 2 The preceding data serials constitute the components of the following fundamental form of GM(1,1) Model: s ( 0 ) ( k ) + az (1) ( k ) = b

(5)

where a = developing factor b = gray action factor ∧ If, parameter data serial, a = [ a, b ]T and ⎡ − z (1) (2 ) ⎢ (1) ⎢ − z (3) B=⎢ ⎢  ⎢ − z (1) ( n ) ⎣

⎡ s 0 (2) ⎤ 1⎤ ⎢ 0 ⎥ ⎥ ⎢ s (3) ⎥ 1⎥ = Y , ⎢ ⎥ ⎥ ⎥ ⎢  ⎥ ⎢ s 0 ( n)⎥ 1⎥⎦ ⎣ ⎦

Then, the serial of estimation parameters for least square of Eq. (5) should satisfy ∧

a = ( BT B )−1 BTY 584

(6)

Based on the above conditions, the white equation (or shadow equation) of GM(1,1) model is: ds ( ) 1 + as ( ) = b dt 1

(7)

Solving the time-dependent serial of Eq. (7) yields (1) b⎤ b ⎡ ∧ s (t ) = ⎢ s (1) (1) − ⎥ e − at + ; a a ⎣ ⎦ Meanwhile, the solution to the time-dependent serial of Eq. (5) is: (1) b⎤ b ∧ ⎡ s ( k + 1) = ⎢ s (1) (1) − ⎥ e − ak + ; a⎦ a ⎣

(8)

(9)

where k = 1, 2,, n Since s (1) ( k + 1) = s (1) ( k ) + s ( 0 ) ( k + 1) , the original data serial becomes ( ) ∧0

s

(1) ∧

(1) ∧

( k + 1) = s ( k + 1) − s ( k );

(10)

where k = 1, 2,, n Eq. (10) forms the basis for forecasting future performance. 4

OPTIMIZING GM(1,1) MODEL PARAMETERS

To improve the accuracy of future performance forecast using Eq. (10), the parameters of GM(1,1) model need be optimized. The optimization is performed using the least square method. In the process of optimization, parameters “a” and “b” of the above equations are determined first. Then, based on the least quadratic sum of difference between serial S(1) and serial S, parameter c of white weight function is determined. For optimization, the time-dependent white equation, Eq. (7), is integrated as follows: s (1) (t ) = c ⋅ e − at +

b a

(11)

The serial of time response of original Eq. (5) is: b ∧(1) s ( k ) = c ⋅ e − ak + ; a

k = 1, 2,…, n

(12)

Parameter c in Eq. (11) and Eq. (12) is then obtained below by using the least square method: (13) c = ( DT D )−1 DT A In which b⎤ ⎡ (1) ⎢ s (1) − a ⎥ ⎡ e −a ⎤ ⎥ ⎢ ⎢ −2 a ⎥ b ⎢ s (1) (2 ) − ⎥ ⎢e ⎥ A=⎢ a ⎥ , and D = ⎢ ⎥ ⎥ ⎢ ⎢  ⎥  ⎥ ⎢ ⎢e − na ⎥ ⎢ (1) ⎣ ⎦ b⎥ ⎢ s ( n) − ⎥ a⎦ ⎣ After the parameters of GM(1,1) model are optimized, the initial value of the original data serial can still be obtained through Eq. (10). 585

5

COMPARISON OF FORECASTED AND OBSERVED EMBANKMENT SETTLEMENT DATA

The embankment settlement data monitored from station K15+200 on the highway described earlier show that the steady state settlement did not commence until 20 days after installment of the settlement plates. At that time, the embankment center and right shoulder settled about 19.9 and 12.5 mm, respectively. The steady state settlement data monitored during the first 150 days, i.e. between 20 and 170 days after plate installment, together with a time interval of 30 days are used for analysis. According to the database, the data serials of embankment settlements at central and right shoulder of K15+200, respectively, are: S1(0) = (4.9, 1.7, 1.1, 0.6, 0.4), S2(0) = (5.5, 2.5, 2.1, 1.6, 1.2) The computed forecast data serials of GM(1,1) model for embankment center and right shoulder, respectively, are: ∧ (0)

s1 ( k + 1) = 2.38 + e −0.3617 k , ∧ (0) s 2 (k

+ 1) = 3.21 + e −0.2351k

The computed data serials of optimized parameters of GM(1,1) model for embankment center and right shoulder, respectively, are: ∧ (0)

s1 ( k + 1) = 3.40 + e −0.3617 k , ∧ (0) s 2 (k

+ 1) = 4.06 + e −0.2351k

The forecasted values of embankment settlement are compared with the monitored data in tables 1 and 2. It is seen that the forecasted data follow the monitored data fairly well. Meanwhile, the forecasted results of GM(1,1) model are not as good as that of optimized parameters GM(1,1) model. The results of optimized model are significantly better. The difference between the two results is greater at the beginning; it then decreases and later slightly increases as time goes by. The average forecast errors of GM(1,1) model are Δ1 = 9.30% and Δ2 = 9.33% for embankment center and right shoulder, respectively. For the optimized model, the average forecast errors for embankment center and right shoulder are Δ1 = 2.09% and Δ2 = 3.40%, respectively. This indicates that the optimization of GM(1,1) model parameters greatly improves the accuracy of forecasting the future performance. The results also show that the gray theory can become an effective tool for forecasting the future settlement of rock-fill embankments. It is noted that in the process of developing the roadway embankment settlement forecasting model, the monitored settlement data were subjected to regression analysis to determine the trend of variation between settlement and time. The results of regression analysis were further used to formulate the differential equation of GM(1,1) model of the gray theory. The GM model is an essential element for forecasting the future roadway performance. Thus, while the results of regression analysis can be used to predict roadway embankment settlement within a reasonable period of time, it is difficult to forecast future settlement directly using the regression analysis. It should also be noted that the developed forecasting model is project specific; namely, the model can be used to forecast only the future settlement of the investigated roadway embankment. However, the developed methodology should be applicable to other project conditions. Moreover, the developed model can be gradually improved as more field settlement data are monitored. This is an important feature of the proposed methodology. 586

6

CONCLUSIONS

1. The variation of monitored rock-fill embankment settlement with time reveals the nature of a negative exponential function S = S0 + K1e −(T −T0 ) / K2 . Such a relationship makes the gray system theory effective for forecasting the future settlement of rock-fill embankments. 2. The embankment settlement forecasted based on the optimized gray system GM(1,1) model is substantially better than the original model as would be expected. 3. To improve the accuracy of future settlement forecast, the database should be continuously updated with new data, and use the new database to improve the GM(1,1) model.

REFERENCES Cao, Xiren; Zhao, Zhenyong; Study of settlement law of high embankment filled with rocks, Highway, 2004, No. 5, pp. 27–31, (in Chinese). Feng, Zhen; Wang, Zhaoyi; Yan, Wenfa; Forecasting and its application of settlement of embankment using gray theory, Journal of Beijing Jiaotong University, 2004, No. 4, pp. 23–26, (in Chinese). Liu, Shifeng; Dang, Yaoguo and Fang, Zhigong, etc. Theory and application of gray system, Beijing, China Science Press, 2004, (in Chinese). The 2nd Highway Engineering Co. Ltd. Roadbed, Beijing, China Communication Press, 2003, pp. 377–407, (in Chinese). Wei, Yangping; Liu, Yongjiang; Forecasting method of gray system theory of settlement of high embankment, Technology of Highway and Transport, 2004. No. 4, pp. 5–7, (in Chinese).

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

FEM analysis of the bearing plate deflection tests on rubblized concrete pavement Ying Liu Anhui Transportation Infrastructure Construction Quality Control Station, Anhui, China

Y. Sheng Chang’an University, China

L. Wang Virginia Polytechnic Institute and State University, USA

ABSTRACT: Old PCC pavements are often broken and seated by the polygonal roller, and rubblized by Multiple Head Breaker (MHB) before rehabilitation. Benkelman Beam, Falling Weight Deflectometer (FWD) and Bearing Plate tests are often conducted to determine the deflection of the broken pavements for rehabilitation design. The elastic modulus of the broken pavements is then computed based on the deflections obtained in these tests. This paper presents simulation of rigid and flexible bearing plate tests with 3-D Finite Element Method (FEM) to evaluate the effects due to different sizes of broken pieces of PCC pavements. The computational method and model yield results consistent with experimental measurements. 1

INTRODUCTION

The deflection of PCC pavement is tested by bearing plate method[1] after rubblization/break and seat. The test results can be used to calculate the subgrade elastic modulus. The equations (1), (2) and (3) are based on the isotropic half-space theory. Because of the influence of broken pavements, the equations for the bearing plate deflection (W ) and elastic modulus (E0) of the broken pavements are not accurate. E01 =

Pd (1 − μ02 )π 4W01

(1)

E02 =

2 Pd (1 − μ02 ) πW02

(2)

E03 =

Pd (1 − μ02 )π W03

(3)

where E01, E02, E03 = subgrade elastic modulus based on the deflections of rigid bearing plate, flexible bearing plate (edge), flexible bearing plate (center) (MPa) respectively; W01, W02, W03 = deflection of rigid bearing plate, flexible bearing plate (edge), flexible bearing plate (center) (cm); P = pressure on the bearing plate (MPa); d = diameter of the bearing plate (cm); μ0 = Poisson’s Ratio, typical value being 0.35. 589

In this study, a 3-D overlay finite element method (FEM) is developed to analyze the influence due to broken pavements. Four conditions are considered. Condition one is that the slab is broken into 16 pieces (6 cracks). Elements’ side is 2.5 cm. Condition two is that the slab is broken into 4 pieces. Element’s side is 2.5 cm. Condition three is that the slab is broken into 4 pieces (2 cracks). Elements’ side is 5 cm. Condition four is that the slab is not broken. Elements’ side is 2.5 cm. Because of axial symmetry, only 1/4 of the slab is simulated. The bearing plate’s diameter is 30 cm, and it is 2 cm thick. The uniformly distributed load is 0.5 MPa on the plate. Actually the bearing plate of 2 cm thick deforms slightly. The pressure doesn’t match the reaction force of the subgrade distributed under a rigid bearing plate. In order to satisfy the condition of a rigid bearing plate, a 10 cm thick plate is used to increase the rigidity of the bearing plate relative to the subgrade. The bearing plate is on the center of the slabs. As local loads can make the slabs lose contacts with the subgrade, gravity of the slab also takes effect. Because the problem is nonlinear, the gravity effect must be considered. So net response due to loading = (slab’s gravity + load) response—slab’s gravity response. 2

CONDITION OF BROKEN PCC PAVEMENT

[3] 2.1 By the rubblization procedure, the size of broken slabs is typically 10∼35 cm

(1) Condition 1: the slab is broken into 4 ∗ 4 pieces (each side is 12.5 cm) with 6 cracks (Figure 1). Element’s side is 2.5 cm, E0 = 100 MPa. It is assumed that the bearing plate’s bending cannot be ignored and that the deflections of the bearing plate, slabs and subgrade are compatible in the region of the bearing plate. It loses contact between slabs and subgrade at the edges. The distribution of the reaction forces of the bearing plate and slabs takes the shape of a saddle. The deflections and reaction forces are presented in figure 2. The deflection of the left half of the bearing plate is presented in table 2. The value on the edge is 93.37 ∗ 10−3 mm. The value calculated by equation (1) is 103.37 ∗ 10−3 mm.

Table 1.

Condition

Slab size (cm)

Broken slab size (cm)

FE size (cm)

1 2 3 4

50 ∗ 50 50 ∗ 50 100 ∗ 100 50 ∗ 50

12.5 ∗ 12.5 25 ∗ 25 50 ∗ 50 ~

2.5 ∗ 2.5 2.5 ∗ 2.5 5∗5 2.5 ∗ 2.5

Condition 1 Figure 1.

(Broken) Slab and FE sizes of the four conditions.

Condition 2

The bearing plate and the condition of the broken slabs.

590

Condition 3

Table 2.

Condition 1: Deflection of left half slab (broken slab is 12.5 cm).

Loading condition

Deflection W(10–3 mm)

Slab’s gravity + load 96.05 107.29 113.06 118.84 124.61 130.39 136.16 Slab’s gravity 2.68 2.82 2.84 2.86 2.88 2.90 2.93 Load 93.37

Table 3.

Condition 2: Deflection of left half slab (broken slab is 25 cm).

Loading condition Deflection W(10–3 mm) Slab’s gravity + load 95.57 104.91 114.25 123.59 132.92 142.26 151.59 Slab’s gravity 2.71 2.79 2.87 2.95 3.03 3.11 3.19 Load 92.86

Figure 2.

Deflection and reaction forces for Condition 1.

Figure 3.

Deflection and reaction forces for Condition 2.

(2) Condition 2: the slab is broken into 2 ∗ 2 pieces (broken slab size is 25 cm in table 3, and broken slab size is 35 cm in table 4) with 2 cracks. Element’s side is 2.5 cm, E0 = 100 MPa. The deflections and reaction forces are presented in Figure 3. The deflection of the left half of the bearing plate is presented in Table 3. Compared with condition one, edge deflection is little smaller. [4] 2.2 By crack/break and seat procedure, the size of broken slabs is nearly 50 cm

(1) Condition 3: the slab is broken into 2 ∗ 2 pieces (each side is 50 cm) with 2 cracks. Element’s side is 5 cm, E0 = 100 MPa. 591

Figure 4.

Deflection and reaction forces for Condition 3.

Table 4.

Condition 2: Left half slab axial line’s deflection (broken slab is 35 cm).

Loading condition

Deflection W(10–3 mm)

Slab’s gravity + load Slab’s gravity Load

95.28 4.00 91.28

103.35 4.08

111.42 4.16

119.48 4.24

127.55 4.32

135.61 4.40

143.68 4.48

Table 5. Condition 3: Left half slab axial line’s deflection (broken slab is 30 cm). Loading condition

Deflection W(10–3 mm)

Slab’s gravity + load Slab’s gravity Load

86.69 5.90 80.79

96.55 6.06

106.42 6.22

116.28 6.38

Table 6. Condition 4: Left half slab axial line’s deflection (broken slab is 50 cm). Loading condition

Deflection W(10–3 mm)

Slab’s gravity + load 54.13 Slab’s gravity 2.20 Load 51.97

54.16 54.18 54.20 54.22 54.23 54.23 2.20 2.20 2.20 2.20 2.20 2.20 52.21

Compared to the conditions 1 and 2, the slab’s area increases significantly. The load on the bearing plate is distributed to a bigger area. The deflection decreases significantly (see Table 5 and Figure 4). (2) Condition 4: the slab is one piece (the side is 50 cm) without cracks. Elements’ side is 2.5 cm, E0 = 100 MPa. This condition is similar to that of the standard wheel load deflection tests. The slab works as the bearing plate. In this case, the bearing plate and slab will deform together. Its function is replaced by the slab (50 ∗ 50 cm). The deflection of the equivalent circular bearing plate as calculated by equation 1, is 54.98 ∗ 10–3 mm, which is 5% bigger than the center value simulated, and 5.5% bigger than the edge value simulated (see Table 6 and Figure 5). 592

Figure 5.

Deflection and reaction forces for Condition 4.

Figure 6.

Bearing plate’s edge deflection.

Figure 7.

Bearing plate deflection and slab’s size and number of elements.

3

ANALYSIS OF THE SUBGRADE DEFLECTIONS

After the subgrade deflections are calculated, their results are plotted with those of the analytical solutions in the following figures. The following conclusions may be drawn from these results. 593

1. Figure 6 illustrates that the deflection at the bearing plate’s edges decreases as sizes of the slab increase. Figure 7 illustrates that the deflection of the bearing plate on the slabs is convergent as the element size decreases. 2. In Figure 7, the deflections of the 2 cm∼10 cm thick rigid bearing plate placed on the subgrade were plotted. It can be seen that its edge deflection is not the same as predicted by equation (1). Their values have 5.5% difference in the case of 1.25 cm element size. The deflection of the 2 cm thick bearing plate is obvious. But the deflection of the 5 cm thick bearing plate is not so apparent. Center and edge deflections of the 0.2 cm thick flexible bearing plate are close to those predicted using equations (2) and (3). 3. Slabs are typically rubblized into pieces of 10∼35 cm sizes. The bearing plate is placed on the crossing of the cracks. The resilient modulus is calculated using equation (1). The result is 7.5% bigger than that with 3-D overlay FEM (1.25 cm element size). 4. When the bearing plate is placed on the center of a piece of broken slab which is big enough, the slab functions as a bearing plate. If the slab is about 50 cm, the bearing plate can be placed on the center of a piece of the broken slab. In this case, the resilient modulus calculated with equation (1) is 5.5% bigger than the result with 3-D overlay FEM (2.5 cm element size). 4

ANALYSIS OF EXPERIMENTAL DATA

The deflections of slab’s surface and subgrade’s surface were measured by the bearing plate in G-205 (Tianchang, Anhui, China) project. The resilient modulus is calculated by the analysis method through measured deflections (resolution <1 mm) with equation (1). The measured and calculated values are plotted in Figure 8. The curves are the bearing plate’s edge values

Figure 8.

Comparison between calculated and measured values.

Table 7.

The slab deflection basin (0.001 m).

Condition Before rubblization After rubblization

W1

W2

W3

W4

W5

W6

W7

W8

W9

Subbase E0 (MPa)

136

79

77

73

69

62

54

46

41

37.18

387

330

299

255

216

149

108

79

58

36.45

594

that are calculated by 3-D overlay FEM. The FEM calculation condition is that the bearing plate is placed on the subgrade, at the center of 50 cm × 50 cm slab, the center of 35 cm × 35 cm slab and the crossing of 12.5 slabs. The element size is 2.5 cm. It should be noted that the calculated values (with 3-D overlay FEM) and measured values (with 1 mm resolution) have differences for the subgrade deflections. When the calculated values were multiplied by a coefficient of 1.07, the two results, as plotted in figure 8, are consistent. The old PCC pavements in Shandong section of G205 project were rubblized. The original pavement structure is 24 cm PCC pavement plus 15 cm cement stabilized Macadam subbase and 15 cm cement stabilized sand subgrade. The resilient modulus of the subbase is almost the same, 37.18 MPa and 36.45 MPa before and after the rubblization. The deflections (Table 7) on the cracks are quite different before and after the rubblization. The slab’s rigidity is totally lost after rubblization. 5

CONCLUSIONS

1. If subgrade resilient modulus cannot be measured directly, its composite resilient modulus can be calculated through slabs’ deflection. The size of broken slabs and the location of the bearing plate must be recorded in experimentation. Instead of using equation (1), 3-D overlay FEM must be used to analyze the problem. 2. The bearing plate can be placed anywhere for back-calculating the subgrade resilient modulus with the above method. It is the worst condition when the bearing plate is placed on the crossing location of cracks. This condition yields minimal composite resilient modulus, or maximal deflection of the pavement. Results from this condition can be used in pavement design. REFERENCES Field Test Methods of Subgrade and Pavement for Highway Engineering, JTG E60-2008, Ministry of Communication of the People’s Republic of China, 2008. Liu, Ying & Liu, X.Y. 2004. 3-D FEM Calculate Model of HMA Overlay on PCC Pavement with Break and Seat Procedure, Communication and Computer Journal, Vol. 22, No. 1. Huang, Y.H. 1993. Pavement Analysis and Design, Prentice-Hall. Liu, Ying, Liu, X.Y., Sun, J. & Huang, X.M. 2004. Broken Size of Crack and Seat PCC Pavement, Journal of Highway and Transportation, Vol. 21, No. 4. Liu, Ying, Sun, J., Huang, X.M. & Liu, X.Y. 2003. Deflection and Resilience Module of Old PCC Pavement after Break and Seat Procedure, East China Highway Journal, No. 6.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Data mining applied to compaction of geomaterials R. Marques & A. Gomes Correia Department of Civil Engineering, University of Minho, Guimarães, Portugal

P. Cortez Department of Information Systems, University of Minho, Guimarães, Portugal

ABSTRACT: This study applied a data mining process to the French Guide for Road Earthworks (GTR), aiming to predict the capacity of compaction and the compaction condition parameters. The database is comprised mainly by the data available in the “Compaction Tables”, part of GTR. The data includes qualitative variables (material, compactor type and energy level) and quantitative variables (Q/S parameter, layer thickness and velocity, number of load applications and theoretical compaction capacity of the compactor). Computations were carried out using the R tool and RMiner library. The best models obtained, based on neural networks and support vector machines, allowed the finding of qualitative and quantitative relationships between variables involved in compaction. Furthermore, a prototype was developed that allows an automatization of the information of the compaction conditions. 1

INTRODUCTION

The compaction task has a crucial role on the response of the structure-foundation system of constructions, particularly roads, railways and airfields, and consequently on their bearing capacity. The guarantee of an adequate compaction can be achieved by two different philosophies, namely through the “control by finished product” and the “control by procedure” (Escario Ubarri et al. 1989). In Portugal, the quality control of earthworks is traditionally made by the specification of properties for the compacted material, such as the compaction degree and the water content. This is a control by finished product. For the opposite, the control by procedure consists of establishing the methodology according to which the compaction must be carried out, where the layer thickness and the number of passes are fixed according to the material properties and the compactor type. The recommendations of the French Guide for Road Earthworks (Guide Terrassements Routiers), GTR (SETRA & LCPC 1992), are example of this control philosophy. Certain inconveniences identified for the procedures of control by finished product, such as the test unreliability, the need to execute the tests only when finished the work, the delay of these, their high costs, and mainly the difficulty of correction a posteriori of parts of the work with deficient quality, had made to tumble the balance in favor of the control by procedure. On the other hand, there are some studies in the past on the area of compaction using Artificial Intelligence techniques (Kotdawala & Hossain 1994, Basheer & Najjar 1995, Najjar et al. 1996, Basheer 2001), which essentially were used to determine prediction models for parameters considered by the finished product control. Therefore, in this work a Data Mining process is applied on the GTR database (see Section 2.1) to obtain useful knowledge, particularly models involving the parameters covered by the control by procedure. In addition, a sensitivity analysis is made to clarify the significance and the relationship of certain physical variables involved in the compaction control according the GTR methodology.

597

2

DATA MINING

2.1 GTR database Data Mining (DM) is a process to extract high-level knowledge from raw data (Witten & Frank 2005). In this study, the database submitted to this process is comprised mainly by the “Compaction Tables” of the Guide Terrassements Routiers (GTR) (SETRA & LCPC 1992), which are the result of the French experience in the compaction task, from various specialists on a representative number of works. This experience was passed to the format of these tables to, based on the identification of the material-compactor duo and the quality required for compaction, determine the compaction conditions: the layer thickness (e) and the velocity (V), the number of load applications (N) and the respective theoretical compaction capacity (Q/L) of the compactor. The “Compaction Tables” include also the Q/S parameter, that is a measure of the ratio between the volume of compacted material Q during a given time, and the area S covered by the compactor in the same time. This Q/S ratio represents an elementary thickness, considered as a reference parameter in the compaction control. Figure 1 shows a graphic matrix that represents, through points, associations of values for the quartet of variables materialcompactor-energy-Q/S, in accordance with the modalities contained in the “Compaction Tables” for embankments. This figure suggests the non-linearity of the problem. 2.2 Data mining techniques In this study were tested different DM techniques, from the traditional technique of multiple regression and the non-parametric methods of decision trees and k-nearest neighbors to the nonlinear techniques based on neural networks and support vector machines. The statistical technique of Multiple Regression (MR) appears in DM studies primarily as a baseline of comparison for nonlinear techniques. This technique represents a generalization of the linear regression for a model with various independent variables (called inputs). The decision trees technique (Quinlan 1986) functions through the creation and training of subsets of information for which is inferred one or more rules. According to a tree structure,

Figure 1.

Relationship matrix between several GTR database variables.

598

Figure 2.

A multilayer perceptron (left) and an example of a SVM transformation (right).

each node of the tree establishes a test based on attributes, and each descending branch of this node is one of the possible values for that attribute. These trees are called of Regression Trees (RTs) when they perform the prediction for a continuous variable. The k-Nearest Neighbors (k-NN) method bases its predictions on the location of the k observations that are closest to the item being predicted. The determination of this similarity is based on distance measures (Hechenbichler & Schliep 2004). The Artificial Neural Networks (ANNs) are inspired in the functioning mode of the human brain. These networks consist of processing units (nodes) interconnected according a given configuration, where the Multilayer Perceptron (left of Fig. 2) is the most popular type (Haykin 1999). The nodes are constituted by: a set of connections (wij), each labeled by a weight, which has an excitatory effect for positive values and inhibitory for negative ones; an integrator (g), which reduces the n entry arguments (stimulus) to a single value; and by a activation function (f ) that can condition the output signal by introducing a component of non-linearity in the computational process. In this study, the weights of the network are initially generated randomly in the range [−0.7, +0.7] and the activation function used is the logistic (1/(1 + exp(−x))). Then, the training algorithm is applied by adjusting successively the weights until the error slope approaches zero or until a maximum of epochs. The prediction model for a neural network is given by the following expression (Hastie et al. 2001): (1) where wi,j denotes the weight of the connection from the neuron j to the unit i, o is the output unit, f is the activation function, and I is the number of input neurons. Support Vector Machines (SVMs) (Cortes & Vapnik 1995) are learning systems that use a space of hypothesis of linear functions in a wide space of features, which are trained with an optimization algorithm that implements a statistical trend of learning (Bautista-Thompson et al. 2004). The basic idea is transform the input x ∈ℜI into a high m-dimensional feature space by using a nonlinear mapping. Then, the SVM finds the best linear separating hyperplane, related to a set of support vector points, in the feature space (right of Fig. 2). The transformation depends on the kernel function (k(x, y) = ∑øi(x) øi(y)) adopted. In this work, the popular gaussian kernel was used, which presents less hyperparameters and numerical difficulties than other kernels as the polynomial or sigmoid (Chang et al. 2003, Cortez 2008): k(x, y) = exp(−γ || x−y ||2), γ > 0

(2)

2.3 Data mining process The DM process was carried out in the environment of the statistical tool R (R Development Core Team 2008). The RMiner library created by Cortez (2008) was used, which contains a 599

coherent set of functions that facilitates the application of different DM techniques, using packages available in the R program. After several experiments testing potential relations between variables, the best models obtained in the Data Mining process, which are valid for the case of embankment layers, were: Q/S ∼ Material + Compactor + Energy level

(3)

e*V ∼ Material + Compactor + Energy level + Q/S

(4)

and

0.35

ANN SVM

0.25 0.20 0.15

Predicted Q/S values

80 60 40

0.05

20

tolerance

RT

0.30

k-NN MR

0.10

100

where the Q/S parameter and the thickness by velocity product e*V (i.e. the dependent variables) come in function (∼) of the independent variables (i.e. the right side of the formulas). The various DM techniques were compared with respect to the predictive capacity according the models (3) and (4), through distinct measures of performance. In this work, the evaluation scheme is based on 20 executions (runs) of a 10-fold cross-validation (Efron & Tibshirani 1993). The overall performance is given by the average of the error metrics and their confidence interval under a t-student test with a 95% confidence level.

0

0.00

Multiple Regression (MR)

0.00

0.02

0.04

0.06

0.08

0.10

0.00

absolute error

0.05

0.10

0.20

0.25

0.30

0.35

(b)

0.05

0.30 0.25 0.20 0.15 0.10 0.05

0.10

0.15

0.20

0.25

Predicted Q/S values

0.30

0.35

0.35

(a)

Predicted Q/S values

0.15

Q/S values (GTR)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

Support Vector Machine (SVM)

0.00

0.00

Artificial Neural Network (ANN) 0.35

0.00

Q/S values (GTR)

0.05

0.10

0.15

(c) Figure 3.

0.20

0.25

0.30

0.35

Q/S values (GTR)

(d)

Graphic comparison of performance between different DM techniques to adjust model (3):

(a) REC curves; (b–d) Predicted Q/S values versus real Q/S values (GTR). 600

60 20

1

40

tolerance

k-NN

3

RT

2

Predicted e*V values

4

100 80

SVM ANN MR

0

0

Multiple Regression (MR) 0.0

0.2

0.4

0.6

0

1

absolute error

(a)

3

4

3 2 1

2

3

Predicted e*V values

4

4

(b)

1

Predicted e*V values

2

e*V values (GTR)

0 0

1

2

3

0

4

e*V values (GTR)

1

2

3

4

e*V values (GTR)

(c) Figure 4.

Support Vector Machine (SVM)

0

Artificial Neural Network (ANN)

(d)

Graphic comparison of performance between different DM techniques to adjust model (4):

(a) REC curves; (b-d) Predicted e*V values versus real e*V values (GTR).

The first measure of performance is based on the concept of the REC curve, Regression Error Characteristic (Bi & Bennett 2003), which is the cartesian representation of the error tolerance (horizontal axis) in terms of absolute deviation versus the percentage of points predicted within that tolerance (vertical axis). The ideal regressor should present a REC area of 1. The comparison of the REC curves in Figure 3a allows concluding, clearly, that the technique based on neural networks (ANN) presents the best performance in the prediction of the Q/S parameter, followed by the technique based on support vector machines (SVM). In the adjustment of the e*V product, the REC curves (Fig. 4a) show an approximate performance for the SVM and ANN techniques, apparently in this order. To better evaluate the performance of the different DM techniques, scatter plots of the values predicted by the models versus the values presented in the GTR guide are also shown. For the Q/S parameter, these graphs (Figs. 3b–d) show that the ANN technique presents the smaller scatter, showing the SVM technique also a low scatter. In the case of the e*V product, the graphs in Figures 4b–d show that the SVM technique presents this time the lowest scatter. For each technique, the following metrics were computed to assess their performances: Mean Absolute Deviation (MAD); Relative Absolute Error (RAE); Root Mean Squared (RMSE); Relative Root Mean Squared (RRMSE); Pearson correlation coefficient (COR); 601

and processing time required in the evaluation of each technique (Time). The metrics based on the error are calculated according to the following expressions (Cortez 2008):

(5)

where N denotes the number of examples, yi the _ desired value, ŷi the value predicted by the model, y– i the average of the desired values and ŷi the average of the predicted values. Table 1 shows that the ANN technique presents the lowest values for any of the error metrics in the prediction of the Q/S parameter, however requiring greater computational time in the evaluation stage. In the adjustment of the e*V product, the values in Table 2 denote approximate performances for the ANN and SVM techniques, but the SVM technique is less penalized with the square of the errors and presents a higher correlation coefficient. In short, while the regression for Q/S should be modeled by a neural network, for the e*V regression the support vector machine is the most accurate model. This shows the nonlinear dependence of these variables, which can be modeled by techniques capable of representing non-linearity and complexity from their model configuration, even if no a priori function form is known to the relation. 2.4 Sensitivity analysis The Sensitivity Analysis is made measuring the variance (Va) produced in the output (ŷ) when the input attribute (a) is moved through its full range (Kewley et al. 2000):

Table 1.

MAD RAE RMSE RRMSE COR Time

Table 2.

MAD RAE RMSE RRMSE COR Time

Performance measures of different DM techniques in the adjustment of model (3). MR

RT

k-NN

ANN

SVM

0.0155 ± 0.0001 39.13 ± 0.13% 0.0211 ± 0.0001 39.99 ± 0.11% 0.9167 ± 0.0005 26.97 s

0.0208 ± 0.0003 52.73 ± 0.82% 0.0280 ± 0.0005 52.99 ± 0.87% 0.8481 ± 0.0054 6.16 s

0.0159 ± 0.0007 40.22 ± 1.75% 0.0264 ± 0.0009 49.97 ± 1.73% 0.8676 ± 0.0095 293.79 s

0.0037 ± 0.0002 9.44 ± 0.43% 0.0065 ± 0.0005 12.38 ± 0.86% 0.9923 ± 0.0011 10853.36 s

0.0090 ± 0.0001 22.85 ± 0.38% 0.0137 ± 0.0004 26.02 ± 0.69% 0.9682 ± 0.0016 7249.79 s

Performance measures of different DM techniques in the adjustment of model (4). MR

RT

k-NN

ANN

SVM

0.0977 ± 0.0004 18.46 ± 0.08% 0.1418 ± 0.0007 21.37 ± 0.10% 0.9769 ± 0.0002 25.06 s

0.2275 ± 0.0029 42.99 ± 0.56% 0.3033 ± 0.0036 45.69 ± 0.55% 0.8901 ± 0.0027 6.69 s

0.2378 ± 0.0062 44.93 ± 1.18% 0.3627 ± 0.0062 54.64 ± 0.93% 0.8645 ± 0.0065 333.02 s

0.0714 ± 0.0023 13.50 ± 0.43% 0.1180 ± 0.0042 17.77 ± 0.63% 0.9844 ± 0.0011 11419.06 s

0.0739 ± 0.0006 13.96 ± 0.12% 0.1132 ± 0.0015 17.05 ± 0.22% 0.9865 ± 0.0003 7347.02 s

602

Table 3. Importance of variables in the Q/S prediction with different DM techniques. Variable importance

MR RT k-NN ANN SVM

Material

Compactor

Energy level

22.89% 6.98% 28.51% 27.39% 26.65%

33.80% 6.30% 8.92% 11.37% 11.67%

43.31% 86.72% 62.58% 61.23% 61.67%

Table 4. Importance of variables in the e * V prediction with different DM techniques. Variable importance

MR RT k-NN ANN SVM

Material

Compactor

Energy level

Q/S parameter

2.98% 10.92% 14.25% 2.37% 4.93%

30.07% 46.53% 9.51% 30.30% 38.43%

0.12% 28.67% 76.25% 0.20% 0.22%

66.83% 13.88% 0.00% 67.13% 56.43%

(6)

where I denotes the number of input attributes and Ra the relative importance of the a attribute. The output ŷi is obtained by holding all input variables at their average values. The exception is xa, which varies through its entire range with L levels. In this work, L was set at 6 for the continuous inputs. For the Q/S prediction according model (3), Table 3 shows that for any of the DM techniques the energy level has, as expected, a predominant importance on the value of this parameter. In fact, compaction practice shows that for materials compacted on the dry side of optimum water content, the lower the Q/S value, the greater the compaction energy achieved. Furthermore, the Q/S parameter and the compactor type have, by this order, a preponderant weight in the prediction of the e*V product according model (4) with the MR, ANN and SVM techniques, that are the most accurate in the e*V prediction (Table 4). 2.5 Automatization of the compaction conditions Artificial Intelligence allowed the development of intelligent systems that use a given knowledge representation to solve problems usually addressed by human experts. In this context, in this work a prototype was developed that extracts automatically the information of the compaction conditions. Based on the knowledge of the variables upstream, particularly the material, the compactor type, and also the energy level in the case of embankments, the DM models are used to reproduce the compaction conditions (Fig. 5). In a first instance the Q/S value is predicted through the model (3) of neural network and after the e*V product is predicted through the model (4) of support vector machine. For each material-compactor pair a recommended 603

Known variables Material Compactor Energy level

Moisture state Meteorology Solution Other factors

Q/S ~

Data V, velocity

e, thickness

Mining

e*V ~

e

V

N

Q/L

Compaction conditions

Figure 5.

Flowchart for setting the compaction conditions.

velocity and/or thickness is associated, or these can be defined by the user within controlled limits, and then the variable eventually at fault (e or V ) is derived from the e*V value. After knowing the values of the Q/S, e and V variables, the other compaction conditions can be determined by the known relations of the GTR methodology. The developed prototype is an alternative to the “GTR Compaction Tables”, which can be used to predict the compaction condition parameters and the capacity of compactors, in phase of work planning and construction. 3

CONCLUSIONS

The main objective of this study was the application of Data Mining techniques on the “Compaction Tables” of the GTR guide, aiming at the discovery of relations between the variables considered there. These relations were represented in the form of predictive models and high predictive accuracies were achieved. Moreover, a sensitivity analysis was applied to these models, which allowed measuring the impact of each independent (input) variable. The most significant relationships obtained in the Data Mining process, which are valid for the case of embankment layers, are expressed as models to predict the Q/S parameter in function of the material, compactor type and energy level attributes, and to predict the e*V product in function of the material, compactor type, energy level and Q/S variables. The computational experiments conducted in this work revealed the neural networks (for Q/S parameter) and support vector machines (for e*V product) as the best predictive models, outperforming the multiple regression, regression tree and k-nearest neighbor methods. The sensitivity analysis applied to the Q/S model showed greater dependence of Q/S from the energy level variable, revealing the material and compactor type attributes smaller importance. On the other hand, the sensitivity analysis on the e*V model showed a strong relation of the e*V product with the Q/S parameter, and a low importance of the material and energy level variables. The importance of the energy level is implicit in the Q/S value. It should be also mentioned that the high performance achieved with the techniques based on neural networks and support vector machines demonstrates the nonlinear characteristics of this domain. In effect, the models obtained with these techniques show a high predictive potential, and in particular enable a faithful reproduction of the data contained 604

in the “Compaction Tables”, i.e. an automatization of the information of the compaction conditions, which is useful to compaction planning and management. ACKNOWLEDGEMENTS This study was supported by “Fundação para a Ciência e a Tecnologia” in Portugal, under the Project POCI/ECM/61114/2004 “Interaction soil-railway track for high speed trains”. REFERENCES Basheer, I.A. & Najjar, Y.M. 1995. A neural-network for soil compaction. In G.N. Pande & S. Pietruszczak (eds.), Proc. 5th Int. Symp. Numerical Models in Geomechanics, Davos, 435–440. Rotterdam: Balkema. Basheer, I.A. 2001. Empirical modelling of the compaction curve of cohesive soils. Can. Geotech. J./Rev. can. geotech. 38(1): 29–45. Bautista-Thompson, E., Guzmán-Ramírez, E. & Figueroa-Nazuno, J. 2004. Predicción de Múltiples Puntos de Series de Tiempo Utilizando Support Vector Machines. Computación y Sistemas 7(3): 148–155. México: Centro de Investigación en Computación—Instituto Politécnico Nacional (in Spanish). Bi, J. & Bennett, K. 2003. Regression Error Characteristic curves. In Proc. 20th Int. Conf. on Machine Learning (ICML), Washington DC. Chang, C. Hsu, C. & Lin, C. 2003. A Practical Guide to Support Vector Classification. Department of Computational Science and Information Engineering, National Taiwan University. Cortes, C. & Vapnik, V. 1995. Support Vector Networks. Machine Learning 20(3): 273–297. Boston: Kluwer Academic Publishers. Cortez, P. 2008. RMiner: Data Mining with Neural Networks and Support Vector Machines using R. In Introduction to Advanced Scientific Softwares and Toolboxes. International Association for Engineering, in press. Efron, B. & Tibshirani, R. 1993. An Introduction to the Bootstrap. New York: Chapman & Hall. Escario Ubarri, V., Hinojosa Cabrera, J.A. & Rocci Boccaleri, S. 1989. Terraplenes y pedraplenes. Madrid: Ministerio de Obras Públicas y Urbanismo, Centro de Publicaciones (in Spanish). Hastie, T., Tibshirani, R. & Friedman, J. 2001. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer-Verlag. Haykin, S. 1999. Neural Networks—A Compreensive Foundation. New Jersey: Prentice-Hall. Hechenbichler, K. & Schliep, K. 2004. Weighted k-Nearest-Neighbor Techniques and Ordinal Classification. Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich. Kewley, R., Embrechts, M. & Breneman, C. 2000. Data strip mining for the virtual design of pharmaceuticals with neural networks. IEEE Transactions on Neural Networks 11(3): 668–679. Kotdawala, S.J. & Hossain, M. 1994. Knowledge and Data-Driven Expert-System for Soil Compaction. In H.J. Siriwardane & M.M. Zaman (eds.), Proc. 8th Int. Conf. Computer Methods and Advances in Geomechanics, Morgantown, Vol. 1: 465–470. Rotterdam: Balkema. Najjar, Y.M., Basheer, I.A. & Naouss, W.A. 1996. On the identification of compaction characteristics by neuronets. Computers and Geotechnics 18(3): 167–187. Quinlan, J. 1986. Induction of Decision Trees. Machine Learning 1: 81–106. R Development Core Team 2008. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL: http://www.R-project.org. SETRA & LCPC 1992. Guide technique Réalisation des remblais et des couches de forme. France (in French). Witten, I.H. & Frank, E. 2005. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. San Francisco: Morgan Kaufmann.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Finite element analyses of pavement materials at or near failure: A constant bulk modulus approach C. Gonzalez & S. Jersey US Army Engineer Research and Development Center, Vicksburg, Mississippi, USA

ABSTRACT: Military engineers are required to implement design methodologies capable of predicting pavement response data; however, they must develop the response data with a minimal amount of input. Input may be limited due to logistical constraints in the field. Researchers at the U.S. Army Engineer Research and Development Center (ERDC) have developed a simplified modeling approach, which is being implemented into design criteria. This approach provides response data that is capable of matching responses in the field. This paper summarizes the technical approach, including validation of this procedure using simulations of both laboratory tests performed on pavement materials and tests performed in the field on full-scale airfield pavements. Prediction of pavement responses using this method provided a reasonable match to stresses observed under field loading. Based on the results of this study, this approach will be used to develop updated military pavement design criteria. 1

INTRODUCTION

The design and evaluation of military airfield pavement structures present pavement engineers with special challenges. Often, available soils and pavement strength data is limited and additional data may be very difficult to obtain. While the pavement community has moved towards implementation of rigorous analytical procedures capable of more accurately representing in situ stress states, the military engineer continues to be controlled by the limitations associated with collecting appropriate data. Hence, advanced mechanistic analytical procedures must be tied back to the quality of information that can be reasonably provided by a soldier in the field. For this reason, recent studies at the U.S. Army Engineer Research and Development Center (ERDC) have focused on developing simplified modeling approaches, which may provide reasonable answers with limited data, in particular, simplified finite element procedures that could provide better predictions than those provided by the current layered elastic standard. There are many ways to analyze pavement structures using the finite element method. The more rigorous case is the three-dimensional, dynamic, non-linear finite element analysis. In this particular case, the true shape and the effects of the moving tire could be modeled more realistically. However, the computer requirements of such an analysis, the complications associated with setting up three-dimensional meshes and multiple, moving loads, and the reduction, analysis and interpretation of computed data make this approach sometimes impractical for routine pavement design. In most cases, reasonable answers can be obtained by analyzing a single tire. For this case, a rather simple, non-linear, axi-symmetric finite element analysis of a static wheel load yields reasonable answers to the problem. It should be noted that the use of static analyses to evaluate the effects of a moving single-wheel load over a pavement structure will indicate a relative trend in terms pavement response. When trying to relate a computed response parameter to the pavement performance (in terms of passes to failure) by means of static analyses, the response parameter should be taken as an index which must be used in a transfer function based on the actual performance obtained from full-scale traffic experiments. However, a number of good correlations have been developed and reasonable predictions of performance have been achieved in the past using these relationships. 607

Although many researchers have successfully used finite element methods to model pavement structures, the issue of handling failure as the material begins to shear is critical. This paper presents a technique that has been implemented by the ERDC into an axisymmetric finite element program to handle the behavior of the pavement materials as they approach failure. Historically, a minimum modulus of elasticity has been assigned to the materials as they approach shear failure. However, the approach proposed herein assumes that the bulk modulus of the material remains constant throughout an element’s stress history. It compensates by recomposing or adjusting the Poisson’s ratio, essentially forcing the element to fail in shear and preventing it from collapsing. Basic laboratory data for subgrade, subbase and base course materials was obtained to establish fundamental material properties. These properties were then incorporated into a hyperbolic soil model to make predictions of the laboratory triaxial tests and field CBR tests, and predictions of actual aircraft loads on a full-scale experimental pavement sections constructed at ERDC. Results from these analyses showed great potential for future implementations in more mechanistic-empirical analyses and design/evaluation procedures. 2

NON-LINEAR HYPERBOLIC SOIL MODEL

The non-linear model selected for this study was the hyperbolic soil model (Kulhawy and Chang, 1969). In this model, the non-linear shape of the stress-strain curves was represented by a hyperbola of the form (σ 1 − σ 3 ) =

εa (a + b ⋅ ε a )

(1)

where (σ 1 − σ 3 ) is the principal stress difference, ε a is the axial strain, and a and b are parameters whose values are determined experimentally. Figure 1 shows a graphical representation of this model. From Figure 1(a) it can be seen that these parameters are the reciprocals of the initial slope (initial tangent modulus) and the asymptote to the stress-strain curve. To determine the parameters a and b, Equation 1 is transformed into the linear form, as described by Equation 2.

εa = a + b ⋅εa (σ 1 − σ 3 )

(2)

By performing compressive triaxial tests the parameters a and b can be determined from the intercept (initial tangent modulus) and slope of the line (ultimate stress difference) as shown in Figure 1(b), respectively. The value of the asymptotic stress difference (σ 1 − σ 3 ) ult , is always larger than the compressive strength of the soil at failure, (σ 1 − σ 3 )f . This relationship is called the “failure ratio” as is expressed as Rf =

(σ 1 − σ 3 ) f

(3)

(σ 1 − σ 3 )ult

Failure ratios, which are a measure of how nearly the shape of the stress-strain curve can be approximated by a hyperbola, have been found to range from 0.5 to 1.0 for a variety of soils. The variation of the initial tangent modulus with confining pressure can be represented by the equation ⎛σ ⎞ Ei = K ⋅ pa ⋅ ⎜ 3 ⎟ ⎝ pa ⎠

n

(4)

where Ei is the initial tangent modulus, σ 3 is the minor principal stress, pa the atmospheric pressure, K is a modulus number, and n an exponent determining the rate of variation of 608

(a)

(b) Figure 1.

Non-linear hyperbolic soil model, (a) basic form, (b) transformed form.

Ei with σ 3. In non-linear finite element analysis it is necessary to know the value of the tangent modulus at various points on the stress-strain curve since incremental stress analysis is required to obtained reliable results. Equation 3 and 4 are combined with the MohrCoulomb failure criteria to obtain the equation. 2

⎛ σ3 ⎞ ⎡ R f ⋅ (1 − sinφ ) ⋅ (σ 1 − σ 3 ) ⎤ Ei = ⎢1 − ⎥ ⋅ K ⋅ pa ⎜ ⎟ ⎝ pa ⎠ ⎣ 2 ⋅ c ⋅ cos φ + 2 ⋅ σ 3 ⋅ sinφ ⎦

n

(5)

Equation 5 was employed to determine the value of the tangent modulus at any point in the stress-strain curve and consequently represent the non-linearity of the materials. A more detailed explanation of the hyperbolic model can be found in Kulhawy, et al. (1969). Because this is an incremental elastic constitutive model, initial values of Poisson’s ratio are assumed and then recomputed based on the state of stress at a particular point. In doing so, it was 609

assumed that there was no volumetric change during loading (indicated by a constant bulk modulus). For saturated fat clays and well compacted granular materials this assumption is reasonable. The initial constant bulk modulus, B is computed by the formula B=

Ei 3(1 − 2ν i )

(6)

where Ei is the initial modulus of elasticity and vi is the initial Poisson’s ratio. During loading, as the material moves up the strain-strain curve (Figure 2) the instantaneous Poisson’s ratio is then recomputed from the equation 1⎛ E ⎞ v = ⎜1 − t ⎟ 2 ⎝ 3B ⎠

(7)

This modeling process in essence prevents the finite elements representing the soil or gravel from collapsing when the modulus of elasticity decreases to small values and forces the materials to “fail” in shear. This fact is illustrated by Figure 3. As the modulus of elasticity

Figure 2.

Change in instantaneous modulus along the stress-strain curve. EFFECT OF ASSUMING CONSTANT BULK MODULUS 5000

0.6

4000 3500

0.4

3000 0.3

2500 2000

0.2

1500

Shear Modulus, psi

Poisson’s Ratio

4500

Poisson’s Ratio

0.5

1000

0.1

500

Shear Modulus 0.0 10

100

1000

10000

0 100000

Modulus of Elasticity, psi

Figure 3. Relationship between modulus of elasticity, Poisson’s ratio and shear modulus for constant bulk modulus (1 psi = 6.89 kPa).

610

is decreased the Poisson’s ratio approaches 0.5, which makes the material incompressible and the shear modulus decrease. This essentially puts the material into shear failure instead of allowing the material to collapse. In summary, five parameters: K, n, c, φ and Rf , are used in conjunction with Equation 5 and are implemented in an axi-symmetric finite element computer program to model non-linear pavement materials. 3

LABORATORY TESTING

To establish the five parameters (K, n, c, φ and Rf) required to model the non-linear behavior of pavement structures tested, a set of laboratory triaxial tests were conducted at the ERDC. These triaxial tests were conducted at a constant strain rate of 1% per minute and at three confining pressures (σ3 = 35, 103, and 207 kPa or 5, 15 and 30 psi). Three materials representing the subgrade, subbase course and base course were tested at approximately the same moisture and density conditions encountered during the construction of full-scale test sections being constructed at ERDC. The subgrade was composed of a locally available high-plasticity clay (CH) known as the Vicksburg Buckshot clay. Subgrade conditions on these test sections were tested at three strengths, California Bearing Ratios (CBRs) of 3, 10, and 15. These strengths correspond to moisture contents of 34%, 30%, and 27%, respectively. The angle of internal friction was determined to be equal to zero (φ = 0). Results from triaxial tests are shown in Figure 4 expressed in their corresponding linear hyperbolic transformation. The laboratory data for the subgrade (CH) material showed an excellent correlation and fitted very well the hyperbolic soil model from strain values of 0.5% up to 3%. These strain values are believed to cover most application of pavement loaded with aircraft tires. The granular subbase course was composed of 67% crushed gravel and 33% limestone fines by weight. This blend resulted in a gradation with an angle of internal friction (φ) of 48 degrees and cohesion of 55 kPa (8 psi). Moisture content for the subbase material ranged from 3% to 4% while the dry density was approximately 861 kPa (125 psi). The results of the hyperbolic fit

Figure 4. Hyperbolic linear transformation of subgrade clay material (CH-Vicksburg Buckshot Clay) (1 psi = 6.89 kPa).

611

are shown in Figure 5 and, as was the case for the subgrade, they show an excellent fit in the range of 0.5% to 3% strain. The results from the triaxial tests were also used to establish the correlation between the initial modulus and the confining pressure, as illustrated in Figure 6. Similarly, the properties of the crushed limestone base are shown in Figures 7 and 8. The angle of internal friction for the base course was found to be 50 degrees and its cohesion was 48 kPa (7 psi) and its dry density was approximately 916 kPa (133 psi). The crushed limestone showed good correlation between 1% and 3% strain, but it departed from the linear hyperbolic soil transformation at strains in excess of 3% strain. However, most strains encountered in the field still fall in this range and therefore the hyperbolic fit was considered adequate for our simplified finite element modeling.

Figure 5.

Hyperbolic linear transformation of crushed gravel subbase (1 psi = 6.89 kPa). SUBBASE MATERIAL 33% LIMESTONE FINES + 67% CRUSHED GRAVEL (CRYSTAL SPRINGS GRAVEL) 100000 y = 3315.0217×0.5820 R = 0.5238

INITIAL MODULUS, Ei/PATM, PSI

2

10000

1000

K = 3315 n = 0.582 PATM = 1.0 PSI 100 1

10

100

CONFINING PRESSURE, S3/PATM, PSI

Figure 6. Initial modulus of elasticity versus confining pressure relationship for crushed gravel subbase (1 psi = 6.89 kPa).

612

4

SIMULATION OF LABORATORY TESTS

The first step to validate the assumption of the constant bulk modulus was to use the laboratory data collected for the subgrade, subbase, and base materials and simulate the actual triaxial tests. Comparison between predicted and measured stress-strain curves will indicate how well the simulation tracks the actual tests. This provides an initial measure of the reasonableness of these assumptions. An axisymmetric finite element code implementing the hyperbolic soil model along with the constant bulk modulus assumption was written at ERDC.

Hyperbolic linear transformation of crushed limestone base (1 psi = 6.89 kPa).

Figure 7.

INITIAL MODULUS FIT FOTR CRUSHED LIMESTONE BASE ANGLE OF INTERNAL FRICTION = 50 DEGREES COHESION = 7 psi

INITIAL MODULUS, psi

1000000

K = 11458 n = 0.5574

y = 11457.6335 × 0.5574 R2 = 0.6304

100000

10000

1000 1

10

100

CONFINING PRESSURE, psi

Figure 8. Initial modulus of elasticity versus confining pressure relationship for crushed limestone (1 psi = 6.89 kPa).

613

Figure 9. Simulation unconfined compressive tests of clayed subgrade (CH-Vicksburg Buckshot clay) (1 psi = 6.89 kPa).

Figure 9 compares a simulation of an unconfined compression test performed on a CBR = 10 CH clay. The simulated curve, depicted by the dotted curve, shows a good fit relative to the laboratory data, as indicated by the Rf = 0.90 hyperbolic parameter. Figure 10 shows simulations performed on the subbase (crushed gravel) material at confining pressures of 35, 103, and 207 kPa (5, 15 and 30 psi). Two simulations were performed at each confining pressure, one assuming a rough interface (rigid loading plate) between the top loading plate and the sample, and the second assuming a smooth interface (flexible loading plate). As Figure 10 indicates, the simulated stress-strain curves generally bound the actual laboratory data, but the simulations with a smooth interface are closer to the measured data. In order to more precisely model this situation, the finite element code used for this study would have to be modified to include interface elements and assign an appropriate friction value between the loading plate and the sample. However, it is still believed that the results provide a reasonable representation of the non-linear behavior of the subbase material. Similar results were obtained from simulations performed on the crushed limestone base. These simulation results showed that the hyperbolic model and the assumption of a constant bulk modulus predicted reasonable well the non-linear behavior of the pavement materials tested. 5

SIMULATION OF FIELD TESTS

Based on the laboratory test simulations, the next logical step was to extend the application of the calibrated hyperbolic soil model to the modeling of field CBR tests. This step included simulations of the surface field CBR tests for a pavement structure that corresponded to recent full-scale experimental test sections constructed at the ERDC. Simulations were performed at the top of the subgrade, subbase, and base layers, corresponding to locations of field CBR tests during construction. Figure 11 shows modeling results for three field CBR tests conducted on top of a CH subgrade. Two cohesion values were used for the simulations based on laboratory results from field studies. These results show excellent agreement between the field results and the simulated load deformation curves. As a comparison, the linear elastic case is also shown. Figure 12 shows the simulated surface deflection profile of 614

Q-TEST RESULTS FOR SUBBASE MATERIAL 33% LIMESTONE FINES + 67% CRUSHED GRAVEL ANGLE OF INTERNAL FRICTION = 48 DEGREES COHESION = 8 psi 260 240

ROUGH END

220

S3 = 30

DEVIATOR STRESS, psi

200

SMOOTH END

180 ROUGH END

160 140

S3 = 15 psi

SMOOTH END

120 100

ROUGH END

80

S3 = 5 psi SMOOTH END

60 40 20 0 0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

VERTICAL STRAIN, IN/IN

Figure 10.

Simulation of field CBR test conducted on surface of clay subgrade (1 psi = 6.89 kPa).

FIELD CBR TEST RESULTS CBR = 10, Water Content = 30% USAF Rapid Parking Ramp Expansion Program 2007 AM2 Mat Test Section 500 450

NON-LINEAR FEM LINEAR

c = 15.8 psi, phi = 6.5

400

LOAD, LB

350

c =18.7 psi, phi = 0 c = 16.8 psi, phi = 0

300 250 200 150

TEST #1 TEST #2 TEST #3

100 50 0 0.00

Figure 11.

0.05

0.10 0.15 0.20 MAXIMUM SURFACE DEFLECTION, IN

0.25

0.30

Simulation of field CBR test conducted on surface of clay subgrade (1 psi = 6.89 kPa).

the field CBR test for the subgrade material as the piston is loaded well beyond the maximum deflection specified by the field CBR test standard. It can be seen that, the hyperbolic model along with the assumption constant bulk modulus predicts the upheaval as the subgrade approaches failure and shears. Figure 13 illustrates results of modeling of field CBR tests conducted on top of the crushed gravel subbase. In this case, two simulations were performed, with and without surcharges. During the field CBR tests surcharge rings are placed around the piston to account for the overburden pressure of the expected base and asphalt layers to be lay on top of the subbase. It is easily observed that a much better prediction is obtained when the surcharges are also modeled. Again, the predictions are considered to be very reasonable and encouraging 615

FINITE ELEMENT SIMULATION OF FIELD CBR TEST CBR = 10, Water Content = 30% USAF Rapid Parking Ramp Expansion Program 2007 AM2 Mat Test Section 0.20

0.10

DEFLECTION, INCHES

0.00 0.0

0.5

–0.10

350 LB

–0.20

400 LB

1.0

1.5

2.0

2.5

3.0

3.5

4.0

425 LB –0.30

450 LB

–0.40

–0.50 DISTANCE FROM CENTERLINE OF PISTON, INCHES

Figure 12. Simulated surface profile of field CBR test conducted on top of clayey subgrade (1 in. = 25.4 mm; 1 lbf = 4.45 N). FEM SIMULATION OF FIELD CBR TEST BASE - CRUSHED LIMESTONE ITEM 4 3000

2500 BASE: 6" CRUSHED LIMESTONE

LOAD, LB

2000 WITH SURCHARGES (1 STEEL RING)

SUBBASE: 23" CRUSHED AGGREGATE

1500

SUBGRADE: 24" CH CLAY CBR = 4

1000

COMPACTED SILTY SUBGRADE

500

AVERAGE BASE CBR = 42 MOISTURE CONTENT = 2.4%

0 0.0

0.2

0.4

0.6

0.8

1.0

DEFLECTION, INCHES

Figure 13. Simulation of field CBR tests conducted on top of the crushed gravel subbase (1 in. = 25.4 mm; 1 lbf = 4.45 N).

and support the assumptions that the hyperbolic soil model with the constant bulk modulus assumptions may be used to predict pavement behavior under actual aircraft loads. 6

PREDICTION OF STRESSES UNDER AIRCRAFT LOADING

In the final phase of this study, the results obtained from modeling laboratory triaxial tests and field CBR tests were extended an additional step to provide predictions of actual stresses under full size aircraft tires. Pavement structures from the full-scale pavement section were modeled using the hyperbolic soil model. Figure 14 shows vertical stress readings collected from earth pressure cells 616

Figure 14.

Vertical earth pressure readings in lane 1 item 4 (1 in. = 25.4 mm; 1 psi = 6.89 kPa).

Figure 15. Comparison between measured and modeled vertical pressures (1 in. = 25.4 mm; 1 psi = 6.89 kPa).

(EPC) installed in the base course and subgrade at depths of 33.0 cm (13 in.) (EPC1) and 91.4 cm (36 in.) (EPC2) below the pavement surface, respectively. The pavement was trafficked with a slow moving (approximately 3.2 km/h or 2 miles/hour) C17 tire loaded to 151.3 kN (34,000 lb) EPC1 read a vertical pressure of 537 kPa (78 psi), while EPC2 read a pressure of 103 kPa (15 psi). The pavement structure illustrated to the right of Figure 14 was modeled using the finite element implementation of the hyperbolic model with constant bulk modulus and using the soil parameters described in this paper. Three simulations were performed, two of them assuming that the asphalt layer was linear and elastic with 1378 MPa (200,000 psi) and 689 MPa (100,000 psi) modulus of elasticity and one assuming that the asphalt behaves more like a high quality aggregate base with a high cohesion value (cohesion = 138 kPa or 20 psi). These results are shown in Figure 15 and show that good agreement between measured and simulated vertical pressures is obtained at the subgrade. However, stresses in the base course are considerably influenced by how the asphalt layer is 617

modeled. If the asphalt layer is assumed to linear elastic, the vertical stresses are underestimated by as much as 60%. If the asphalt layer is modeled like a high quality aggregate layer, the vertical stress is only underestimated by about 20%. This implies that more rigorous analyses of the asphalt properties are required to properly model the influence of the asphalt layer in vertical stresses at depths near the surface of the pavement. However, the ability of the finite element analytical procedure described in this paper to model the laboratory and field tests and the good predictions obtained for the subgrade stresses presents a viable tool for future analyses of full-scale pavement structures subjected to aircraft loads. 7

CONCLUSIONS AND RECOMMENDATIONS

This paper presented a new approach implemented at the ERDC for modeling pavement materials. In this approach, the materials are assumed to maintain a constant bulk modulus while varying the elastic modulus and Poisson’s ratio as the element approaches failure. These assumptions prevent the collapse of elements as they approach failure, forcing material failure in shear. The results of the analyses performed during this study lead to the following conclusions and recommendations: 1. The hyperbolic model can be fit to the subgrade, subbase, and base course materials used in this study. Results of simulations of laboratory tests used to obtain model parameters produced curves that matched laboratory data. 2. Simulations of additional laboratory and field tests yielded responses that matched tests performed on these materials. 3. Predictions of responses to full-scale traffic loading yielded reasonable results at the subgrade level. Responses in the base and subbase are more dependent upon the material properties used to model the asphalt concrete surface layer. 4. Additional analyses are required to predict the response of the asphalt concrete layer. 5. It is recommended that this analysis method be implemented into military design procedures for flexible pavements. This method may be used to develop criteria for pavements in regions where limited data is present.

ACKNOWLEDGEMENTS The tests described and the resulting data presented herein, unless otherwise noted, were obtained from research conducted under the Validation of CBR Design Method project sponsored by the U.S. Air Force, and performed at the U.S. Army Engineer Research and Development Center, Waterways Experiment Station. Permission was granted by the Director, Geotechnical and Structures Laboratory, to publish this information. REFERENCES Brabson, W.N. 1973. Use of Finite Element Theory to Predict Modulus of Soil Reaction in Soft Clays, M.S. Thesis, Mississippi State University, Mississippi. Chou, P.C. and Pagano, N.J. 1967. Elasticity: Tensor, Dyadic, and Engineering Approaches, New York, Dover. Hinton, E., and Owen, D.R.J. 1977. Finite Element Programming, San Diego, Academic Press. Kulhawy, F.H., Duncan, J.M. and Seed, H.B. 1969. Finite Element Analyses of Stresses and Movements in Embankments During Construction. Report No. TE-69-4, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. Townsend, F.C. and Chisolm, E.E. 1976. Plastic and Resilient properties of Heavy Clay under Repetitive Loadings, Technical Report S-76-16, U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. U.S. Army Engineer Waterways Experiment Station. 1960. The Unified Soil Classification System. Technical Memorandum No. 3–357, Vicksburg, MS. Zienkiewicz, O.C. and Taylor, R.L. 2000. The Finite Element Method, Volume 1, The Basis, Woburn, Butterworth-Heinimann.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Use of 3-dimensional discrete element model to examine aggregate layer particle movement due to load wander P.R. Donovan, E. Tutumluer & H. Huang Department of Civil and Environmental Engineering, University of Illinois, Urbana, Illinois, USA

ABSTRACT: Many large aircraft have similar wheel loads and tire pressures but different gear configurations. Individual aircraft also have slightly different transverse travel variation (wander) depending on factors such as the width of the pavement, the time of day, and type of operation (landing, takeoff, or taxiing). As a result, aircraft wheel loads are commonly applied on relatively wide traffic lanes. In recent full-scale pavement test studies at the US Federal Aviation Administration’s National Airport Pavement Test Facility, a complete load wander cycle was applied sequentially but not randomly to realistically apply traffic loading and investigate effects of offset wheel loads on performance. Each pass at a different offset was observed to cause particle movement and rearrangement in the unbound aggregate base and subbase layers of the flexible pavement test sections. This paper aims to demonstrate how a wheel load can cause particle movement in an unbound aggregate layer using a simplified 3-dimensional discrete element model. 1

INTRODUCTION

Unbound aggregate layers commonly used in flexible pavements as structural components serve the main function of load distribution. During pavement construction and compaction as well as the application of traffic loading, the granular layer consolidates, gains strength with time, and stabilizes with little additional residual or plastic deformation. This so-called “shakedown” process is often observed in the channelized highway pavement loading case as well as with repeated load triaxial testing in the laboratory. The recent successful research efforts on the aggregate shakedown concept by Werkmeister et al. (2002) identified three zones of shakedown as: A–plastic shakedown, B–plastic creep, and C–incremental collapse. In range A (plastic shakedown), the residual strain rate decreases quickly and eventually, the layer shows no further residual deformation with additional load repetitions. Range B (plastic creep) initially shows a decreasing residual strain rate but as the number of load cycles increase, the residual strain rate resumes an upward climb, eventually leading to incremental collapse. This behavior has been attributed to grain abrasion caused by the large resilient deformations seen in this stress range. The grain abrasion is believed to decrease the angle of internal friction by polishing the grain contact points thus lowering the coefficient of friction between grains. This causes more residual deformation with additional load cycles without increasing the applied stress. In range C (incremental collapse), it is probable that due to the high stress range both grain abrasion and particle crushing combine to quickly destroy, i.e., permanently deform in an excessive manner, an unbound aggregate layer. This region is characterized by a slower reduction in the residual strain rate than range A or B and a quick resurgence of the strain rate after a very limited number of load cycles. It is also likely that for all shakedown ranges, any particle rearrangement that occurs due to stress will relieve some small amount of the residual compressive stress in an unbound layer that was induced by compaction and preloading of the layer; which in turn will cause additional rutting. In the case of airfield taxiways and runways, pavements must be wide enough to allow the safe movement of the largest anticipated aircraft and keep any wing-mounted engines 619

over paved areas to prevent ingestion of foreign objects. This requirement translates into pavement widths much larger than required for many aircraft. Depending on paved shoulder widths, even the largest aircraft will have a substantial amount of freedom to move from one side to the other. Tests at the Federal Aviation Administration’s (FAA’s) National Airport Pavement Test Facility (NAPTF) using new generation aircraft loads indicate that applying a sequential wander pattern to asphalt pavements can reduce or even negate rutting. What has been seen is that the downward residual deformation (rutting) caused by a pass of heavily loaded landing gear is canceled by the upward residual deformation (heave) resulting from the pass of the same gear offset by wander (Hayhoe & Garg 2002). Figure 1 provides a simple diagram of the observed behavior and Figure 2 shows how the stress in a soil element offset from a load can change with a moving wheel. The test data indicate that the sequential wander pattern reduces or even negates the shakedown effect possibly due to particle movement and rearrangement. The particle rearrangement in turn reduces the strength of the unbound layer causing future load applications to cause more residual deformation. The strength reduction can be due to the following factors: (1) a less dense particle matrix and (2) grain abrasion, which reduces the coefficient of friction between particle contact points, as seen in range B shakedown behavior. This paper highlights recent analysis results of the NAPTF full-scale pavement trafficking data that show the detrimental effects of offset wheel loads on unbound aggregate layer

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Original Rut Negated

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Schematic explaining the influence mechanism of offset wheel.

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Stress change due to moving offset wheel.

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deformation behavior. Using a three-dimensional (3D) discrete element model, individual particle movements are investigated in this paper due to the application of offset wheel loading. 1.1 Aircraft wander Aircraft gear dimensions are relatively small compared to runway and taxiway widths and aircraft are not restricted to specific travel lanes. The side-to-side drift is called wander and pilots have freedom to safely wander across a wide area. Airports can have runways 150 to 200 ft (46 to 61 m) wide with taxiways from 75 to 100 ft (22.9 m to 30.5 m) wide. The newest Airbus A380 currently has the widest gear carriage width, which is 45.3 ft (13.8 m). The Lockheed L1011, the Boeing 747 (B747), and B777 have carriage widths of around 40 ft (12.2 m). The minimum distance from the outer A380 carriage wheels to the edge of the pavement ranges from 27 ft (8.3 m) for a 100 ft (30.5 m) taxiway to 77 ft (23.5 m) for a 200 ft (61 m) runway; clearly a large tolerance and a lot of room to maneuver. A normal highway lane of 12 ft (3.7 m) provides only 1.75 ft (0.5 m) of clearance for a tractor trailer with a nominal 8.5 ft (2.6 m) outer wheel spacing; considerably less freedom to wander. In addition, centerline pavement markings help channelize traffic as pilots try to keep their engines over paved surfaces to prevent ingesting debris, but the possibility exists for safe maneuvering well away from the centerline, especially if there are paved shoulders. Wander varies based on the airfield area traversed. Aprons and the interior portions of the runway usually see the most wander. Aprons see high wander because paths to parking spots are not exact and maneuvering any large aircraft into the parking stalls is difficult. Interiors of runways also experience high wander because the aircraft move at high speed whether taking off or landing. Crosswinds, slightly uneven pavement, shifting fuel and baggage loads, and minor thrust variations from multiple engines all cause horizontal forces that the pilot has to correct for and minor corrections at high speeds translate to large horizontal movements. Taxiways and the ends of runways see the least amount of wander because aircraft move relatively slowly in these areas and steering corrections by the pilot can keep the aircraft near the centerline. Taxiways see the largest and slowest moving loads, and are therefore the critical design areas on an airfield. From research findings in the 1970’s, the FAA selected a taxiway wander width of ±35 in. (±889 mm) based on a wander standard deviation of 30.5 in. (775 mm) which covers 75% of all traffic, 1.15 standard deviations (Brown & Thompson 1973, HoSang 1975).

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Figure 3.

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Various in-service aircraft gear locations with superimposed wander widths.

621

1.2 Aircraft gear variation The various gear configurations between aircraft introduce offset wheels regardless of wander. Figure 3 shows the various gear configurations for some in-service aircraft along with the ranges of their wander patterns based on the FAA taxiway wander width of ±35 in. (±889 mm). It is interesting to note how many of the different aircraft have gear wheels that bisect the carriages of another aircraft. An example is how the inner and outer carriage wheels of the A380 are offset almost exactly halfway between the wheels of the B747 carriages. Because the transverse offset of loads is important to pavement response, it is important to know the location of various aircraft gear wheels to capture the load effects from one aircraft on the pavement under another. 2

NAPTF TESTING

The FAA’s NAPTF located at the William J. Hughes Technical Center close to the Atlantic City International Airport was built to analyze the effects of New Generation Aircraft (NGA) on pavements. The NAPTF was constructed to generate full-scale tests in support of the investigation of airport pavements subjected to complex NGA gear loading configurations. Full-scale pavement tests were conducted using a specially designed test vehicle which can apply loads of up to 75 kips (34,020 kg) per wheel on two landing gears with up to six wheels per gear. The test vehicle at NAPTF is supported by rails on either side, which allow the load to be varied according to the testing protocols. The vehicle can be configured to handle single, dual, dual-tandem, and dual-tridem loading configurations. The wheel and gear spacing can be varied. Wheel loads are programmable along the travel lanes and the lateral positions of the landing gears are variable up to plus or minus 5 ft (1524 mm) from the nominal travel lanes to simulate aircraft wander. The first series of tests conducted are referred to as Construction Cycle 1 (CC1) tests. The Boeing 777 (B777) type landing gear tested in the North lane was a six wheel dual-tridem configuration with dual wheel spacing of 54 in. (1372 mm) and tridem axle spacing of 57 in. (1448 mm). The wheel loads were set to 45 kips (200.2 kN) and the tire pressure was set to 189 psi (1.3 MPa). The complete six wheel strut load was (270 kips) (1.2 MN). Traffic was applied at 5 mph (8 km/h). This speed represents aircraft taxiing from the gate to the takeoff position. The south wheel track was loaded with a four-wheel dual-tandem type representing a Boeing 747 (B747) gear configuration. The dual wheel spacing was 44 in. (1118 mm) and the tandem axle spacing was 58 in. (1473 mm). Wheel loads of 45 kips (200.2 kN) per wheel similar in magnitude to the B777 loading case were applied to give a strut load of 180 kips (800.8 kN). The load carriage containing both struts is a continuous system, therefore traffic speed for the B747 and B777 matched. 2.1 NAPTF Multi-depth deflectometer data The CC1 NAPTF pavement test section details are given in Figure 4 with the target subgrade California Bearing Ratios (CBRs) for the low and medium strength test sections. Multi-depth deflectometers (MDDs) were used to record the deflections of the pavement system under applied traffic loading. The MDDs were located at critical locations within the asphalt, unbound aggregate, and subgrade layers. The MDDs work by recording the deflection of the individual sensors in relation to an “anchor” sensor that is buried below the zone of influence of the anticipated loads. The surface sensor is actually the only sensor to be directly connected to the anchor; the other sensors measure their deflection in relation to the surface sensor. The absolute movement of the individual sensors is then calculated by subtracting the individual sensor reading from the surface sensor reading. Individual layer response is calculated by subtracting the lower sensor reading from the higher sensor reading. 622

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Figure 4.

Cross section details of the CC1 NAPTF pavement test sections.

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66 pass wander pattern applied at NAPTF CC1 tests.

2.2 NAPTF load wander patterns To account for aircraft wander, the test passes or load applications were divided into nine wander positions spaced at intervals of 9.843 in. (250 mm). One complete wander pattern consists of 66 vehicle passes (33 East and 33 West) with five wander sequences per wander pattern. Each position was traveled a different number of times based on a normal distribution with a standard deviation that is typical of multiple gear passes on airport taxiways, i.e., 30.5 in. (775 mm). The 78.7 in. (2 m) wander width of the nine wander positions cover 80% (1.29 standard deviations) of all traffic from a normal distribution curve of real world taxiway traffic. Figure 5 shows the wander position, pass number (odd move West to East and even move East to West), and wander sequence for a complete wander pattern. A random application of wander positions would provide a more realistic simulation of traffic, however, a sequential wander pattern was applied to all previous full-scale tests and a sequential pattern allows for the analysis of the wander effect, which would otherwise be hard to distinguish. 623

3

DATA ANALYSIS—PARTICLE MOVEMENT

The individual layer response under wheel loading can be separated by wander position, traffic direction, and wander pattern sequence. Such an analysis was necessary to combine the data into the 66 pass wander patterns and investigate the influences of wander sequence and wander position on the pavement residual responses. Figures 6 through 8 show the residual deformation responses in the layers of the B777 LFC section over 66 pass wander patterns. The MDDs did not measure significant residual deformation in the subgrade layer with the residual response values rarely exceeded ±10 mils (0.25 mm). This is considerably less than the responses measured in the unbound aggregate layers indicating that the unbound aggregate layers were responsible for the majority of the upward and downward residual response of the pavement system. As seen in Figure 6, no significant contractive or dilative residual responses were caused by multiple wander positions in the subgrade. Figures 7 and 8 show the 66 pass wander patterns for the P154 and the P401-P209 layers, respectively. Note that Figure 8 includes both the P401 and P209 layers; in other sections, the P401 layer did not exhibit significant residual deformation, therefore Figure 8 shows the deformation behavior of the P209 layer. Both figures indicate that traffic in the West to East (W-E) direction on wander row 0 produced the maximum downward residual deformation. This corresponded to the maximum load position with a wheel centerline located a mere 0.6 in. (1.5 cm) from the MDD centerline. Wander row 1 was the only other wander position to produce a consistent downward residual deformation of both the P154 and P401-P209 layers. All of the other wander positions contribute various amounts of upward residual deformation. Wander position 2 seems to provide the highest upward deformation for both layers, but due to limited data points, this wander position cannot be conclusively regarded as causing the most dilative effect.

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Figures 7 and 8 show that as the number of passes increases both the upward and downward residual deformation values, in general, increase. This is in contrast to the shakedown concept where residual deformation per pass decreases with increasing repetitions for stable behavior. The occurrence of upward and downward residual deformations proves the rearrangement of particles in the unbound aggregate layers. 4

DISCRETE ELEMENT MODELING

The Discrete Element Method (DEM) is a numerical procedure that can solve problems involving individual particles interacting with each other in a granular assembly. Cundall (1971) was the first to propose the DEM for use in rock mechanics. Essentially, the method attempts to solve problems with particulate materials realistically as opposed to finite element or elastic layered calculations that treat particulate matter as a continuum. The advantage of the DEM is that it can simulate the actual particles in an unbound aggregate layer; the disadvantage is often the computational complexity of the problem and the number of calculations it takes to solve DEM simulations. The 3D DEM simulation conducted for this paper was intended to highlight in a simple simulation case the effects of offset wheel loads on the deformation behavior of a granular layer assembly. The DEM program BLOKS3D developed at the University of Illinois has been used to model unbound aggregate layer deformation behavior (Nezami et al. 2006, Zhao et al. 2006). The particles are simulated as non-deformable blocks represented by 3D polyhedrons. Each particle is assigned with the coordinates of each vertex and vertices included for each face. A user defined particle library is used to develop the particle size distribution or gradation. The program utilizes realistic aggregate shapes scaled to different sizes to establish the specified gradation (see Figure 9). 4.1 3D model of unbound aggregate particle rearrangement The analyses of the NAPTF data indicated that wheel loads caused dilation of unbound aggregate materials some distance away from the load location (Hayhoe & Garg, 2002; Donovan & Tutumluer, 2008). Finite element and elastic layered calculations do not show this dilative response. Therefore, the goal with the 3D DEM is to show that upward movement of particles away from the loaded area can happen in granular layers. To simplify the problem the unbound aggregate layer was simulated without asphalt surfacing and in the presence of a rigid underlying layer that does not deform under load. This

Figure 9. Comparisons of an actual aggregate particle with the aggregate element generated for BLOKS3D DEM program.

626

would highlight the movement of the unbound aggregate particles, which would normally have imposed confinement from the asphalt layer although the dilative effect does occur with a thin asphalt layer as shown in Figures 6 through 8. The load was applied monotonically because calculations of a cyclic load response required approximately 30 minutes of computer time for every second of load time and if one cycle took one second then the response from 1000 cycles would take 20 days to calculate. An attempt was made to simulate either the P209 or the P154 particle gradations, however the well-graded nature of these specifications are difficult to simulate because a well graded soil has by definition multiple particle sizes and decreasing the particle size greatly increases the calculation effort. Therefore, the size distribution of particles used was limited to 0.25 to 0.5 in. (6.35 mm to 12.7 mm). The angularity of the particles was defined by an imaging based quantitative “Angularity Index” (AI) which is higher for more angular particles (AI = 390 rounded, AI = 630 angular) according to Rao et al (2002). The AI used for this simulation was 574. Surface texture properties were simulated using a surface friction angle of 35o, which corresponds to a coefficient of friction of 0.7. The domain of the simulation was limited to an aggregate box with 19.7 in. × 19.7 in. × 7.9 in. (0.5 m × 0.5 m × 0.2 m) deep and approximately 12,000 particles were required to fill this space. The simulation applied a 5,000 lb. (22.2 kN) load on a 5.1 in. (0.13 m) square plate centered on the box assembly as shown in Figure 10. The applied pressure of 189 psi (1.3 MPa) matches the tire pressure of the NAPTF tests. This load greatly exceeds the load capacity of the simulated unbound aggregate layer; however, the goal was to observe the movement of the particles and by applying a static load close to failure clearly indicated movement of the particles. 4.2 Results The simulation shows that the particulate nature of the unbound aggregates causes movement of the particle around the load plate. Figures 11 and 12 show the predicted contact force vectors, with lengths proportional to magnitudes, calculated in the simulation after 10 seconds of load application. The particle movement follows the direction of contact force vectors. Note that Figure 12 magnifies both the picture size and the force vector length; therefore, force vectors not visible in Figure 11 are visible in Figure 12. The plate pushes through the particles because of the excessive pressure. The plate would continue to the bottom of the domain if the simulation continued. In this case, the applied load causes the particles to move upward around the plate as one would expect from a close to failure load level. The force vectors do show some upward movement of the particles away from the load location; however, some are directed horizontally and not upward. At the right

Figure 10.

Details of DEM simulation of the granular box assembly.

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Individual particle contact force vectors from monotonic load plate 3D DEM simulation.

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(m) Figure 12. Detail A: close up view of the force vectors from monotonic load plate 3D DEM simulation.

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end of the analysis domain shown in Figure 12, the force vectors are clearly directed upward with larger horizontal components. Such particle movements and rearrangements favor loosening of compacted and shaken-down aggregate layers, i.e. an anti-shakedown effect, when traffic loading is applied with wander such as in the case of NAPTF CC1 tests. 5

SUMMARY & CONCLUSIONS

Studies conducted at the Federal Aviation Administration’s (FAA’s) National Airport Pavement Test Facility (NAPTF) have shown that the individual particles in unbound aggregate base/subbase layers can slide, rotate, and rearrange under load causing a heave or dilative effect at an offset distance from an applied aircraft wheel load. The particulate nature of the unbound aggregate layer along with the combination of wheel load, tire pressure, wheel spacing, axle spacing, trafficking speed, trafficking direction, and pavement system characteristics dictate where the dilative element or elements are. They also dictate the magnitude of the heave. It is the reaction of the discrete particles to load that cause upheaval of soil elements away from the load. If airfield traffic were channelized there would be little concern over the effect of offset wheel loads, but wide pavements and different aircraft gear configurations ensure that airfield traffic will always apply offset wheel loads with significant wander. Simulation of the offset wheel load effect is difficult to accomplish using a finite element or an elastic layered analysis, which inadequately assumes a continuum for modeling the granular layer. Discrete Element Methods (DEMs), on the other hand, can simulate individual particle movements, such as translation, sliding and rotation, and therefore are more suitable to investigate effects of load wander on the residual or permanent deformation behavior due to each load pass. The DEM considered in this paper utilized realistic three-dimensional (3D) polyhedron shaped angular particles in the simulation of an unbound aggregate box assembly response to monotonic loading close to failure loads. The purpose of this simulation was to show the movement of unbound aggregate particles at an offset distance from the load location could be in the horizontal and upward direction. Despite many simplifying assumptions made, such as the uniform particle size and the rigid base used in the simulation, the DEM results showed such movement clearly with the help of visualizing particle contact force vectors and their predicted orientations. Such tendencies for dilative behavior may cause particle rearrangements in favor of loosening the compacted and shaken down aggregate layers, i.e. an anti-shakedown effect, when traffic loading is applied with wander. ACKNOWLEDGEMENTS This paper was prepared from a study conducted in the Center of Excellence for Airport Technology. Funding for the Center of Excellence is provided in part by the Federal Aviation Administration. The Center of Excellence is maintained at the University of Illinois at UrbanaChampaign in partnership with Northwestern University and the Federal Aviation Administration. Ms. Patricia Watts is the FAA Program Manager for Air Transportation Centers of Excellence and Dr. Satish Agrawal is the FAA Airport Technology Branch Manager. The contents of this paper reflect the views of the authors who are responsible for the facts and accuracy of the data presented within. The contents do not necessarily reflect the official views and policies of the federal aviation administration. This paper does not constitute a standard, specification, or regulation. REFERENCES Brown, D.N. & Thompson, O. 1973. Lateral distribution of aircraft traffic; Miscellaneous Paper S-73-56, Soils and Pavements Laboratory, U.S. Army Engineer Waterways Experiment Station, Vicksburg, Mississippi. Cundall, P.A. 1971. A computer model for simulating progressive, large scale movements in block rock systems; Symposium of the International Society for Rock Mechanics, Nancy, France.

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Donovan, P. & Tutumluer, E., “Anti-shakedown of unbound aggregate pavement layers subjected to traffic loading with wander,” Proceedings of the 1st International Conference on Transportation Geotechnics and the 7th Unbound Aggregates in Roads Symposium (UNBAR7), Nottingham, UK, August 25–27, 2008. Hayhoe, G.F. & Garg, N. 2002. Subgrade strains measured in full-scale traffic tests with four and sixwheel landing gears; Proceedings of the FAA Airport Technology Transfer Conference, Atlantic City, NJ, USA, May 5–8 2002. Ho Sang, V.A. 1975. Field survey and analysis of aircraft distribution on airport pavements; Report No. FAA-RD-74-36. U.S. Federal Aviation Administration. Rao, C., Tutumluer, E. & Kim, I.T. 2002. Quantification of coarse aggregate angularity based on image analysis,” Transportation Research Record (TRB), National Research Council, No. 1787, Washington, D.C., 117–124. Nezami, E.G., Hashash, Y.M.A., Zhao, D. & Ghaboussi, J. 2006. Shortest link method for contact detection in discrete element method. International Journal for Numerical and Analytical Methods in Geomechanics 30(8): 783–801. Werkmeister, S., Numrich, R. & Wellner, F. 2002. The development of a permanent deformation design model for unbound granular materials with the shakedown-concept; Proceedings of the 6th International Symposium on the Bearing Capacity of Roads and Airfields (BCRA), Lisbon, Portugal, 24–26 June 2002, 1081–1098. Rotterdam: Balkema. Zhao, D., Nezami, E.G., Hashash, Y.M.A. & Ghaboussi, J. 2006. Three-dimensional discrete element simulation for granular materials; Engineering Computations, 23(7): 749–770.

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Backcalculation analyses of deflection measurements

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Backcalculation of the stiffnesses of cement treated base courses using artificial intelligence M. Miradi, A.A.A. Molenaar & M.F.C. van de Ven Delft University of Technology, Delft, The Netherlands

S. Molenaar EDP Consultants Inc., Kirtland, Ohio, USA

ABSTRACT: It is common practice to evaluate the condition of pavements by means of deflection measurements and by back-calculating the stiffness modulus of the various pavement layers. Practice has shown however that the commonly used back-calculation procedures not always result in realistic values for the stiffness of stiff cement treated bases (CTB). This becomes a problem when the stiffness of the base course is specified in contract documents. This study presents a procedure for the prediction of stiffness of CTBs from deflection measurements using two artificial intelligence (AI)-based methods, being support vector machines (SVM) and artificial neural network (ANN). The procedure is based on a data base of deflection bowls of 2880 three layer pavement. The structures consisted of an asphalt top layer, a cement treated base and subgrade. The deflection bowls were calculated using the multi-layer program BISAR. The results showed that SVMs produce better results than ANNs. However, an extra validation using 100 new data points showed the quality of ANN. It is therefore concluded that both ANN and SVM are powerful tools for accurate prediction of stiffness of CTB. 1

INTRODUCTION

In the Design and Build (DB) and Design, Build and Maintain (DBM) contracts which are currently used in the Netherlands, contactors are responsible for the selection of the materials to be used as well as for the structural design. Nevertheless the clients want proof that the contractor has really built what he has proposed and one way of getting that proof is back calculation of the stiffness of the pavement layers using deflection measurements and measured layer thicknesses as input. This so called “backward analysis” is not as straightforward as it seems. Especially in cases where the pavement has a thin asphalt top layer and where the stiffness of the base layer is higher than that of the asphalt layer, the iterative process might result in too high values for the asphalt layer stiffness and too low values for the base layer stiffness. Since a pavement structure with a cement treated base quite often belongs to this category, such inaccurate backward analysis might very well occur when analyzing such pavements resulting in too low values for the back calculated cement treated base stiffness. This, in turn, might lead to contractual disputes since the base modulus seems not to have the expected value, and then the authority supposes that the pavement structure has not been constructed according to the proposal made by the contractor even though in reality the stiffness of the base might be according to the design. A model which correctly predicts the stiffness of a cement-treated base, using the deflection bowl and the thicknesses of the pavement layers as input variables, is therefore highly desirable. Such a model may be provided by artificial neural networks (ANNs) or support vector machines (SVM), being two strong modeling tools within the field of artificial intelligence (AI). AI is the science of making computers do things that require intelligence if 633

done by men (Minsky, 1986). Artificial neural networks are data processing systems. They are mathematical models of the human neural system, trying to mimic the intelligence of humans. ANNs have the same network structures as human brain. An artificial neural network (ANN) is a layered network of artificial neurons (ANs). Each AN receives signals from input variables or from other ANs, gathers these signals and, when needed, transmits a signal to all connected ANs. Figure 1(a) is a representation of an artificial neuron. Input signals are inhibited or excited through negative or positive numerical weights associated with each connection to the AN. The strength of an existing signal is controlled via a function, referred to as the activation function, which calculates the output signal of the AN. The role of this function is to bring nonlinearity to ANN. An ANN may consist of an input layer, hidden layer(s), and an output layer. ANs in one layer are connected, fully or partially, to the ANs in the next layer. A typical ANN structure is depicted in Figure 1(b). ANN can be employed to develop regression or classification models (Engelbrecht, 2007). For a detailed explanation of ANN, the reader is referred to Haykin (1999). Traditional neural network approaches have suffered difficulties with generalization, producing models that can over-fit the data. This is a consequence of the optimization algorithms used for parameter selection and the statistical measures used to select the ’best’ model. These problems have more or less been solved by another recent AI-based modeling technique, being support vector machines (SVM). The foundations of SVM have been developed by Vapnik (1995) and are gaining popularity due to many attractive features, and promising empirical performance. Support vector machines (SVM) ultimately make predictions based on the following function ⎛N ⎞ f ( x, w ) = sign ⎜ ∑ wi K ( x, xi ) − b ⎟ ⎝ i =1 ⎠

(1)

The key feature of the SVM is that, in the binary classification case (only two classes available), its target function attempts to minimize a measure of error on the data set while simultaneously maximizing the distance (margin) between the two classes by a separating plane ( f (x,w)). To calculate the margin, two parallel planes, one on each side of the separating plane, are “pushed up against” the data points of two classes. These data points are called support vectors. Intuitively, a good separation is achieved by the plane that has the largest margin to the neighboring data points of both classes, since in general the larger the margin the better the performance of the SVM. This is an effective mechanism leading to good generalization because the training depends only on a subset of data points, namely the support vectors that lies on the margin. Next to this, SVM uses the kernel trick (kernel = K(x,xi)) which makes the SVM construction independent on the dimensionality of input space (number of input variables).

Hidden layer Weight

Input signal x1 x2

Output layer

W1 W . 2

. . xn

Input layer

AN

Output signal

Wn

(a) Figure 1.

(b) Illustration of an artificial neuron (a) and a three layer artificial neural network (b).

634

)

3

)

f ( x, w) = sign ∑ wi K (x, xi ) − b w1

K (x, x1)

x1 Figure 2.

i=1

w2

w3

K (x, x2)

x2

Output

Weights

K (x , x3 )

Hidden layer of 3 Kernels

Input vector x

x3

An example of a support vector machine.

Kernels are generally highly nonlinear functions such as radial basis function, two-layer neural network or high degree polynomial, which enables SVM to solve complex nonlinear problems. Vector wi is the orientation of the separating plane b and is the offset of the plane from the origin. Both wi and b are automatically calculated during the construction of the separating plane. Figure 2 shows the structure of an SVM with three inputs. SVM has also been extended for regression applications. A detailed explanation of SVM regression can be found in Burges (1996, 1998), Osuna & Girosi, (1998), Vapnik (1995, 1998), and Haykin (1999). Significant research efforts have been made on modeling the stiffness of base layers. However, these efforts have been hampered by the inability to capture the underlying non-linear nature of pavement materials and by the widespread use of linear statistical relationships to model a complex and non-linear phenomena. As explained, ANN and SVM both are powerful intelligent techniques with the ability to solve complex problems. Therefore, in this paper both ANN and SVM for modeling of stiffness modulus of cement treated base courses. The remainder of this paper is as follows. First, papers from literature are discussed. Next, it is explained how the construction and deflections dataset has been set up. Then, modeling results using ANN and SVM classification will be discussed. After that, the validation of ANN regression models will be tested using a new dataset. The paper ends with conclusions. 2

LITRATURE REVIEW

Over the past two decades, there has been an increased interest in modeling with artificial intelligence (AI) techniques. Going through the litrature, we noticed that the artificial neural network (ANN) has been applied most. It also became obvious that the support vector machines have not been applied to determine the stiffness of pavement layers at all. This section provides an overview of the previous investigations of the stiffness of different pavement layers using AI techniques, mainly ANN. All of the investigations which are discussed used FWD measurements as input. Considering the computation time, some investigation showed that ANN is much faster than methods like linear-elastic multilayer programs (ELPs) or finite element methods (FEMs). Meier and Rix (1994, 1995) trained ANN with a backpropagation algorithm to calculate the elastic modulus (E) of the asphalt layer. They developed a neural network that operated 4500 times faster than the conventional algorithmic program used at that time. Khazanovich and Roesler (1997) used ANN to perform the same task for data obtained from composite pavements. Meier et al. (1997) as well as Kim & Kim (1998) trained ANN with a backpropagation algorithm to calculate the stiffness modulus of pavement layers and reported a fifty fold increase in processing speed. 635

Concerning the type of ANN being used, most researchers used ANN models with a standard backpropagation algorithm. But there were also other algorithms of ANN. For instance, Terzi et al. (2003) as well as Saltan & Sezgin (2007) applied ANN with the LevenbergMarquardt algorithm. We also reviewed the validation methods of different researches. Some researchers validated the result of their ANN models with field data. Researchers at the University of Texas at El Paso (Abdallah et al., 1998, 1999) validated their ANN models with field data from the Texas Mobile Load Simulator and observed an agreement between the results of the ANN model and the field data. Guclu & Ceylan (2007) validated their ANN models with the LongTerm Pavement Performance (LTPP) data from US29, Spartanburg County, South Carolina. Other types of validation used were cross validation methods. Saltan & Terzi (2007) used a 5-fold cross validation. But, Bredenhann & Van de Ven (2004), Loizos et al. (2007), Guclu & Ceylan (2007), Demir (2007), Ozsahin & Oruc (2007), and Ceylan et al. (2007) chose for a hold-out cross validation because of its shorter calculation time. Considering the data, we focused our review on the number of data points, the origin of data, and the input variables. The number of data points varied between less than 50 to more than 24 000. Saltan and Terzi (2007) used only 35 data points while Terzi et al. (2003), Demir (2007), Ozsahin & Oruc (2007) had gathered about 150 data points. Bredenhann & Van de Ven (2004) had a much larger dataset with 10 000 data points. The largest datasets belonged to Ceylan and his co-workers (Guclu & Ceylan, 2007; Ceylan et al., 2007), containing more than 20 000 data points. The data of pavements were originated from different countries such as Greece (Loizos et al., 2007), South Africa (Bredenhann & Van de Ven, 2004), Turkey (Saltan & Terzi, 2007), and the United States (Abdallah et al., 1998, 1999a; Guclu & Ceylan, 2007). Many researchers used the thickness of the layers and the deflection bowl as input variables (Ceylan et al., 1998, 1999; Abdallah et al., 1998, 1999a; Bredenhann & Van de Ven, 2004; Saltan & Terzi, 2007; Loizos et al., 2007; Ceylan et al., 2007). The latest investigations went further than just ANN models. They compared or combined ANN models with other methods. Rakesh et al. (2006) used the combination of ANN and genetic algorithm (GA). Saltan & Sezgin (2007) as well as Ceylan et al. (2007) combined ANN models with finite elements. 3

BISAR DATA

As discussed before, the goal of this study is to use two AI tools to predict the stiffness modulus of the cement treated base (CTB), E2, with available deflections at 0,300,...,1800 mm distance from the centre of the load (D0, D300,….,D1800) and the total pavement layer thickness (h1 + h2) as input variables. This is presented as follows E2 = f ( D0 , D300 , D600 , D900 , D1200 , D1500 , D1800 , h1 + h2 )

(2)

The reason for using the total thickness instead of each layer thickness separately was that the error that is made in determining the total thickness by means of radar measurements is less than the error that is made when the thickness of the individual layers needs to be determined. The first part of this section deals with the calculation of data using the linear-elastic multilayer program BISAR. The second part discusses how the number of input parameters is reduced to decrease the complexity of the function. 3.1 Calculations We calculated the deflection bowls for this study using the multilayer linear-elastic computer program BISAR. The BISAR calculations are done for a pavement structure with three layers namely the asphalt layer, the cement treated base (CTB) layer, and the subgrade. The properties used for the calculations are summarized in Table 1. As it is obvious from Table 1, for E1, E2, and E3 discrete values have been used, for instance 1500, 3000, 4500 etc and so no values 636

Table 1.

Overview of the layer combinations for which deflection bowls were calculated.

Variable

Value

Unit

Number of layers Stiffness modulus of asphalt layer (E1) Stiffness modulus of cement treated base (E2) Stiffness modulus of subgrade (E3) Poison’s ratios of asphalt layer (v1) Poison’s ratios of cement treated base layer (v2) Poison’s ratios of subgrade layer (v3) Asphalt layer thickness (h1) Cement treated base thickness (h2)

3 4000, 6000, 8000, 10000 1500, 3000, 4500, 6000, 7500, 9000 50, 100, 150, 200 0.35 0.20 0.35 100, 150, 200, 250, 300 150, 200, 250, 300, 350, 400

– MPa MPa MPa – – – mm mm

between 1500 and 3000. The reason for this was to limit the time needed to prepare the input. These specific values have been chosen because according to road experts this range is often measured in practice. Full friction between all the layers is assumed in all the calculations. The magnitude of the load pulse is taken as 50 kN with a radius of 150 mm. The total number of calculations thus is 4 values of E1 multiplied by 6 values of E2 multiplied by 4 values of E3 multiplied by 5 values of h1 multiplied by 6 values of h2, resulting in 2880 combinations. For each of the 2880 pavement structures, the surface deflections caused by the load are calculated at the loading plate centre (D0), 300 mm from the centre (D300), 600 mm from the centre (D600), 900 mm from the centre (D900), 1200 mm from the centre (D1200), 1500 mm from the centre (D1500), and 1800 mm from the centre (D1800). Through D0 to D1800 the deflection bowl can be concluded. After calculations, 2880 deflection bowls were ready to model the elastic modulus of the cement treated base (CTB) (E2). 3.2 Selection of input variables Although all the deflections (D0, D300, D600, D900, D1200, D1500, D1800) can be used to predict E, using less input variables reduces the degree of complexity of the final model and enhances the effectiveness and potential interpretability. Work done by KOAC consultants and the Delft University of Technology (van Gurp & Wennink, 1997) has shown that it is much more effective to use the variables SCI (D0 – D300) [μm], BDI (D300 – D600) [μm], and BCI (D600 – D900) instead of all deflections (D0, D300, D600,…,D1800) for predictive purposes. It was therefore decided to use these variables and the total pavement layer thickness (h1 + h2) as input variables. This means that the goal function shown by Equation 2 will be changed to the following one, reducing the input variables from eight to five. E2 = f ( D0 , SCI , BDI , BCI , h1 + h2 )

(3)

where SCI = D0 – D300 [μm], BDI = D300 – D600 [μm], and BCI = D600 – D900 [μm]. 4

ARTIFICIAL INTELLIGENCE BASED MODELS

This section discusses the results of the application of two AI-based methods: artificial neural network and support vector machines. 4.1 Artificial neural network models Applying the regression power of ANN, a regression ANN model was developed. The dataset (2880 data points) was partitioned into a training set (1999 data points), a validation set (441 data points), and a test set (440 data points). The training set is used to train (fit) the model, the validation set is used to validate the training process and to avoid over-fitting. 637

Over-fitting means that if the model starts to fit to each single data points instead of finding a general pattern in the data. Finally, the test set is used to test the performance of the model after the training was carried out. One of the important variables in ANN modeling is the activation function. Trying different activation functions for this problem showed that hyperbolic tangent shows the highest model performance. In ANN modeling, the determination of the number of hidden layers and hidden neurons is a crucial step. Concerning the number of hidden layer, according to universal approximation theorem (Hecht-Nielsen, 1990), one hidden layer is enough to model almost all problems. The detailed mathematical description of this theorem is given by Haykin (1999). Concerning the optimal number of hidden neurons, an approach explained by Haykin (1999) was used. Following this approach, the network was trained with different number of hidden neurons in one hidden layer (from 1 to 30) and was tested on the validation set each time. The number of hidden neurons which results in the lowest validation error is the optimal number of hidden neuron. In this case, 17 neurons showed the best performance. Experiencing with many different training algorithms leads to the Quasi-Newton backpropagation algorithm. The root mean square error (RMSE) of the training and testing set were 250.66 and 277.01, respectively. RMSE can be calculated using Equation 4.

∑ i =1( yp − y)2 n

RMSE =

n

(4)

where yp = predicted output, y = the actual output, n = the number of data points. The trained model was then tested with the test set. The RMSE of the test set amounted 257.64 with R-squared of 0.982. R-squared is the statistical measure of how well a regression method approximates input data. Figure 3 shows the scatter plot of the comparison between the actual output (from dataset) and the predicted output (predicted by ANN) using the test set. Figure 4 shows the relative importance (contribution to ANN training) of the input variables. Road engineering experts rated the outcome of the ANN modeling as not good enough. First of all the scatter in the predicted E2 value (see Figure 3) was considered too large. This implies that there are too many cases where the base modulus E2 is predicted too high (which is beneficial to the contractor) or where the predicted base modulus is too low. This is bad

Figure 3.

Scatter plot of the ANN regression model (Quasi-Newton).

638

Figure 4.

Relative input importance of the input variables used in the ANN model.

for the contractor because it implies that the structure is not approved although it fulfills the requirements. 4.2 Support vector machine models To develop a model based on SVM for regression or support vector regression (SVR), the determination of two parameters is essential: kernel function and parameter C. Kernel functions add nonlinearity to the SVM. The parameter C, a positive constant, controls the tradeoff between complexity of the classification function and the number of inseparable patterns. A higher C corresponds to assign a higher penalty to errors. The parameter C has to be selected by the user. This is mostly done using K-fold cross validation. We chose for the radial basis kernel function with the power 2. The optimal value for C was 10000000, and for ε 10. The trained SVR model had an RMSE of 132.6 and an r-squared of 0.999. The RMSE of the test set amounted 180.75 with an r-squared of 0.999. Figure 5 is the box plot of the output of the trained SVR model and the actual output (taken from dataset). The plot has produced a box and whisker plot. The box has lines at the lower quartile, median, and upper quartile values. A quartile is any of three values (lower quartile, median, upper quartile) which divide the sorted dataset into four equal parts. The whiskers are lines extending from each end of the box to show the extent of the rest of the data. Outliers are data with values beyond the ends of the whiskers, which are indicated with ‘+’. (McGill et al., 1978). Figure 5 shows that SVR predicts E2 for values other than 1500 [MPa] with a very low error. Road engineering experts were very pleased with these results because the accuracy of the predictions was much higher than was obtained by using ANN. 5

VALIDATION OF THE ANN REGRESSION MODEL

In spite of the fact that the ANN regression model was not considered to be the best one, it was decided to test the predictive capabilities of the model using a completely different data set. As one can observe from Table 1, the original dataset consisted of pavement structures of which the thickness and stiffness of the layers were varied in a rather systematic way. In fact only 6 different values for the stiffness of the base were considered. The question was how well the model could predict the stiffness of the base course for pavement structures with layer thickness and stiffness combinations that differ from the combinations shown in Table 1. In order to determine how well the model would predict the stiffness of the base 639

Figure 5.

Scatter plot of the testing set using support vector regression.

Figure 6.

Comparison between actual and predicted E2 values (three layer system).

course, the deflection profiles of 100 additional structures were calculated using the BISAR PC software. In Figure 6, the actual E2 values used in the BISAR calculations are compared to the E2 values predicted with the ANN regression model. One can observe that a remarkable good fit between the actual and predicted values was obtained. Based on this result, the conclusion was drawn that although the ANN regression model was initially rated as “not as good”, it still is capable of giving very good predictions of the stiffness of the cement treated base course. A similar check of the SV regression model still has to be performed but is expected to give at least similar results. 640

6

CONCLUSIONS

From the results of the models, the following conclusions have been drawn: 1. AI techniques have proven to be powerful tools to predict layer stiffness of the CTB in typical Dutch pavement structure using the measured deflection profile and total pavement thickness as input. 2. The Support vector machine regression has proven to produce even better results than artificial neural network regression. 3. Extra validation of ANN regression model showed that in spite of the lower performance of the ANN regression model, this model is capable of accurately predicting the stiffness of cement treated base courses. 4. The models could be used in contractual situations. 5. The models can be used purely based on non-destructively measurements (FWD and radar). REFERENCES Abdallah, I., Ferregut, C. & Nazarian, S. 1998. Nondestructive Integrity Evaluation of Pavements Using Artificial Neural Networks. In 1998 First International Conference on New Information Technologies for Decision Making in Civil Engineering. Montreal, Canada, 539–550. Abdallah, I., Ferregut, C., Nazarian, S. & Melchor-Lucero, O. 1999a. Prediction of Remaining Life of Flexible Pavements with Artificial Neural Networks Models. Nondestructive Testing of Pavements and Backcalculation of Moduli: Third Volume. Abdallah, I., Nazarian, S., Melchor-Lucero, O. & Ferregut, C. 1999b. Validation of Remaining Life Models Using Texas Mobile Load Simulator. In 1999 First Accelerated Pavement Testing Conference. University of Nevada, Reno. Bredenhann, S.J. & van de Ven., M.F.C. 2004. Application of Artificial Neural Networks in the Backcalculation of Flexible Pavement Layer Moduli from Deflection Measurements. In Proceedings of the 8th Conference on Asphalt Pavements for Southern Africa (CAPSA 2004). Sun City, South Africa. Burges, C.J.C. 1996. Simplified support vector decision rules. In Saitta, L. ed. The Thirteenth International Conference on Machine Learning. Bari, Italy: Morgan Kaufman, 71–77. Burges, C.J.C. 1998. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery, 2, 115–224. Ceylan, H., Gopalakrishnan, K. & Guclu, A. 2007. Nonlinear Pavement Analysis Using Artificial Neural Network Based Stress-Dependent Models. In Transportation Research Board 86th Annual Meeting, 2007. Washington DC: Transportation Research Board. Ceylan, H., Tutumluer, E. & Barenberg, E.J. 1998. Artificial Neural Networks As Design Tools in Concrete Airfield Pavement Design. In Proceedings of the International Air Transportation Conference, 1998. Austin, Texas. Ceylan, H., Tutumluer, E. & Barenberg, E.J. 1999. Artificial Neural Network Analyses of Concrete Airfield Pavements Serving the Boeing B-777 Aircraft. Transportation Research Record 1684, 110–117. Engelbrecht, A.P. 2007. Computational Intelligence: An Introduction. Wiley. Guclu, A. & Ceylan, H. 2007. Condition Assessment of Composite Pavement Systems Using NeuralNetwork-Based Rapid Backcalculation Algorithms. Transportation Research Board 86th Annual Meeting. Haykin, S. 1999. Neural Networks: A Comprehensive Foundation. New Jersey: Prentice Hall. Hecht-Nielsen, R. 1990. Neurocomputing. Addison-Wesley. Khazanovich, L. & Roesler, J. 1997. DIPLOBACK: A Neural-Networks—Based Backcalculation Program for Composite Pavements. Transportation Research Record No. 1570, 143–150. Kim, Y. & Kim R.Y. 1998. Prediction of Layer Moduli from Falling Weight Deflectometer and Surface Wave Measurements Using Artificial Neural Network. Transportation Research Record 1639, 53–61. Loizos, A., Georgiou, P. & Plati, C. 2007. Assessment of Asphalt Pavement Remaining Life using Artificial Neural Network Modelling. In Loizos, A., et al. eds. 2007 Advanced Characterisation of Pavement and Soil Engineering Materials. 993–1002. McGill, R., Tukey, J.W. & Larsen, W.A. 1978. Variations of Boxplots. The American Statistician, 32, 12–16.

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Meier, R.W., Alexander, D.R. & Freeman, R.B. 1997. Using Artificial Neural Networks As A Forward Approach to Backcalculation. Transportation Research Record 1570, 126–133. Meier, R.W. & Rix, G.J. 1994. Backcalculation of Flexible Pavement Moduli Using Artificial Neural Networks. Transportation Research Record No. 1448, 75–82. Meier, R.W. & Rix, G.J. 1995. Backcalculation of Flexible Pavement Moduli from Dynamic Deflection Basins Using Artificial Neural Networks. Transportation Research Record No. 1473, 72–81. Minsky, M. 1986. The Society of Mind. New York, USA: Simon and Schuster. Osuna, E. & Girosi, F. 1998. Reducing the run-time complexity of support vector machines. In International Conference on Pattern Recognition. Rakesh, N., Jain, A.K., Reddy, M.A. & Reddy, K.S. 2006. Artificial neural networks—genetic algorithm based model for backcalculation of pavement layer moduli. International Journal of Pavement Engineering, 7(3), 221–230. Saltan, M. & Sezgin, H. 2007. Hybrid neural network and finite element modeling of sub-base layer material properties in flexible pavements. Materials & Design, 28(5), 1725–1730. Saltan, M. & Terzi, S. 2007. Modeling deflection basin using artificial neural networks with crossvalidation technique in backcalculating flexible pavement layer moduli. Advances in Engineering Software, In Press. Terzi, S., Saltan, M. & Yildirim, T. 2003. Optimization of The Deflection Basin By Genetic Algorithm And Neural Network Approach. Lecture Notes in Computer Science, LNCS 2714. van Gurp, C.A.P.M. & Wennink, P.M. 1997. Design of pavement structures for rural roads (in Dutch). Apeldoorn, the Netherlands: KOAC-WMD. Vapnik, V.N. 1995. The Nature of Statistical Learning Theory. New York: Springer—Verlag. Vapnik, V.N. 1998. Statistical Learning Theory. New York: Wiley.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Bearing capacity assessment of recycled asphalt pavements V. Papavasiliou Laboratory of Highway Engineering (NTUA), Athens, Greece

A. Loizos National Technical University of Athens (NTUA), Athens, Greece

ABSTRACT: Full-depth cold in place recycling technology was used for the rehabilitation of a heavily trafficked highway asphalt pavement. For the evaluation of the bearing capacity of the foamed asphalt treated recycled pavement, the NTUA Laboratory of Highway Engineering undertook research on the subject, including continuous monitoring of the pavement performance through detailed analysis. The trial field investigation was based primarily on non-destructive tests using the falling weight deflectometer (FWD) along several trial subsections of a rehabilitated pavement. According to the data analysis, the FWD was proven a useful tool for reliable assessment of the bearing capacity of recycled pavement. Deflection indicators give useful information about the structural condition of the recycled pavement, but more precise results are drawn with backanalysis and strain response analysis of the in-situ collected data. The distress in the body of the recycled layer is lower than expected, indicating adequate bearing capacity of the recycled pavement. 1

INTRODUCTION

Cold full-depth recycling is an advantageous rehabilitation technique, since it is eminently suited for the reworking of the upper layers of distressed pavements to depths up to 30 cm. There are multiple reasons why this process has gained wide acceptance in the road pavement industry, including economic, technical and environmental advantages over alternative road rehabilitation options (PIARC 2001). Benefits of cold recycling have been widely publicized, among others by Jenkins et al. (1995). The foamed asphalt technique offers multiple advantages, including the ability to re-open the rehabilitated road to traffic shortly after construction, lowered construction costs in comparison to other standard methods of rehabilitation and the ability to effectively use marginal aggregates in pavement layers. In international literature there is sufficient information about laboratory tests for the estimation of the performance and the bearing capacity of the recycled material. However, insufficient information is available concerning in-situ estimation of the bearing capacity of the recycled asphalt pavement using non-destructive tests (NDT) including the falling weight deflectometer (FWD) technique. For this reason, a field experiment on a rehabilitated pavement of a heavily trafficked Greek highway using the foamed asphalt technique was undertaken by the Laboratory of Highway Engineering of the National Technical University of Athens (NTUA). The aim of the experiment is to investigate whether the implementation of simple NDT can be a useful tool for the assessment of the bearing capacity of a recycled asphalt pavement. 2

BACKGROUND

In order to assess the bearing capacity of a recycled pavement, a trial section was constructed, comprised of six trial sub-sections. The foamed asphalt in depth recycling technique (Fig. 1) was used for the rehabilitation of the above mentioned trial sub-sections with semi-rigid 643

Figure 1.

Implementation of the cold in depth recycling technique using foamed asphalt.

40 mm asphalt surface course (AC surface) 50 mm asphalt binder course (AC binder)

250 mm foamed asphalt cold recycling material (FA)

Remaining CTB layer Crushed stone drainage layer Subgrade Figure 2.

Recycled pavement structure.

pavement, i.e. a pavement constructed above the subgrade with two layers of cement treated base (CTB), overlaid with asphalt concrete (AC) layer material. The rehabilitated trial subsections were subjected to continuous monitoring by the NTUA. Prior to the implementation of cold recycling, a thorough testing program was performed, as documented by Loizos et al. (2004). Foamed asphalt mix design was undertaken to establish the application rates for foamed asphalt and active filler (cement), to achieve optimal strengths and to determine the strength characteristics for use in the structural design exercise on several different blends of in-situ recovered material. These blends were treated with foamed asphalt using the appropriate laboratory unit and several briquettes were manufactured for tests to determine the indirect tensile strength (ITS), the unconfined compressive strength (UCS), the cohesion (c) and the angle of internal friction (Φ), as well as the determination of the indirect tensile stiffness modulus (ITSM) (ASTM 2004). Details of the mix design blends can be found in 644

(Loizos et al. 2004). A standard mix design of 3% foamed asphalt and 1% cement was used in the recycled material. The decision to introduce 1% cement was based on improvement in the achieved soaked strengths. An analytical rehabilitation design approach was used based both on national and international experience to estimate the structural capacity of each pavement configuration. For the analytical pavement design the stiffness modulus of the AC and the recycled (FA) layers was considered to be 3000 MPa. According to the analytical design with a structural capacity requirement in excess of 10 million 13-ton axle-loads, the pavement structure is described by an asphalt concrete (AC) layer (90 mm thick) and a cold in-place recycled and stabilized with foamed asphalt (FA) layer (250 mm thick). The AC layer was constructed of two courses, a 50 mm binder course and a 40 mm final semi-open graded surface course using polymer modified asphalt. Figure 2 shows the pavement cross-section after rehabilitation. 3

DATA COLLECTION AND ANALYSIS

3.1 In-situ measurements During and after completion of the recycling works at the test section, a comprehensive FWD survey was undertaken. The FWD generates a load pulse by dropping a weight on a damped spring system mounted on a loading plate as shown in Figure 3. The peaks of the vertical deflections were measured at the center of the loading plate and at several radial positions (200, 300, 450, 600, 900, 1200, 1500 and 1800 mm) by a series of 9 deflection sensors. In-situ measurements were conducted on the surface of the recycled layer (FA), on the binder course (AC binder) and finally on the surface course (AC surface) 3 weeks after the rehabilitation work (see Table 1). The post-construction monitoring was comprised of measurements on the surface course approximately 6 months and 1–6 years after construction. Table 1.

Figure 3.

In-situ measurements.

Time since construction

Measurements on

2 days 4 days 3 weeks, 6 months, 1–6 years

Recycled layer (FA) AC binder course AC surface course

Schematic presentation of the FWD sensors instrumentation.

645

All in-situ non-destructive tests were performed on the outer traffic wheel path of the heavily trafficked lane. Six trial sub-sections were investigated: Westbound AK1 (900 m) and AK2 (1200 m) and eastbound KA1 (450 m), KA2 (800 m), KA3 (250 m) and KA4 (600 m). The Ground Penetrating Radar (GPR) system of the Laboratory of Highway Engineering of the NTUA (GSSI 2002) was used for the analysis, with the aim to assess pavement layer thicknesses. This data is useful for backanalysis procedures. The system used, is appropriate for the evaluation of the upper part of the pavement structure, since it produces reliable information to an approximate 0.7 m penetration depth (Al-Qadi et al. 2005). The system follows the principles of ASTM (2005) and is supported by the appropriate software (RoadScanners 2001). A limited number of cores from the asphalt layer as well as from the foamed asphalt recycled layer were extracted at specific FWD test locations, in accordance to a predetermined coring schedule. The cores were used as ground truth data for the validation of the FWD GPR thickness data. 3.2 Backanalysis and strain response analysis A thorough field data analysis was performed including a backanalysis with the aim to verify the robustness of the recycled pavement. The backanalysis was undertaken using ELMOD software (Dynatest 2001). Considering the level of the subgrade at the top of the drainage layer (Fig. 2), the backanalysis model consisted of four layers. The backcalculation was performed using layer thicknesses obtained from GPR analysis. The ELMOD software was also used for the estimation of the horizontal tensile strain (εxx) at the bottom of the recycled layer. Strains were also calculated using pavement design data (Loizos et al. 2004), following the related pavements model of Figure 2. 4

DATA ANALYSIS RESULTS

4.1 Deflection indicators The overall pavement condition of the recycled pavement was determined using internationally accepted indicators (COST-336 1998), which are relevant to the measured elastic deflections. For this purpose, the center (maximum) deflection (D1) was taken into account, which represents the overall pavement performance at the time of the investigation (Hakim et al. 2002). The surface curvature index (SCI) based on the deflection deference was also calculated, for the evaluation of structural condition of the new constructed layers (FA and AC). The in-situ collected data were normalized to the reference temperature of 20ºC (Van Gurp 1995). The results (average values for the measurements until one year after construction) are presented graphically in Figures 4 and 5. Figures 4 and 5 clearly show a decrease of the average maximum deflection D1 and the SCI with time. This is an indication of improvement of the overall pavement structural condition over time (see Figure 4), mainly due to the increase of the bearing capacity of the recycled layer (curing of the FA) and the overlay with AC layers (binder and surface courses) as well (see Figure 5). Significant differences in the average values between the trial sub-sections were observed during the first 3 weeks. This might be due to differences in the curing of the recycled material. Differences between the trial sub-sections were also observed in the rate of decrease of the average D1 and SCI values. This is an indication of different impact of the AC overlays on the structural condition of the recycled trial sub-sections during the early life of the pavement. The average deflection differences SCI values for the measurements 1–6 years after construction presented graphically in Figure 6 show a tendency of reduction or stabilization with time. This is an indication of the structural improvement or stabilization of the upper pavement layers (AC and FA). A tendency of reduction of the differences in the structural condition of the trial sub-sections KA and AK can also be noticed. The level of homogeneity was determined using the coefficient of variation (CV). This parameter is defined as the ratio of the standard deviation over the mean value per sub-section. 646

FA 6 months

400

AC binder 1 year

AC surface

Average max deflection (microns)

350 300 250 200 150 100 50 0 KA1

Figure 4.

KA2

KA3 KA4 Trial section

AK1

AK2

Average maximum deflection (D1, 20ºC).

FA 6 months

300

AC binder 1 year

AC surface

250

Average SCI (microns)

200 150 100 50 0

KA1

Figure 5.

KA2

KA3 KA4 Trial section

AK1

AK2

Average SCI values (20°C).

The CV of the center deflection D1 and the SCI as well for the different monitoring levels ranged from 10% to 30%, indicating good to moderate homogeneity of the structural condition of the recycled pavement (COST-336 1998). The results for the measurements one and six years after construction are presented in Table 2. Six years after construction almost in all trial sub-sections (except KA1) the CV was lower in comparison with the CV one year after construction, indicating stabilization of the deflection indicators values. 647

Table 2.

Coefficient of variation (CV). Trial sub-sections KA1

KA2

KA3

KA4

AK1

AK2

CV (D1) 1 year 6 years

15.8 25.0

11.9 11.3

19.1 15.3

24.8 24.0

30.5 20.0

20.1 16.5

CV (SCI) 1 year 6 years

14.8 22.2

16.3 15.8

27.8 25.5

29.5 23.3

29.5 19.9

32.8 22.8

Average SCI (microns)

30

KA1

KA2

KA3

KA4

AK1

AK2

20

KA2

KA4

AK1

KA1

AK2

KA3

10

0 0

Figure 6.

1

2

3 4 5 Time since construction (years)

6

7

Average SCI graphed with time.

4.2 Backanalysis results The most recent (6 years after construction) in-situ collected deflection data were backanalyzed in order to estimate the modulus of the AC and the recycled material (FA) and to compare with the modulus that was taken into account during the pavement design. The average temperature of the bituminous overlay during the measurements ranged between 22 and 26ºC. These temperature values allow comparison between the moduli without further correction of the results. The minimum, average and maximum backcalculated values are presented graphically in Figures 7–8. It can be seen, that six years after construction the minimum backcalculated moduli of the AC and FA layers were higher than the related pavement design values, indicating adequate bearing capacity of the recycled pavement. 4.3 Strain response analysis Following the backanalyzed data during the most recent monitoring (6 years after construction), the horizontal tensile strain (εxx) was calculated at the bottom of the recycled layer. The max εxx was also calculated using pavement design data (Loizos et al. 2004) following the related pavements model of Figure 5. The calculations were conducted using linear elastic analysis software (BISAR 1998). A 40 kN single wheel load was used, with a 15 cm radius. 648

25000

Min

Aver

Max

AC modulus (MPa)

20000

15000

10000

5000

design

0

KA1

KA2

KA3

KA4

AK1

AK2

Test section

Figure 7.

Backanalysis results (AC, 6 years).

25000

Min

Aver

Max

FA modulus (MPa)

20000

15000

10000

5000

design

0

KA1

KA2

KA3

KA4

AK1

AK2

Test section

Figure 8.

Backanalysis results (FA, 6 years).

The in-situ max εxx for every sub-section was compared with the relative one using the design data. The results presented in Figure 9 show that the maximum tensile strain at the bottom of the recycled layer was much lower than the relative strain based on the design data. According to these results, the distress in the body of the recycled layer is lower than expected and consequently the bearing capacity of the recycled pavement is adequate. 5

CONCLUSIONS

In the present research study an effort was made to investigate whether the implementation of simple NDT can be a useful tool for the assessment of the bearing capacity of a recycled asphalt pavement. The major findings and discussion points are the following: The analysis taking into account the FWD deflection indicators (center deflection, surface curvature index) gives useful information about the overall pavement structural condition 649

70 design

60

Tensile strain (microns)

50 40 30 20 10 0 KA1

KA2

KA3

KA4

AK1

AK2

Test section

Figure 9.

Maximum tensile strain (recycled layer).

of the pavement. It can also show differences between several sub-sections, but not enough information is available in regards to the bearing capacity of the recycled pavement. The backcalculated moduli of the AC and the recycled layer (in comparison with the related pavement design values), can give more useful information about the structural adequacy of the recycled pavement. However, a better concept for obtaining useful in-situ bearing capacity information can be achieved using the backanalysis approach in terms of strain response analysis. The FWD was proven a useful tool for the assessment and comparison of the bearing capacity of recycled asphalt pavements. Deflection indicators give useful information about the structural condition of the recycled pavement, but more precise results are drawn with backanalysis and strain response analysis of the in-situ collected data. ACKNOWLEDGMENTS The authors would like to thank the Greek Ministry of Public Work and the involved organizations for supporting the research work of this study. REFERENCES Al-Qadi, I.L., Lahouar, S., McGhee, K.K. & Mokarem, D. 2005. Accuracy of Ground-Penetrating Radar for Estimating Rigid and Flexible Pavement Layer Thicknesses. Transportation Research Record: Journal of the Transportation Research Board, No. 1940: 69–78. Washington, D.C. ASTM D4123-82, 2004. Standard Test Method for Indirect Tension Test for Resilient Modulus of Bituminous Mixtures, American Society of Testing and Materials, Pennsylvania. ASTM D4748, 2005. Standard Test Method for Determining the Thickness of Bound Pavement Layers Using Short-Pulse Radar, Non-destructive Testing of Pavement Structures, American Society of Testing and Materials. Pennsylvania. BISAR User Manual. 1998. Hibbitt, Bitumen Business Group. COST-336. 1998. Guidelines for Evaluation of Flexible Pavements at Project Level Using Falling Weight Deflectometer. Final Report, European Commission. Brussels. Dynatest. 2001. ELMOD: Pavement Evaluation Manual.

650

GSSI, 2002. RADAN for Windows NT (Version 4.0), User’s Manual, Geophysical Survey Systems Inc., North Salem, New Hampshire. Hakim, B.A., Brown, S.F. & Armitage, R.J. 2002. Pavement Evaluation and Strengthening Design: Sixteen Years Experience. Proceedings, 9th International Conference on Asphalt Pavements, ISAP. 3: 1–12. Copenhagen. Jenkins, K.J., Lindsay, R.L. & Rossmann, D.R. 1995. The Deep In Situ Stabilization Process: Case Study. Annual Traffic Convention (ATC.) Pavement Engineering, I 3A: 1–13, Pretoria. Loizos, A., Collins, D. & Jenkins, K. 2004. Rehabilitation of a Major Greek Highway by Recycling/ Stabilizing with Foamed Bitumen. Proceedings, 8th Conference on Asphalt Pavements for Southern Africa (CAPSA 04): 119–126. South Africa. Loulizi, A., Al-Qadi, I.L. & Lahouar, S. 2003. Optimization of Ground Penetrating Radar to Predict Layer Thicknesses in Flexible Pavements. Journal of Transportation Engineering, Vol. 129, No. 1: 93–99. PIARC, 2001. Recycling of Existing Flexible Pavements. Technical Committee on Road Pavements, C7/8, World Road Association. RoadScanners, 2001. Use of Ground Penetrating Radar in Relation with FWD. Road Doctor Software, Version 1.1 User’s Guide, Rovaniemi, Finland. Van Gurp, C. 1995. Seasonal Influence on Asphalt Pavements with the Use of Falling Weight Deflectometers. PhD Thesis. Delft, The Netherlands.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Dynamic analysis of non-destructive tests W.T. van Bijsterveld & R.L. Álvarez Loranca Geotecnia y Cimientos S.A. GEOCISA, Coslada, Madrid, Spain

ABSTRACT: The use of static backcalculation procedures for the interpretation of Falling Weight Deflectometer (FWD) measurement results is commonly accepted. However, to obtain accurate results, it is necessary to know the structure of the pavement in detail, which often requires coring, thereby annulling the essence of nondestructive testing. Also, the current backcalculation procedures are not accurate in predicting the properties of surface layers, especially in semi-rigid pavements. This paper describes the research activities initiated by GEOCISA to improve the pavement analysis procedures for non-destructive tests. In the first place the load and displacement histories obtained from FWD tests were analyzed in order to establish a dynamic characterization procedure of the data. Extensive dynamic finite element analyses were carried out to model and simulate the dynamic behavior of the pavement during a FWD test. Secondly a study has been carried out into the application of seismic measurements to obtain additional information regarding the surface layers. 1

INTRODUCTION

The use of the Falling Weight Deflectometer (FWD) for pavement auscultation in Spain is widely spread. Although the current standards for pavement management and rehabilitation design are based on the main deflection only, i.e. the deflection measured directly under the loading area, there is an increasing interest in exploiting the additional information the FWD-measurements provide. As is known, the FWD consists of at least 7 geophones at distances up to 2.5 m from the load center, measuring surface deflections caused by the impact of the falling weight. The first step in optimizing the use of the FWD data is the use of backcalculation software to determine the young’s modulus of the different layers of the pavement structure. The input for this software is the maximum deflection measured at each geophone and the thickness of the layers. In an iterative process the software performs multilayer calculations with assumed values for the young’s moduli, in order to reproduce the deflections measured by the FWD. Although in many cases this procedure yields reasonable results, there is a number of practical problems and theoretical shortcomings to the method. To begin with the practical problem, the layer thicknesses of the pavement are unknown in most of the situations. It is therefore necessary to drill cores from the road, thereby annulling the essence of nondestructive testing, or to perform additional measurements with for example ground penetrating radar (GPR). In the second place, the backcalculation methods work well for flexible pavements where the stiffness moduli gradually decrease with increasing depth and the differences in material stiffnesses between the layers is limited. In Spain however, there are many semi-rigid pavements with a firm cement-treated base (CTB) and a relatively thin bituminous overlay. In this case, small deviations in the layer thickness or modulus of the CTB, results into large variations in the bituminous overlay. On a more fundamental and theoretical level, it has been remarked by several authors (e.g. Al-Khoury et al. 2001) that the backcalculation procedure uses static linear-elastic models, whereas the nature of the FWD test is clearly dynamic. This dissimilarity can most clearly be observed in Figure 1 where actual deflection profiles at several moments in time are shown next to the deflection bowl that would be the input for the backcalculation procedure. 653

Dynamic deflection profiles 1000 time in ms

deflection [mm].

800 600 400

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

Max

200 0 –200 0

300

600

900

1200

1500

distance to load center [mm]

Figure 1. Deflection profiles at different time intervals and the enveloped curve of maximum deflections.

From this figure it becomes clear that the deflection bowl used in the iterative calculation is in fact an enveloped curve, which in reality does not exist at any time. The latest generations of the Dynatest FWD equipment in use by GEOCISA allows the recording of the full time history of the deflections, recording data every 0.05 ms, so that the dynamic characteristics of the tests are available for analysis. On the other hand, increasing computer power and availability of user friendly finite element software, makes dynamic analysis of pavement structures possible within a reasonable time (15 to 20 minutes on a desktop computer, 3 GHz CPU, 1 Gb RAM). It is for these reasons that a procedure was established to analyze the dynamic data from the FWD measurements. Also, dynamic finite element analyses of the FWD test have been performed, in order to build a database for the calibration of dynamic backcalculation methods. Simultaneously, additional non-destructive measurements were investigated for its complementarily to FWD measurements, providing additional information on the properties of the surface layers. This paper describes the research activities summarized above. 2

CHARACTERISATION OF THE FWD LOAD AND DEFLECTION DATA

The load imposed on the pavement by the FWD is generated by means of a weight falling on rubber buffers. Depending on the desired load level, e.g. 50 kN, the total weight and the drop height can be adjusted. The load level is the only adjustment criterion available in the equipment, whereas the pulse duration and shape are inherent properties of the buffers and the pavement itself. The Dynatest deflectometers are designed to generate a pulse with duration of approximately 25 to 30 ms, although the actual pulse shape and duration may vary with the type of equipment (HWD or FWD, see Figure 2) and, as mentioned before, with the pavement properties. In dynamic analyses the time factor is of high relevance and therefore a routine has been developed to perform a dynamic characterization of the load pulse. For this purpose a selection of the indicators proposed by van Gurp (1995) was utilized. First of all, a threshold for the load level is established at 5% of the maximum value to determine the start and the end of the load signal. Once defined the start and end of the signal, the following indicators can be calculated: − the total pulse duration; defined as the time between the 5% threshold of the up going signal and the down going signal. 654

Load characteristics FWD vs HWD 70

FWD

60

normalized load [kN]

HWD 50 40 30 20 10 0 –10 0

5

10

15

20

25

30

35

40

45

50

time [ms]

Figure 2.

Load characteristics of High weight deflectometer versus standard FWD.

In-time force and deflection measurements 1400

70

D2

1000 deflection [μm]

60

D1

50

D3

800

40

D4 D5

600

30

D6 D7

400

20

Force

200

10

0

Applied Force [kN]

1200

0

‒200

‒10 0

10

20

30 time [ms]

40

50

60

Figure 3. Typical representation of force and deflection data in time obtained with a FWD on a flexible pavement.

− the time elapsed till the maximum force level; determined as the time elapsed between the start of the test and the maximum force level. In some cases there appears an irregularity in the pulse shape, having a local maximum before reaching the absolute maximum. In this case the absolute maximum is taken. − the time elapsed till the maximum force level, determined as the time elapsed between the lower threshold and the maximum force level. − the total energy of the pulse; defined as the surface under the time-force diagram between the 5% thresholds as defined before. − the energy of the pulse until the maximum force. 655

The same type of analysis is applied at each of the deflection curves (see Figure 3), although in this case the main interest is in the time at which the maximum deflection occurs, since this provides information on the velocity of the wave propagation. The physical meaning of the other indicators is not as clear and relevant as is the case with the force shape, especially since the force is an important input in the finite element analysis of the test. 3

FINITE ELEMENT MODELING OF THE FWD TEST

3.1 Geometry modeling For the first experimental modeling of the FWD test, two pavement sections of an accelerated pavement testing facility in El Goloso, Spain were modeled. The first section consists of 120 mm of asphalt mixture on 300 mm of cement stabilized soil. This section has a deflection of approximately 0.3 mm under a 65 kN load. The second section consists of 120 mm of asphalt mixture on 600 mm of unbound granular material. This section has a deflection of approximately 1 mm under a 65 kN load. Due to the simplicity of the geometry, the test can be modeled in a 2D axi-symetric environment, thereby significantly reducing the number of degrees of freedom, compared to a full 3D model. This makes it possible to have a model large enough to reduce disturbing boundary effects to a minimum and on the other hand to have a sufficient level of detail to ensure a proper discretization of the load wave. As a standard procedure, first of all a static linear-elastic analysis of a wheel load with the FE model is compared to the results of a commonly accepted multi-layer program, such as Alize-LCPC or Everstress to check if the model size and boundary conditions are adequate. 3.2 Dynamic load modeling The characteristics of the load input for the dynamic analysis determine the number of time steps needed to obtain numerical stability. Sudden changes in the load level, as can be observed in Figure 2, are complicated to model and require a smaller time step. For reasons of simplicity a harmonic pulse load is defined as in Equation 1 to model the load. ⎛ π ⎞ F (t ) = F0 sin2 ⎜ (t − ϕ ) ⎟ ⎝T ⎠

(1)

where F0 is the amplitude, T the pulse duration and ϕ the phase shift. These parameters are adjusted in order to obtain the best possible fit with the loads actually measured during the execution of the test. The indicators described in section 2 of this paper are used to obtain the best possible fit, rather than commonly used least square methods on the actual shape of the curve. 3.3 Damping parameters The dynamic analysis brings along the need for some additional parameters compared to static analyses. The first and easiest parameter to obtain is the density of the material. In static analyses the proper weight of the materials is insignificant compared to the magnitude of a wheel load. However in dynamic analyses, where accelerations are taken into account, it is necessary for the assembly of the mass matrix. Next it is required to determine the damping parameters of the system. The finite element program used for this analysis incorporates the Rayleigh damping parameters α and β. A procedure proposed by Chowdhury et al. (2003) was utilized to make a first estimation of the damping parameters. The parameters α and β are established in order to obtain an overall damping between 2% and 7% for the frequencies between the lowest Eigen frequency of the system and an upper limit established by the user (see Figure 4). The damping ratio level between 2% and 7% is considered appropriate for geotechnical structures. 656

Damping parameter determination 10% 9%

ξ1

Damping rate [%]

8%

ξ2

ξ1+ξ2

7% 6% 5% 4% 3% 2% 1% 0% 0

10

20

30

40

50

60

Frecuency [Hz] Figure 4.

Diagram for damping parameter determination.

Results of Dynamic Simulation of FWD test 0

deflection [mm]

‒0.1

‒0.2

0 300 450 600 900 1200 1500 1800 2100 max

‒0.3

‒0.4

‒0.5

‒0.6 0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

time [ms] Figure 5.

4

Results of the dynamic analysis of the FWD test.

ANALYSIS RESULTS

The output from the FE analysis is obtained in the same format as the data from the FWD equipment. A typical result from one of the first analyses is presented in Figure 5. Since the aim of the study is to create a database with dynamic analysis results of various types of 657

pavements, with a range of different moduli per material type, it becomes clear that there is a need to characterize the results in a more efficient way. For this reason an additional curve is drawn through the maximum values of the curves “recorded by the geophones.” This curve contains information on the maximum deflections, as well as the time elapsed between the subsequent maximums.

Characteristic curves for section 2

maximum deflection [mm]

–0.1

–0.2

–0.3

–0.4

–0.5

–0.6

E1 = 6000; E2 = 1000

E1 = 6000; E2 = 500

E1 = 6000; E2 = 800

E1 = 6000; E2 = 2000

E1 = 5000; E2 = 1000

E1 = 5000; E2 = 500

E1 = 5000; E2 = 800

E1 = 5000; E2 = 2000

E1 = 8000; E2 = 1000

E1 = 8000; E2 = 500

E1 = 8000; E2 = 800

E1 = 8000; E2 = 2000

E1 = 10000; E2 = 1000

E1 = 10000; E2 = 500

E1 = 10000; E2 = 800

E1 = 10000; E2 = 2000

–0.7 17

19

21

23

25

27

29

31

33

35

time [ms] Figure 6.

Characteristic curves for section 2.

Calibration FEM vs FWD field data 0.2

deflection [mm]

0 –0.2

FEM 0 FEM 300

–0.4

FEM 450 FEM 600

–0.6

FWD 0 –0.8

FWD 300 FWD 450

–1 –1.2 0.00

FWD 600

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

time [ms] Figure 7. Representation of field measurements vs finite element results (damping parameters α and β: 2.7% and 7% resp).

658

In the next step, the FE computations are repeated, changing the material properties of the top two layers. For each of these layers 4 different young’s moduli are assumed, resulting in 16 different cases. For each of these cases the characteristic curve is determined and displayed in Figure 6, where E1 and E2 represent the young’s modulus in MPa of the two upmost layers. The aim is to build up a reference database with characteristic curves for the most common sections for roads in Spain, based on the instructions for design issued by the Ministry of Public works. 5

CALIBRATION OF THE DYNAMIC MODEL

Before extending the simulations a calibration trial was carried out to verify whether the results of the FEM analysis do correspond to the actual field data. As the initial results were rather poor, a further refinement of the load modeling and the damping parameters was carried out. The graph in Figure 7 represents the best result obtained after various iterations for the four “geophones” closest to the loading area. It became clear that an accurate representation of the load shape is highly relevant. For this reason the harmonic pulse shape will have to be abandoned and replaced by the actual pulse shape. Currently, more field data are being collected in order to establish accurate damping parameters and an appropriate pulse shape model, depending on the pavement type and material properties. The hypothesis under investigation is that a correlation exists between the damping parameters and the ratio of load level and maximum deflection. Also the surface curvature or similar indices may correlate with the damping parameters. 6

ADDITIONAL SEISMIC MEASURING METHODS

Parallel to the research described in the previous paragraphs, the application of seismic measuring techniques has been investigated in order to resolve the shortcomings of the FWD test in determining the characteristics of the surface layers. Although the young’s modulus of the surface layer is not of high relevance in bearing capacity determination, the evolution of it in time may provide information on the ageing, the susceptibility to top-down cracking and/or the structural integrity (cracking). Seismic techniques or Spectral Analysis of Surface Waves (SASW) have been described extensively in literature (e.g. Nazarian, et al. 2002, Abdallah et al. 2001). The research activities in this project focused on the selection of the appropriate load signal and the equipment (accelerometers, data acquisition equipment and software), given the intended field of application. Considering the widespread use of FWD measurements, the seismic technique should be additional and non-restrictive to the current FWD measurement procedure. The current status of the research has lead to the compilation of a first prototype which is used for calibration measurements. Seismic measurements are carried out and compared to conventional laboratory methods for the determination of the dynamic modulus. For the moment, the (interim) conclusion from the calibration measurements is that the relation between the seismic and conventional measurements is different for every bituminous mixture investigated (Norambuena, 2008). This would convert the seismic method into an additional independent measurement which can be used to monitor its evolution in time. However, the intended use for obtaining more accurate information for the backcalculation of the Young’s moduli of the pavement material is still beyond reach. 7

CONCLUSIONS AND RECOMMENDATIONS

The dynamic nature of the falling weight deflectometer test provides a source of time dependent information which is ignored in traditional backcalculation methods. The dynamic computational methods however, require additional material and system parameters. It will 659

require experience and an important process of model calibration before the method becomes operable in daily practice. However, the authors believe that the current computer power and availability of user-friendly FEM software obliges pavement engineers to exploit the existing techniques to the fullest to improve the understanding of (dynamic) pavement behavior. Seismic measurements provide a way to measure stiffness characteristics of surface layers. However, the interoperability with the falling weight deflectometer and the integration in young’s modulus backcalculation procedures is still a matter for further research. ACKNOWLEDGEMENTS The research described in this paper was co-financed by the Spanish Ministry of Industry, Tourism and Trade through its program for the promotion of technological research (PROFIT 2007). REFERENCES Abdallah, et al. 2001. Integrating seismic and deflection methods to estimate pavement moduli. Center for Highway Materials Research, University of Texas, El Paso, USA. Al-Khoury, R. et al. 2001. Spectral element technique for efficient parameter identification of layered media. I. Forward calculation. International Journal of Solids and Structures 38: 1605–23. Chowdhury, I. & Dasgupta, S.P. 2003. Computation of Rayleigh Damping Coefficients for Large Systems. Electronic Journal of Geotechnical Engineering. Vol 8, Bundle C, Technical Note. Nazarian, S. et al. 2002. Quality management of flexible pavement layers with seismic methods. Center for Highway Materials Research, University of Texas, El Paso, USA. van Gurp, C.A.P.M. 1995. Characterization of seasonal influences on asphalt pavements with the use of falling weight deflectometers. Ph.D. Thesis, Delft University of Technology, Delft, The Netherlands. Norambuena Contreras, J. & Castro Fresno, D. (2008). Final Report on Dynamic Analysis of Road Pavements (ALADIN)—in Spanish. University of Cantabria, Santander, Spain.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Automated pavement thickness evaluation for FWD backcalculation K.R. Maser, L.A. McGrath & B.C. Miller Infrasense, Inc., Arlington, MA, USA

H. Ceylan Iowa State University, Ames, IA, USA

G. Sanati Foundation Mechanics, Inc., El Segundo, CA, USA

ABSTRACT: Knowledge of the bound pavement layer thickness is important in obtaining accurate back-calculated layer moduli, since small deviations between assumed and actual layer thickness produce large differences in back-calculated moduli. This paper describes the development and application of a fully automated system for analyzing the GPR data. The system searches out the FWD analysis location in GPR thickness data, identifies the significant layers, chooses the layer boundary that most likely represents the bottom of the bound material, and reports the depth to this boundary. The user can plot these bound layer thickness results for a series of FWD tests, check consistency in the selected layer structure, and, where indicated, select alternate layer thickness choices for those locations that appear to be out of pattern. The paper describes the methodology employed in this system, and the results of the evaluations that have been carried out to date. 1

INTRODUCTION

Falling Weight Deflectometer (FWD) data, combined with known pavement layer thickness, is routinely used to obtain the “in-situ” resilient elastic moduli of a pavement structure. This moduli information is used in a structural analysis to determine the bearing capacity, estimate expected life, and calculate overlay requirements over a desired design life. A key element in the successful analysis of FWD data is the knowledge of the pavement layer thickness. With most FWD evaluations, pavement layer thickness is estimated based on construction plans and occasional cores. However, pavement thickness can vary significantly from these assumed values, and small errors in the assumed asphalt thickness can result in large errors in back-calculated moduli of the asphalt and base layer (Briggs et al., 1991). Figure 1 illustrates this effect. A prediction error shown in Figure 1 was computed from the value of the predicted layer properties using the given FWD deflection basin, the correct layer thickness, and various deviations from the correct layer thickness (inputted into ILLI-PAVE to generate deflection basins). The back-calculation procedure was carried out using an Artificial Neural Network methodology for matching a database of calculated deflection basins to that provided by the FWD (Ceylan et al., 2007). As seen in Figure 1, the thickness errors significantly influence the predicted asphalt concrete (AC), base, and subgrade layer properties. Ground penetrating radar provides a means for obtaining accurate layer thickness data at FWD tests locations. The initial application of this technique to pavements (Maser & Scullion, 1992a) established the ability and accuracy of measuring the thickness of bound AC and unbound aggregate base layers, and for distinguishing the thickness of individual AC layers within the pavement structure (Maser & Scullion, 1992b). GPR application to measurement 661

Modulus prediction error, %

300 250

ACC Modulus

200

Base layer K

150

Subgrade ERi

100 50 0 –50

–100

–80

–60

–40

–100 –20 0 20 40 Asphalt thickness error, %

60

80

100

Figure 1. Influence of AC thickness estimation error on backcalculated moduli (based on a 20-cm, 8-in. thick pavement).

Figure 2.

Combined GPR/FWD test vehicle (photo courtesy of foundation mechanics, Inc.).

of pavement thickness has since become a subject of ongoing study and evaluations, and GPR has become a well established technology for pavement thickness evaluation. The level of accuracy in the GPR thickness measurement depends on the type of pavement structure and on the degree of calibration used. The differences between GPR thickness values and pavement core thickness values have generally ranged from 2–10% (Maser, 1999; Wenzlick et al., 1999; Al Qadi et al., 2005). The variation is typically lowest for newer pavement, and highest for old pavement. The use of calibration cores helps to improve the accuracy of GPR, and studies that have used this calibration generally have more accurate correlation with core data (Maser, 2003; Al Qadi et al., 2005). GPR has already been used in conjunction with FWD data on a number of projects. For example, the Oklahoma DOT recently conducted statewide FWD/GPR surveys for pavement management purposes. In this project (Williams et al., 2006) GPR data were analyzed at FWD test locations over 3500 lane-miles to provide back-calculation information at a network level. The GPR data was collected independently of the FWD testing, and the FWD data locations in the GPR files were identified using GPS coordinates collected during FWD testing. Other agencies are using systems that combine both GPR and FWD units, so that the data is collected concurrently. An example of such a system is shown in Figure 2. 662

distance

pavement surface

asphalt base

(a) Simple GPR pavement structure data

asphalt p base

(b) GPR pavement structure data with layers “picked”

bottom of asphalt base

(c) GPR pavement structure data with multiple AC layers

asphalt

asphalt asphalt or base

(d) GPR pavement structure data with unclear layer interpretation Time (depth) Figure 3.

Sample GPR pavement data with processing.

One problem with the use of GPR is that the analysis of the GPR data requires specialized expertise, and can be time consuming. There are various computer programs available to assist with this process. Figure 3 illustrates a sample of GPR data along with the required processing. The data analyst must observe the significant layers in the data; “pick” these layers (see Figure 3b, 3c), and identify the type of material (AC, granular base) that the layer represents. Once the layer is picked, the software automatically follows the layer for a specified distance until the analyst must repeat the picking. While the picking aspects of GPR processing are fairly straightforward, the interpretation of layer material type can sometimes be complex. Figures 3a and 3b represents a straightforward interpretation, while Figures 3c 663

and 3d are more complex. Often there are multiple layers, and it is not always clear which layer represents the boundary between bound and unbound material. 2

AUTOMATION OF GPR PROCESSING

Given the interpretive aspects of GPR data processing discussed above, in general it is not possible to fully automate the processing of this data. Maser & Vandre (2006), for example, have demonstrated that automated processing can be carried out on a network level, as long as it is understood that the interpretation of layer types may require correction at a future date. For FWD application, however, knowing the depth of the bound pavement is critical to backcalculation, and therefore this information must be available. One advantage of the FWD application is that backcalculation can provide a reality check on the GPR data. If the GPR data yields alternate values of bound layer thickness (see Figure 2d), and the initial choice yields an unreasonable surface layer modulus, then a correction can be made using an alternative value. This logic has been implemented in an automated analysis procedure, as discussed below. 2.1 Analysis of GPR sections The GPR data collection process used in this work employs a combined GPR/FWD system as shown in Figure 2. At each FWD test point, a short section (∼50 feet) of GPR data is collected. Since the GPR antenna is a fixed distance in front of the FWD equipment, the FWD test location is always at a fixed location from the end of each GPR file. Figure 4a shows a series of these short GPR files, one each for each FWD test. An algorithm has been developed to cycle through a list of these files, locate the significant layer boundaries in each file, and calculate the layer thicknesses. The algorithm applies a two-step procedure for each GPR data file. In the first step, statistical measures are used to find the most significant GPR waveform peaks in a prescribed region around the FWD test point. In the second step, these peaks are “tracked” much like a GPR analyst would do manually. Statistics are then computed for the amplitude and arrival time of each tracked layer, and a layer indicator, calculated from these statistics, is used to determine which of the layers is the most likely candidate for the bottom of the bound pavement. The indicator is designed to be a maximum for the most likely layer. If multiple layers are detected, the algorithm reports alternative candidate values in the order of their likelihood. Figure 4b shows the results of the automated processing of the files of Figure 4a. Note that in addition to locating the correct layer, the automated processing has tracked “layers”

Table 1.

Sample output of automated processing. AC thickness (in)

DONE

1st

2nd

3rd

Quality index

Data DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN DUG\Auburn\AUBURN

7.95 8.67 8.60 9.61 9.56 9.09 7.90 8.45 8.77

#N/A #N/A #N/A #N/A #N/A #N/A 4.52 #N/A #N/A

#N/A #N/A #N/A #N/A #N/A #N/A 13.74 #N/A #N/A

GOOD GOOD GOOD GOOD GOOD GOOD AVERAGE GOOD GOOD

664

top of pavement

bottom of AC (a) Series of GPR files at FWD locations before auto-processing

(b) Series of GPR files at FWD locations after auto-processing Figure 4.

Automated processing of GPR files collected at FWD locations.

in the GPR data that an analyst would generally ignore. Nevertheless, for each of the layers identified in each file, a layer indicator is calculated, and the layer with the maximum indicator value is reported as the asphalt thickness. If other layers exceed a prescribed threshold, they are reported as alternate candidates. Table 1 shows the output for the analysis carried out on the Figure 3 data. The automated analysis was implemented as a macro in Excel, and the output appears in spreadsheet format. Note from the table that the true AC bottom is always reported as the 1st choice, and, for the most part, no other choices are offered (#N/A = no choice). This is because the data interpretation is very clear. The quality index in the right column of Table 1 is an indicator of the clarity of the layer choice. For the Figure 4 data, the choice is generally very clear, and so the quality index is generally “good”. 2.2 Analysis of multi-layered data As indicated earlier, automating the data analysis becomes more challenging when there are multiple pavement layers, since the program then has to decide which layer boundary is the bottom of the bound (AC) material. This decision, while often obvious to an analyst, may be less obvious to an automated program. Figure 5a shows a set of GPR files with multiple layers, and Figure 5b shows the result of the automated processing. Note that the automated processing captures the bottom of the asphalt, along with other layers in the data. The results of the analysis are plotted in Figure 6. In the figure, the diamonds, squares, and triangles represent the order of likelihood for the choice of the bound pavement thickness. The predominant choice for the bottom of the asphalt is the bottom of the second layer, and this layer is selected as the first choice in 9 of the 13 tests. Based on the observation of this pattern, the analyst can modify the result by instructing the program to make the second layer the first choice. The choices can then be re-ordered automatically, and the final result is shown in Figure 6.

665

bottom of base

bottom of AC

(a) Series of GPR files at FWD locations before auto-processing

(b) Series of GPR files at FWD locations after auto-processing Figure 5.

Automated processing of multi-layer GPR files collected at FWD locations. File Number

Thickness (in.)

1

2

3

4

5

6

7

8

9

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00

Figure 6.

10

11

12

13

12

13

1st Choice 2nd Choice 3rd Choice

Results of automated processing from figure 4b.

File Number

Thickness (in.)

1

2

3

4

5

6

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00

Figure 7.

7

8

9

10

11

1st Choice 2nd Choice 3rd Choice

Adjusted results of automated processing.

666

CONCLUSIONS This paper presented a method for automating the calculation of bound pavement layer thickness using GPR data collected in conjunction with FWD testing. The method has been implemented using an automated processing algorithm and software, and has been demonstrated for specific sections of pavement. When a single bound pavement layer appears in the GPR data, the automated analysis is straightforward and the results are self-sufficient. When multiple layers appear in the GPR data, the method identifies the most likely pavement thickness value, and also reports alternative values. By plotting the automated results, the analyst can determine where these alternate values might be more appropriate than the first choice, and can make the appropriate corrections. REFERENCES Al-Qadi, I.L., Lahouar, S., Jiang, K., McGhee, K. & Mokarem, D. 2005. “Validation of ground penetration radar accuracy for estimating pavement layer thicknesses”, Paper No. 05-2341, Proceedings, Transportation Research Board 84th annual meeting, 9–13 January 2005, Washington, DC. ASTM D 4748-98. 1998. “Standard test method for determining the thickness of bound pavement layers using short-pulse radar”, Annual book of ASTM standards, American Society for Testing and Materials, March, 1998. Briggs, R.C., Scullion, T., and Maser, K.R. 1991. “Asphalt thickness variation on Texas SHRP sections and effect on backcalculated moduli” Symposium on NDT and Backcalculation, Nashville, TN, August 1991, Nashville, TN. Ceylan, H., Guclu, A., Bayrak, M.B., and Gopalakrishnan, K. 2007. Nondestructive evaluation of Iowa pavements-phase I, Center for Transportation Research and Education, Iowa State University, Ames, IA. http://www.ctre.iastate.edu/reports/nde-pavements.pdf Maser, K.R. 1999. “Pavement characterization using ground penetrating radar: state of the art and current practice”, Nondestructive testing of pavements and backcalculation of moduli: third volume, ASTM STP 1375, American Society for Testing and Materials, West Conshohocken, PA, 1999. Maser, K.R. 2003. “Non-destructive measurement of pavement layer thickness”, Report FHWA/CA/ OR-2003/03 prepared for the California Department of Transportation, April, 2003. Maser, K.R. and Vandre, B. 2006. “Network-level pavement structure assessment using automated processing of ground penetrating radar (GPR) data” Proceedings of the 2006 Airfield and Highway Pavement Specialty Conference, Atlanta, GA April 30–May 3, 2006. Wenzlick, J., Scullion, T. and Maser, K.R. 1999. “High accuracy pavement thickness measurement using ground penetrating radar”, Report No. RDT 99–003, Missouri Dept. of Transportation, February, 1999. Williams, R., Martin, T., Maser, K.R. and McGovern, G. 2006. “Evaluation of network-level groundpenetrating radar effectiveness,” Paper No. 06–2243, CD-ROM, Transportation Research Board 85th Annual Meeting, 11–15 January 2004, Washington, DC.

667

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Analysis of FWD data and characterization of airfield pavement materials in New Mexico M.U. Ahmed, R. Bisht & R.A. Tarefder The University of New Mexico, Albuquerque, New Mexico, USA

ABSTRACT: This paper describes in detail the laboratory and field evaluation of runways at two airports: Double Eagle II at Albuquerque and Sierra Blanca at Ruidoso, New Mexico. Field skid resistance test, Falling Weight Deflectometer (FWD) test, and coring are carried out. Cores and soil samples are collected and tested in the laboratory. The CBR values and the skid numbers were compared to the tables in Advisory Circulars 150/5320-6D and 150/5320-12C to make an assessment. The modulus values from FWD data are presented in a 2D contour plot to determine the distress area of each runway. The structural health of the pavement of runway 17-35 at Double Eagle II airport is in a good condition while runway 4-22 of the same airport is not in good condition based on the resilient modulus and CBR values. As for Sierra Blanca airport, runway 6-24 is in a good condition while the surface of the runway 12-30 needs attention. 1

INTRODUCTION

Rehabilitating airfield pavements in poor condition can be up to three times more expensive than rehabilitating pavements in good condition (USGAO 1998). Timely maintenance can prolong major maintenance works and reduce the overall cost over time. The United States General Accounting Office (USGAO) recommended that the FAA improve the existing runway condition information to create a database for forecasting anticipated needs. The idea of creating a runway condition database is helpful to ensure that the airports are funded in a timely manner to reduce the cost in the long run. Well aligned with the USGAO recommendation, the research presented herein is a part of the second phase of the on-going airfield pavement evaluation effort by the New Mexico Department of Transportation—Aviation Division (NMDOT-AD). The objective is to analyze the FWD data, and to characterizes asphalt core from surface and underlying base, subbase, and subgrade materials through laboratory testing and engineering analysis. The major goal is to generate airfield pavement and subgrade strength data to populate the New Mexico airfield pavement database and subsequent analyses to gain a comprehensive view of an airfield’s remaining life as well as past performance. This is a multi-year contract to assess a total of 47 airports, about 10 airports per year. In New Mexico, there are about 57 airports and the runway pavements of these airports have not been evaluated for their structural capacity for more than 20 years. Federal Aviation Administration (FAA) has initiated this project to evaluate 10 of these airfield pavements this year. These 10 airports were selected based on the surface condition survey (Lucero 2008). This study focuses on the structural health of the pavements. The runways of two airports are evaluated using field and laboratory tests. This paper discusses data from only two airports each with two runways; however they suffice the purpose of this study. The first airport evaluated is Double Eagle II, which is located on the northwest side of Albuquerque, New Mexico at an elevation of 5837 feet. It has two asphalt paved runways: 4-22 and 17-35. The other airport conducted is Sierra Blanca Regional Airport located 15 miles northeast of Ruidoso, New Mexico and about 175 miles southeast of Albuquerque at an altitude of 6814 feet. It also has two asphalt paved runways: 6-24 and 12-30. 669

Figure 1.

Distress of runway 4-22 at Double Eagle.

The functional conditions of the pavements were surveyed last year. The outcome of the survey is a Pavement Condition Index (PCI), which is a numerical rating of the pavements. The ratings range from 0 to 100, with 0 being the worst possible condition and 100 being the best possible condition. The PCI of runway 4-22 is 54 (see Figure 1). The PCI for 17-35 is 99 as it was rehabilitated just last year. The PCI of Sierra Blanca airport pavements are in the range of 45-50. Thus these airports have deteriorated surface conditions. It is necessary to determine the structural capacity of these airfield pavements except runway 17-35. However, runway 17-35 is selected for FWD test in the evaluation plan for the completeness of database and also to compare old versus new pavement conditions. This study conducted field tests which includes the skid resistance test, FWD test, and coring. Laboratory tests include the determination of the index properties of base and subgrade materials. Skid resistance test is conducted to determine if the pavement surface provided enough friction to prevent skidding without compromising riding quality. The FWD test is carried out for the determination of the Young’s modulus (elastic) of different layers of the pavements. Laboratory soil testing is performed to determine the CBR value of the base and subgrade material. Subgrade CBR value is an important factor to determine rutting or permanent deformation of a airfield pavement. Ulukaya et al. (2003) studied excessive rutting on a section of taxiway at Sacramento International airport. The rutting problem persisted despite the fact that this section was milled and resurfaced several times. Ulukaya et al. (2003) investigation revealed that the subgrade was in a wet condition with a low CBR value of 3. Instability rutting was also observed in the asphalt concrete layers. The stiffness of the rutted pavement on the wheel paths was half of the stiffness of the non rutted area outside the wheel paths. Garg et al. (2004) have analyzed the different procedures and models of airfield pavement design. These authors pointed out that different maintenance and rehabilitation criteria may be appropriate for each individual airport and the FAA’s present structural design procedures are adequate. They have also pointed out that there is a need for improvement in the construction and material standards for flexible pavements. McQueen et al. (2008) carried out a study at the Federal Aviation Administration’s National Airport Pavement Test Facility using Heavy Weight Deflectometer (HWD) and FWD. They used the FAA’s backcalculation software for data analysis. Their study reported that pavement stiffness and backcalculated subgrade moduli are independent of FWD and HWD force amplitudes. Chitrapu et al. (2002) performed a study on the effect of subgrade nonlinearity and the presence of a stiff layer at a shallow depth on the backcalculated resilient moduli. These authors studied eight different projects in Kansas. They analyzed the FWD data using EVERCALC modulus backcalculation software. They also determined the resilient modulus according to the AASHTO Design Guide (1993). They observed that there 670

was a difference in the resilient modulus from the AASHTO Design Guide algorithms and EVERCALC when the depth to the stiff layer is less than 2.54 m (100 in.). The difference is negligible at a deeper depth. The difference is mainly because AASHTO algorithm does not consider the effect of the stiff layer. 2

OBJECTIVES AND SCOPE

The main objective of this study is to evaluate the structural health of airfield pavements. The scope of this study is to determine the structural health based on field and laboratory testing of airfield pavement materials. Two airports each with two runway pavements are presented. Specific of objectives of this study are to: • Evaluate pavement structural capacity based on the coring, FWD, and skid resistance data. In particular, collect and analyze the FWD data for quantitive evaluation of the strength of runway pavements. Using the appropriate backcalculation program, obtain the modulus at the current damage level for in-service runway pavements. • Assess pavement subgrade strength through parameters such as soil classification, particle size distribution, and Atterberg limits in the laboratory. Determine the relationship between subgrade CBR and backcalculated modulus values for airfield pavements in New Mexico. 3

FIELD TESTING

As mentioned previously, three tests are conducted in the field. These are surface friction test, FWD test, and field coring. A short description of these tests is given below: 3.1 FWD test In a FWD test, an impulse load is applied by dropping a weight (ball) on the pavement and the resulting deflections are measured at specified distances from the point of load application by the sensors. These sensors are geophones. The number of load applications is called the drop number and the number of drops can be adjusted according to the requirements. Three weights or loads 40, 53.4, and 71.2 kN (9, 12, and 16 kips) are applied in this study. The responses are measured using seven sensors spaced at 0, 20.3, 30.5, 45.7, 61.0, 91.4, and 152.4 cm (0, 8, 12, 18, 24, 36 and 60 in.) from the point of impact. After obtaining the deflections, the elastic moduli of the different layers are determined by backcalculation. Finally, the contour plots of those values show the overall structural capacity of the airfield pavement based on the stiffness evaluation of each layer. 3.2 Field coring Coring and drilling operations are carried out in locations to cover an entire runway. For example, the coring locations for Runway 4-22 are shown in the Figure 2. Asphalt cores of 10.2 cm (4 in.) diameter are collected and pavement thickness is determined in the field from the core thickness. Drilling was carried out in the core locations up to a depth of 152.4 cm (5 ft) using a 25.4-cm (10-in.) auger to collect base and subgrade soils. Samples were collected from each layer of soil based on change in the soil type or texture. Visual classification of the soil samples is performed. 3.3 Surface friction test Surface friction test was carried out to evaluate the roughness characteristics of the surface, which is a required criterion for safety against skidding. Friction largely depends on the texture of the surface aggregates. The texture of surface aggregate is classified into two 671

Runway centerline

@ 200 ft c/c up to L/4 L = 7400 ft

@ 400 ft c/c up to L/2

@ 200 ft c/c up to L/4

Station 0 + 00

Test direction

10 ft 20 ft 50 ft Figure 2.

Coring plan for Double Eagle airport runway 4-22 (1 ft = 30.48 cm).

categories. One is micro texture, which depends on the roughness of an individual particle, and the other is macro texture, which depend on the overall arrangements of the particles. The aggregates on the surface are polished gradually due to the rubbing action of the tires. Eventually the pavement surface becomes smooth and slippery. Skid number (SN) is used for evaluating the surface friction. The SN value is measured directly from the surface friction tester. Surface friction tester is a vehicle with a trailer attached to it. The vehicle was driven at 40 mph. During the measurement of SN value, water is sprayed on the left wheel and the wheel is locked at a certain intervals. The wheel is allowed to skid for a distance of 54.9 m (180 ft), and SN is calculated based on fundamental law of physics. Skid number is defined as the ratio in percent of the frictional force and the weight of a moving body. SN = μ × 100 % =

F × 100% W

(1)

where F is the friction force and W is the weight. 4

LABORATORY TESTING

Laboratory testing includes particle size analysis and determination of the Atterberg limits and soil classification. Soil samples are tested in the laboratory in accordance with ASTM D 2487-00 and ASTM D 422-63. Atterberg limit tests followed the ASTM D 4318-00. Coring was not performed on runways 17-35 and 6-24 because these runways were built just a couple of years ago and they are in good condition. From the results of the laboratory tests, the California Bearing Ratio (CBR) was determined using the empirical correlations shown below (MEPDG, 2008): CBR = 28.09(D60 )0.358 CBR =

75 1 + 0.728(P200 )( PI ) 672

for PI = 0 for PI > 0

(2) (3)

where PI is the plasticity index and P200 is % soils finer than 0.075 mm size. D60 is the sieve size through which 60% soils pass. 5

RESULTS AND DISCUSSION

5.1 FWD data analysis The FWD data are analyzed using BAKFAA software. In backcalculation, surface deflections are calculated by assuming trial values of modulus of elasticity of different layers of the pavement. Next, the calculated values are compared to the deflection values measured in the field. When the deviation between the field deflections and calculated deflections is minimized, the trial modulus values are considered as the modulus of the layers of the pavement. In this software, pavement layer thickness and Poisson’s ratio are given as inputs. The field deflection values are loaded into the software in a predefined file format. The spacing of the sensors is entered. Then a trial set of modulus values are supplied. The iteration is done until the root mean square (RMS) of the deviation of the field deflection and the calculated deflection is minimized. Table 1.

Typical modulus values and ranges for paving materials.

Material

Low value ksi (MPa)

Typical value ksi (MPa)

High value ksi (MPa)

Asphalt concrete Portland cement concrete Lean-concrete base Asphalt-treated base Cement-treated base Granular base Granular subbase Stabilized soil Cohesive soil

70 (483) 1,000 (6,895) 1,000 (6,895) 100 (689) 200 (1,379) 10 (69) 5 (34) 10 (69) 3 (21)

500 (3,447) 5,000 (34,474) 2,000 (13,790) 500 (3,447) 750 (5,171) 30 (207) 15 (103) 50 (345) 7 (48)

2,000 (13,790) 9,000 (62,053) 3,000 (20,684) 1,500 (10,342) 2,000 (13,790) 50 (345) 30 (207) 200 (1,379) 25 (172)

Table 2. Mean and range of modulus values in runway 4-22 (1 ft = 30.48 cm; 1 kip = 4.45 kN; 1 ksi = 6.89 MPa). Location

Layer

EBL 5 ft. from center

Surface

EBL 20 ft. from center

Surface

EBL 40 ft. from center

Surface

WBL 5 ft. from center

Surface

WBL 20 ft. from center

Surface

WBL 40 ft. from center

Surface

Load (kip)

Mean (ksi)

Std. Dev. (ksi) Range (ksi)

9 12 16 9 12 16 9 12 16 9 12 16 9 12 16 9 12 16

302.96 529.82 521.52 336.54 442.64 437.71 329.70 418.16 345.36 484.15 528.52 515.50 483.06 482.86 439.46 348.19 255.12 222.93

138.72 429.13 375.22 189.70 297.01 336.64 254.74 394.29 352.33 318.29 412.89 401.53 412.42 538.04 496.29 165.82 198.68 209.61

673

441.69–164.24 958.95–100.68 896.74–146.29 526.24–146.84 739.66–145.63 774.35–101.06 584.45–74.95 812.45–23.87 697.69 802.44–165.86 941.41–115.62 917.03–113.96 895.48–70.64 1020.90 935.75 514.02–182.37 453.81–56.43 432.54–13.31

Table 1 shows typical modulus values and ranges for paving materials according to FAA guideline (AC No.: 150/5370-11A). The calculated values are compared with the values in Table 6 and discussed below for each runway. Runway 4-22: For the surface, the modulus values along east bound lane 40 ft. from the centerline (EBL 40 ft), west bound lane 6.1 m (20 ft) from the centerline (WBL 6.1 m or 20 ft) and WBL 12.2 m (40 ft) are below the minimum value for asphalt concrete. These are shown in Table 2. Due to space limitation in this paper, other tables are not listed in this paper. For the base course, the values along EBL 1.5 m (5 ft), EBL 12.2 m (40 ft) and WBL 1.5 m (5 ft) are below the minimum value for base course. Contours are drawn for different layers of the pavement to identify the weak areas. The lowest values of modulus are represented by dark blue. The values increase as the color changes from light blue to orange, and the highest values are represented by red. Figure 3

× 10

5

psi

7000 10

9

6000

8 WBL

Length (ft)

5000 7

4000

6

5 3000 4 EBL 2000

3

2 1000

1

0

0

10

20

30

40

50

60

70

80

90

100

Width (ft)

Figure 3. Contours of surface course modulus for 40-kN (9-kip) load in 4-22 runway (Double Eagle) (1 ft = 30.48 cm; 1 psi = 6.89 kPa).

674

psi × 10

4

7000 12

6000 10 WBL

Length (ft)

5000

8 4000

6 3000

EBL 4

2000

1000

0

2

0

10

20

30

40

50

60

70

80

90

100

Width (ft)

Figure 4. Contour of base modulus for 40-kN (9-kip) loading in 4-22 runway (Double Eagle) (1 ft = 30.48 cm; 1 psi = 6.89 kPa).

shows the contour of surface modulus values of runway 4-22 for 40-kN (9-kip) loading. This contour plot shows that the eastbound lane is weaker than the westbound lane. Figure 4 shows the contour plot of base modulus values for 40-kN (9-kip) loading. The east end of the runway is weak in comparison to the west end. Figure 5 shows the contours of subgrade modulus values of runway 4-22 for 40-kN (9 kip) loading. Again, it can be seen that the east end of the runway is weak in comparison to the west end. Runway 17-35: The modulus values of all the layers are above the minimum value required value. Runway 6-24: Only the values of base course along WBL 1.5 m (5 ft) and WBL 6.1 m (20 ft) are below the required minimum value for base course. Runway 12-30: Some of the modulus values of base course along SBL 1.5 m (5 ft) fall below the required minimum value 675

× 10 7000

psi

2

1.8

6000

WBL 5000

Length (ft)

4

1.6

SBL

1.4 4000

1.2 3000 1

EBL EBL 2000 0.8

1000 0.6

0

0

10

20

30

40

50

60

70

80

90

100

0.4

Width (ft)

Figure 5. Contour of subgrade modulus for 9 kip loading in 4-22 runway (Double Eagle) (1 ft = 30.48 cm; 1 psi = 6.89 kPa).

for base course. Also, the values of the subgrade modulus along SBL 1.5 m (5 ft) fall below the minimum value for cohesive soil. 5.2 Skid resistance analysis The skid tests are carried out at 1.5 m (5 ft), 6.1 m (20 ft), and 9.1 m (30 ft) on either side of the centerline depending. The measured skid resistance values are compared with the specification values shown in Table 2 (FAA: AC 150/5320-12C) to determine if the existing surface meets the requirements. The average SN at Double Eagle II airport is 55 for runway 4-22 and 60 for runway 17-35. Similarly, at Sierra Blanca airport, the average SN is 54 for runway 6-24 and 42 for runway 12-30. A minimum value of 50 is required (Table 1). Runway 12-30 fails to meet the criteria. All the other runways are close to the maintenance planning value of 60. 676

Table 3.

Friction level classification for runway pavement surfaces. 64 km/h (40 mph )

Tester Mu Meter Dynatest Consulting Inc. Runway Friction Tester Airport Equipment Co. Skiddometer Airport Surface Friction Tester Airport Technology USA Safegate Tester Findlay, Irvine, Ltd. Griptester Friction Meter Tatra Friction Tester Norsemeter RUNAR

96 km/h (60 mph)

Maintenance New design/ Maintenance New design/ Minimum planning Construction Minimum planning Construction 0.42

0.52

0.72

0.26

0.38

0.66

0.50

0.60

0.82

0.41

0.54

0.72

0.50

0.60

0.82

0.34

0.47

0.74

0.50

0.60

0.82

0.34

0.47

0.74

0.50

0.60

0.82

0.34

0.47

0.74

0.43 0.48 0.45

0.53 0.57 0.52

0.74 0.76 0.69

0.24 0.42 0.32

0.36 0.52 0.42

0.64 0.67 0.63

Figure 6. Soil profile of runway 4-22 at Double Eagle II Airport with CBR values (1 in. 25.4 mm). For runway 12-30 at sierra Blanca airport, the base course is mainly well graded gravel (GW) with sand and well graded sand (SW) with gravel. The CBR value ranges from 53 to 64. These values are fair to good for base course. The CBR values for the subgrade are high ranging from 36 to 67 due to high percentage of sand. These values are good to excellent for subgrade.

5.3 Laboratory CBR analysis Bar charts are drawn to show the variation of the CBR values with depth for each borehole and presented in Figure 6 for Double Eagle II airport and Figure 7 for Sierra Blanca airport. For runway 4-22 at Double Eagle airport, the base course is mainly well-graded gravel (GW) with sand or well graded sand (SW) with gravel. The CBR value ranges from 677

Figure 7.

Soil profile of runway 12-30 at Sierra Blanca Airport with CBR values (1 in. = 25.4 mm).

50 to 64. These values are fair to good for base course according to the FAA: AC 150/53206D Part 1 specification. The CBR value for the subgrade ranges from 18 to 22 with only two slightly high values of 26 and 29 mainly due to the high percentage of gravel. These values are fair to good for subgrade. 6

CONCLUSION

• Pavement surface, base, and subgrade conditions were successfully evaluated through the determined backcalculated modulus values. • Subgrade was evaluated based on the CBR value calculated using index properties of soils. REFERENCES Federal Aviation Administration (FAA). 2002. Advisory Circular No. 150/5320-6D, Airport Pavement Design and Evaluation. Advisory Circular No. 150/5320-12C, Measurement, Construction, and Maintenance of Skid-Resistant Airport Pavement Surfaces. Advisory Circular No. 150/5370-11A: Use of Non Destructive Testing in the Eva. of Airport Pavements. United States General Accounting Office (USGAO). 1998. Airfield Pavement: Keeping Nation’s Runways in Good condition Could Require Substantially Higher Spending. Report to the Chairman, Committee on Commerce, Science, and Trans.U.S. Senate, 20548. Ulukaya, M., Reeves, I., Hadipour, K., Maher, M., and McQueen, R. 2003. Excessive Rutting on Taxiway A at Sacramento International Airport: Possible Causes and Remedies. Airfield Pavement Specialty Conference, Las Vegas, Nevada. Garg, N., Guo, E., and McQueen, R. (2004). “Operational Life of Airport Pavements.” Final report to U.S. Department of Transportation, Federal Aviation Administration, Washington, D.C. 20591. McQueen, R.D., Marsey, W., and Arze, J.M. 2000. (Dec. 1, 2008). Chitrapu, S.V., Hossain, M., and Romanoschi, S. 2002. http://pms.nevadadot.com/2002.asp (Nov. 12, 2008). MEPDG Guide. 2008. “Guide for Mechanistic-Empirical design of new and rehabilitated pavement structures”. http://www.trb.org/mepdg/2appendices_cc.pdf (Aug. 25, 2008).

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

SOFTSYS for backcalculation of full-depth asphalt pavement layer moduli O. Pekcan, E. Tutumluer & J. Ghaboussi Department of Civil and Environmental Engineering, University of Illinois Urbana, Illinois, USA

ABSTRACT: This paper describes a computational approach, SOFTSYS, recently developed at the University of Illinois for determining layer properties from nondestructive pavement testing and evaluation. Specifically, it is capable of backcalculating properties of pavement layers using results of the Falling Weight Deflectometer (FWD) test. SOFTSYS is based on a set of algorithms derived from the use of artificial neural networks and genetic algorithms in the field of soft computing. The backcalculation approach considers geomaterial nonlinearity that may seriously affect the overall response. SOFTSYS includes structural models developed for various types of pavements including full-depth asphalt pavements and fulldepth asphalt pavements built on lime stabilized subgrade soils. In this paper, the algorithm of SOFTSYS is introduced and described in detail by solving an example backcalculation problem that uses synthetic FWD data generated from finite element analysis of a full-depth asphalt pavement structure. 1

INTRODUCTION

Evaluating structural condition of existing, in-service pavements constitutes a major part of the annual maintenance and rehabilitation activities undertaken by state highway agencies. The decision strategies for maintenance and rehabilitation of pavements are highly dependent on accurate assessment of pavement layer properties. Nondestructive testing methods are generally used to backcalculate these properties, i.e., the layer moduli. The Falling Weight Deflectometer (FWD) test is one such method that is frequently used and widely accepted to evaluate pavement structural conditions. In this test, pavement deflection basins are gathered by dropping a load over pavement surface and the collected deflections are used to backcalculate pavement layer properties. Since backcalculation requires an inverse analysis, it may not always be easy to obtain reliable results. Therefore, the robustness and effectiveness of the backcalculation methodology is essential in obtaining accurate and reliable pavement layer moduli. In this paper, an innovative methodology, called SOFTSYS, is introduced for interpreting the results of an FWD test. It is a computational method to describe the properties of pavement layers. Using only FWD test results (i.e., deflections) along with the layer thicknesses as inputs, SOFTSYS can calculate all the layer moduli for pavement nondestructive evaluation. To do this, SOFTSYS uses a combination of nontraditional computing tools, such as Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) and a structural analysis model. With quick and robust algorithms used in SOFTSYS, advanced real time evaluation of pavements becomes feasible. For example, verification of as-constructed pavement design parameters such as layer thicknesses in the field is possible. SOFTSYS interprets FWD test results and performs pavement structural analysis based on the Finite Element Method (FEM). FEM performs pavement structural analysis due to applied wheel loading to compute pavement deflections. Unlike the linear elastic theory commonly used in pavement analysis, nonlinear models can be considered in finite element (FE) analysis for characterizing unbound aggregate base and subgrade soil modulus behavior. This accounts for the typical hardening behavior of granular bases and softening nature of 679

fine-grained subgrade soils under increasing stress states. The results of the nonlinear FE approach have been proven to be more consistent with the deflections obtained from FWD tests (Ceylan et al. 2005). Since FEM internally captures the nonlinear material properties to better simulate actual pavement behavior, SOFTSYS approach has an inherent capability of incorporating the nonlinear geomaterial, i.e., aggregate base and subgrade soil, properties. After discussing essentials of FWD testing and the need for nonlinear characterization of pavement geomaterial layers, this paper is aimed to introduce the SOFTSYS approach for backcalculation which consists of the combined hybrid use of ANN and GA soft computing methods. The SOFTSYS approach is then demonstrated for backcalculating layer material properties of a typical Illinois full-depth asphalt pavement. The results obtained from SOFTSYS compares favorably with the synthetic FWD basins generated from FE based pavement analysis. 2

FALLING WEIGHT DEFLECTOMETER SIMULATION

With the recent AASHTO move towards adopting mechanistic based pavement analysis and design concepts and procedures in the US, interpretations of FWD data from routine nondestructive testing currently demands the use of advanced multi-layered and finite element (FE) solutions for proper analyses of pavement structural conditions. This naturally states that any backcalculation technique should properly include the use of accurate numerical modeling. For example, according to Illinois DOT’s mechanistic based pavement design procedure, algorithms based on the ILLI-PAVE FE solutions are used for this evaluation (Thompson 1989). In this study, ILLI-PAVE 2005 FE program, the most recent version of this extensively tested and validated ILLI-PAVE pavement analysis program for over three decades, was used as an advanced structural model for solving deflection profiles and responses of the typical Illinois full-depth pavements (Thompson and Elliott, 1985). ILLI-PAVE uses an axisymmetric stress analysis to model the layered flexible pavement structure. Unlike the linear elastic theory commonly used in pavement analysis, nonlinear resilient modulus characterization models are used in the ILLI-PAVE program to account for typical hardening behavior of base course granular materials and softening nature of fine-grained subgrade soils under increasing stress states. 2.1 Pavement layer modeling Adequately characterizing pavement layer behavior plays a crucial role for an accurate backcalculation of the layer moduli. Accordingly, modeling of full-depth asphalt pavements (FDPs) requires accurate material characterizations for the asphalt concrete and subgrade soil layers. After material shakedown has taken place due to construction loading and early trafficking of the pavements, most of the deformations under a passing truck wheel are recoverable and hence considered resilient or elastic. The resilient modulus (MR), defined by repeated wheel load stress divided by recoverable strain, is therefore the elastic modulus (E) often used to govern flexible pavement layer behavior under traffic loading. Figure 1 shows an FWD test simulation on an FDP. ILLI-PAVE FE solution considers the asphalt concrete (AC) structural layer as linear elastic with layer modulus EAC and Poisson’s Ratio νAC considered for the instant loading during FWD testing. A typical value for νAC is often taken as 0.35. For modeling fine-grained subgrade soils commonly encountered in Illinois, a nonlinear modulus characterization has to be employed since a soft, cohesive subgrade has a major impact on all the responses predicted under traffic loading from mechanistic analysis. Fine-grained subgrade soils exhibit nonlinear behavior when subjected to traffic loading (Thompson and Robnett 1979). The subgrade stiffness characterized by the resilient modulus (MR) is usually expressed as a function of the applied the deviator stress through nonlinear resilient modulus response models. These models can be developed based on the results of repeated load triaxial tests used to evaluate resilient properties of fine-grained 680

Figure 1. Pavement layer properties and critical pavement responses indicated for a Falling Weight Deflectometer loading simulation on full-depth asphalt pavements.

Figure 2.

Bilinear model for fine-grained subgrade soils (Thompson and Robnett, 1979).

soils (AASHTO-T307-99. 2000). The bilinear arithmetic model proposed by Thompson and Robnett (1979) simply captures the stress-softening modulus-deviator stress relationship, as shown in Figure 2. The upper limit deviator stress in the bilinear model, σdul, is dependent on the breakpoint modulus, ERi, which is also a function of the unconfined compressive strength, Qu, expressed by Equation 1 (Thompson and Robnett 1979). ERi is a characteristic property of the fine-grained soil often computed for Illinois soils at a breakpoint deviator stress σdi of 6 psi. The corresponding values and parameters of the bilinear model used in the analyses are also given in Figure 2.

σ dul ⋅ 6.895( kPa ) = Qu ⋅ 6.895( kPa ) = 681

ERI ⋅ 6.895(MPa ) − 0.86 0.307

(1)

2.2 Finite element mesh Pavement FE modeling was performed in this study using an axisymmetric mesh for all pavement sections considered. Using ILLI-PAVE FE program, FWD tests on flexible pavements were modeled with the standard 40-kN equivalent single axle loading applied as uniform pressure of 552 kPa over a circular area of 152-mm radius. The FE mesh was selected according to the uniform spacing option of the FWD sensors as follows: 0 mm, 305 mm, 610 mm, 915 mm away from the center of the FWD plate. The surface deflections corresponding to the locations of these FWD sensors were abbreviated as D0, D12, D24 and D36, respectively. Deflections from outside sensors such as D48, D60 and D72 (see Figure 1) were also specified for future studies to backcalculate moduli of pavements with more than two layers. In general, finer mesh spacing was used in the loaded area with the horizontal spacing adjusted according to the locations of the geophones used in FWD tests. In addition to the deflections, the critical pavement responses, i.e., horizontal strain at the bottom of AC layer (εAC), vertical strain at the top of the subgrade (εSG), and the vertical deviator stress on top of the subgrade (σDEV) directly at the centerline of the FWD loading, also shown in Figure 1, were extracted from ILLI-PAVE results to evaluate effects of FWD loading. 3

SOFTSYS AND SOFT COMPUTING METHODS

SOFTSYS, Soft Computing Based Geomaterial and Pavement System Analyzer, is a computational methodology based on novel artificial intelligence techniques to backcalculate modulus values of the pavement layers. SOFTSYS can also evaluate a pavement’s structural adequacy in real time. It is a hybrid algorithm that combines three different techniques namely, Genetic Algorithms, Artificial Neural Networks, and nonlinear FEM. Each component performs certain tasks in order to run SOFTSYS at a desirable reliability, accuracy, and speed. It is an algorithm that uses a combination of GAs and ANNs as to guarantee that the proposed methodology becomes robust, quick, and imprecision tolerant (Ghaboussi 2001). 3.1 Artificial neural networks In the field of transportation geotechnics, ANNs are most often implemented as powerful regression tools. For example, they were successfully used for pavement layer backcalculation by Ceylan et al. (2005), Meier & Rix (1995) and Pekcan et al. (2006; 2008a). Previous studies also showed that ANNs were powerful and quite effective as forward analysis tools to replace or mimic advanced pavement analyses (Ceylan et al. 1999; Meier et al. 1997; Pekcan et al. 2007; 2008b). In these studies, effects of nonlinear geomaterial modulus characterizations on critical pavement responses were also successfully modeled using ANNs. In SOFTSYS, ANNs are used as quick and precise pavement structural analysis tools for the prediction of pavement deflection profiles. Training of ANNs is accomplished based on the results of nonlinear FE analyses of pavements. Any sophisticated FE program solution can be implemented in SOFTSYS. It can analyze any flexible pavement geometry, i.e., fulldepth and conventional flexible pavements, due to an applied static loading. For the sake of providing results, ILLI-PAVE FE software was selected herein for solving deflection profiles and responses. First, broad range of input parameters of the pavement layers (layer moduli and thicknesses) were created in a database (see Table 1). Then, randomly selected combinations of the parameters were inputted into ILLI-PAVE. Analyses were conducted for the simulation of FWD tests, as previously discussed. Multi-layered, feed-forward backpropagation type ANNs (Haykin 1999; Wythoff 1993) were trained to capture the nonlinear relationships between the aforementioned input parameters and output variables (deflections) of ILLI-PAVE. The developed ANN model was used for computing pavement surface deflections based on the known pavement layer moduli and thicknesses. 682

3.2 Genetic algorithms GAs are computational models based on natural evolution (Goldberg 1989; Holland 1975). They are powerful optimization and search methods. GA methodology is highly robust and imprecision tolerant. In GAs, a system is represented by binary strings (i.e., genotype), which encodes the real values of parameters of the system (i.e., phenotype). A population with initial random parameters is used. Population members get better and better to satisfy the fitness criteria through number of generations. This is performed using the operators inspired by the nature such as competition, fitness based selection, crossover, and mutation. The results are not necessarily exact, instead, are accurate to a certain degree of approximation (Ghaboussi 2001). Table 1.

Geometries and material properties of full-depth asphalt pavements analyzed.

Material type

Thickness (mm)

Material model

Modulus (MPa)

Poisson’s ratio

Asphalt Concrete (AC)

127–610

Linear elastic

690–13 800

0.35

Fine Grained Subgrade (SG)

(7620- tAC)

Nonlinear bilinear model

6.9–96.5

0.45

Obtain Deflections from Falling Weight Deflectometer Testing Initialize Population of Full-Depth Pavement Parameters Randomly Run Artificial Neural Network Model & Extract Deflections

Evaluate Fitness Function

Apply Genetic Algorithm Operators

Form the Next Generation Population

Report Pavement Layer Moduli

Figure 3.

SOFTSYS flowchart for pavement layer backcalculation.

683

Genetic algorithms (GAs) have been successfully implemented for the solution of pavement layer backcalculation problem in the past (Fwa et al. 1997; Reddy et al. 2002; Reddy et al. 2004). The contribution of GAs in this study is to efficiently explore the search space formed by nonlinear parameters defined for pavement layers. 3.3 Hybrid methodology In SOFTSYS, GAs work for random search with the operators inspired by the natural evolution. The algorithm is provided in Figure 3. A collection of input parameters within a reasonable range are created randomly to have the database of all possible combinations of pavement layer material properties including material moduli encountered in the pavement. These are then fed into the ANN model as testing data set to compute the corresponding deflection profiles. The testing of all data sets created by GAs is done within a second, which is quite insensitive to number of testing data. GAs, then, sort input data set based on the imposed fitness function calculated using the outputs of ANN results and the deflection profile obtained by FWD testing. Natural evolution operators; selection, crossover, and mutation are then applied to the so called parents and to their offspring to establish the most satisfactory data set for the surface profile obtained from FWD. The major components of GAs are; the genotype/phenotype presentation of parameters of the problem domain (i.e., pavement layer moduli), fitness evaluation (mathematical expression as a measure of the difference between the surface deflections obtained by the FWD test and the ones calculated from ANN model), selection scheme, crossover method, and mutation (Goldberg 1989). The fitness function for the GA is defined in Equation 2. In this equation, DFWD and DANN stand for deflection values obtained from FWD testing and ANN simulations of ILLI-PAVE, respectively. The number “n” is the number of deflectometers used in the FWD testing and simulation, taken as 4 in this paper since the problem size is relatively small. Fitness =

4

1 ( DFWD ,i − DANN ,i )2 1+ ∑ DFWD ,i i =1 n

(2)

SOFTSYS MODEL AND RESULTS

SOFTSYS includes an ANN structural model that was designed in a forward analysis fashion to compute the responses of flexible pavements under a typical FWD loading. Pavement surface deflections were predicted using different geometries and layer properties. The inputs for ANN model were EAC, tAC, and ERi while the outputs were D0, D12, D24, D36. The AC thickness was taken as the design thickness and the corresponding deflections were consistent with the backcalculate moduli values obtained using ILLI-PAVE (Thompson 1989). The ANN model architecture had two hidden layers with more than 30 neurons in each layer. This was according to the findings from similar ANN trainings performed by Ceylan et al. (2005). Although the maximum number of epochs was limited to 10,000 epochs, cross validation was also considered to overcome memorization of the developed model (Reed and Marks 1999). 4.1 Synthetic FWD database ILLI-PAVE FE program was used to create a synthetic FWD database. For a typical FWD loading, the program was executed with random combinations of EAC, tAC, and ERi, the values of which were selected considering the ranges defined in Table 1. To represent the entire range, 12 different stations were analyzed with various thicknesses and pavement layer moduli. The deflection profiles for each run were obtained separately. These profiles were then inputted into SOFTSYS together with their corresponding design thicknesses. The performance of SOFTSYS was then verified by comparing the backcalculated results with the ILLI-PAVE 684

(a) EAC

(b) ERI Figure 4.

SOFTSYS predictions for pavement layer moduli.

inputs of the corresponding deflection profiles. The comparisons for EAC and ERi are made according to the mean absolute percentage errors (MAPEs) of deflection values. MAPE is defined in Equation 3 where the actual values are ILLI-PAVE inputs and the calculated ones are SOFTSYS results. Mean AbsolutePercentageError (MAPE ) = 685

1 n Actuali − Calculated i × 100 ∑ Actuali n i =1

(3)

The estimated results are given Figure 4a–b for EAC and ERi. Note that EAC values calculated for the given synthetic deflection profiles match very accurately with the ILLI-PAVE results with the given MAPE value of 2.0%. Similarly, computed ERi values also show very good matches (MAPE = 2.1%) with the ERi values from ILLI-PAVE. Successful predictions given above prove that SOFTSYS can easily determine the pavement layer moduli for a given FWD deflection profile. It also performs this action in a very quick way. Although the accuracy of backcalculated moduli is limited with the assumptions made when using ILLI-PAVE, the SOFTSYS algorithm is quite robust. Considering these advantages, the potential of this method can be extended beyond estimating pavement layer moduli and towards predicting thicknesses using only FWD deflection data. 5

CONCLUSION

SOFTSYS, Soft Computing Based System Analyzer, is introduced for the solution of backcalculation problem for the pavement layer moduli. SOFTSYS uses a combination of Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs) together with a structural pavement analysis model, such as the Finite Element Method (FEM), to obtain accurate and reliable solutions. SOFTSYS also proved to be robust and quick in the analysis of Falling Weight Deflectometer (FWD) deflection data for backcalculation purposes. The numerical modeling of a full-depth asphalt flexible pavement was done using the nonlinear finite element (FE) program ILLI-PAVE. In SOFTSYS, GAs were used as a searching algorithm for optimal solutions that satisfy the FWD deflection profile, whereas ANNs were used to accelerate the running time of the nonlinear FE program ILLI-PAVE. This way, the SOFTSYS methodology was verified using a synthetic database generated by the ILLI-PAVE FE program. The accurate predictions of the layer moduli computed by SOFTSYS clearly demonstrated the applicability of the methodology. Current and future work in this area is intended to prove the full potential of SOFTSYS approach for determining not only pavement layer moduli but also thicknesses, to be validated in the field by pavement coring and/or ground penetrating radar evaluations. ACKNOWLEDGEMENT/DISCLAIMER This paper is based on the results of ICT-39-2, “NDT Evaluation Using ILLI-PAVE-Based Artificial Neural Networks” research study. ICT-39-2 is conducted in cooperation with the Illinois Department of Transportation, Division of Highways, and the U.S. Department of Transportation, Federal Highway Administration. The contents of this paper reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Illinois Department of Transportation or the Federal Highway Administration. This paper does not constitute a standard, specification, or regulation. REFERENCES AASHTO-T307-99. (2000). “Determining the Resilient Modulus of Soils and Aggregate Materials.” Standard Specifications for Transportation Materials and Methods of Sampling and Testing, AASHTO, Washington, D.C. Ceylan, H., Guclu, A., Tutumluer, E. and Thompson, M.R. (2005). “Backcalculation of full-depth asphalt pavement layer moduli considering nonlinear stress-dependent subgrade behavior.” International Journal of Pavement Engineering, 6(3), 171–182. Ceylan, H., Tutumluer, E. and Barenberg, E.J. (1999). “Artificial neural networks for analyzing concrete airfield pavements serving the Boeing B-777 aircraft.” Transportation Research Record, 1684, 110–117. Fwa, T.F., Tan, C.Y. and W.T., C. (1997). “Backcalculation Analysis of Pavement—Layer Moduli Using Genetic Algorithms.” Transportation Research Record, 1570, 134–142. Ghaboussi, J. (2001). “Biologically inspired soft computing methods in structural mechanics and engineering.” Structural Engineering and Mechanics, 11(5), 485–502.

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Goldberg, D.E. (1989). Genetic algorithms in search, optimization, and machine learning, Addison-Wesley Pub. Co., Reading, Mass. Haykin, S.S. (1999). Neural networks: A Comprehensive Foundation, Prentice Hall, Upper Saddle River, N.J. Holland, J.H. (1975). Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence, University of Michigan Press, Ann Arbor. Meier, R., Alexander, D. and Freeman, R. (1997). “Using Artificial Neural Networks as a Forward Approach to Backcalculation.” Transportation Research Record, 1570, 126–133. Meier, R.W. and Rix, G.J. (1995). “Backcalculation of Flexible Pavement Moduli from Dynamic Deflection Basins using Artificial Neural Networks.” Transportation Research Record, 1473, 72–81. Pekcan, O., Tutumluer, E. and Thompson, M.R. (2006). “Nondestructive flexible pavement evaluation using ILLI-PAVE based artificial neural network models.” American Society of Civil Engineers, Atlanta, GA, United States, 227–232. Pekcan, O., Tutumluer, E. and Thompson, M.R. (2007). “Analyzing Flexible Pavements on LimeStabilized Soils with Artificial Neural Networks.” Advanced Characterisation of Pavement and Soil Engineering Materials: Proceedings of the International Conference on Advanced Characterisation of Pavement and Soil Engineering, Athens, Greece T.S. Andreas Loizos, Imad L Al-Qadi, ed., Taylor & Francis, 587–596. Pekcan, O., Tutumluer, E. and Thompson, M.R. (2008a). “Artificial Neural Network Based Backcalculation of Conventional Flexible Pavements on Lime Stabilized Soils.” Geomechanics in the Emerging Social & Technological Age, 12th International Association for Computer Methods and Advances in Geomechanics, Goa—India, 1647–1654. Pekcan, O., Tutumluer, E. and Thompson, M.R. (2008b). “Quantifying Effects of Lime Stabilized Subgrade on Conventional Flexible Pavement Responses.” Advances in Transportation Geotechnics: 1st International Conference on Transportation Geotechnics, E. Ellis, H.S. Yu, G. Mc Dowell, A. Dawson, and N. Thom, eds., Taylor & Francis, Nottingham, UK, 529–534. Reddy, M.A., Murthy, M.S., S.K., R. and Pandey, B.B. (2002). “Backcalculation of pavement layer moduli using genetic algorithms.” Journal of Highway Research Board, 66, 1–10, Indian Roads Congress, New Delhi. Reddy, M.A., Reddy, K.S. and Pandey, B.B. (2004). “Selection of Genetic Algorithm Parameters for Backcalculation of Pavement Moduli.” International Journal of Pavement Engineering, 5(2), 81–90. Reed, R.D. and Marks, R.J. (1999). Neural smithing: Supervised Learning in Feedforward Artificial Neural Networks, The MIT Press, Cambridge, Mass. Thompson, M.R. (1989). “ILLI-PAVE Based NDT Analysis Procedures.” Nondestructive Testing of Pavements and Backcalculation of Moduli, ASTM—STP 1026, A.J., Bush III and G.Y., Baladi, ed., American Society for Testing and Materials, Philadelphia, 487–501. Thompson, M.R. and Elliott, R.P. (1985). “ILLI-PAVE Based Response Algorithms For Design of Conventional Flexible Pavements.” Transportation Research Record, 1043, 50–57. Thompson, M.R. and Robnett, Q.L. (1979). “Resilient Properties of Subgrade Soils.” Journal of Transportation Engineering ASCE, 105(TE1), 71–89. Wythoff, B.J. (1993). “Backpropagation neural networks. A tutorial.” Chemometrics and Intelligent Laboratory Systems, 18(2), 115–55.

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Deterministic-empirical backcalculation of LWD deflection basins R.N. Stubstad Applied Research Associates, Inc., Sacramento, California, USA

H.C. Korsgaard, K. Olsen & J.P. Pedersen Grontmij—Carl Bro A/S Pavement Consultants, Kolding, Denmark

ABSTRACT: A new method of calculating layered-elastic moduli from Light Weight Deflectometer (LWD) deflection basins is introduced. The suggested procedure is called “Deterministic-Empirical Backcalculation” since it utilizes closed-form solutions to calculate at least two modulus values, or stiffnesses, from LWD load-deflection data on a point-bypoint basis. At least three deflection readings are required at appropriate distances from the LWD loading plate, depending on the structure tested and the diameter (200 or 300 mm) of the plate. Background technical information is provided on the theory behind and the development of the Deterministic-Empirical Backcalculation (acronym—DEB) methodology. 1

INTRODUCTION

A new so-called Deterministic-Empirical Backcalculation (acronym—DEB) method of analyzing Light Weight Deflectometer (LWD) has been developed by the authors of this paper. Stiffnesses, or layered elastic moduli, of the unbound materials are the ultimate results of this recently-developed deterministic-empirical backcalculation process. Using the DEB software (now available for use with the LWD model shown in Figure 1), the following parameters are backcalculated: • The stiffness, or modulus, of any bound upper layer (called Layer #1). Layer 1 should be a relatively thin layer to insure reliable results due to the lower load levels associated with LWD devices vs. the heavier Falling Weight Deflectometer (FWD) load-deflection devices. • The stiffness of any unbound Layer #1 (or Layer #2 if Layer #1 is bound). • The stiffness of the critical, upper portion of the subgrade layer under the loading plate using a modified Hogg model. • The depth to a relatively stiff or unyielding layer beneath the subgrade, based on the shape of the deflection basin. If three unknown pavement layers are involved, with the upper layer being a thin (roughly between ⅓ and ¾ the radius of the loading plate) bound layer, the Dorman-Metcalf relationship is used to calculate the modulus of unbound layer #2, based on the subgrade modulus calculated through the modified Hogg model. To utilize the LWD-based deterministic-empirical backcalculation process, a minimum of three deflection readings must be measured—at the center of the LWD load (assumed to be an evenly distributed load) and at two or more distances from the loading plate. For testing on unbound materials, the loading plate must be 300 mm (or 12 in.) in diameter. When testing on thin bound pavement surfaces, the loading plate may should be 200 mm (or 8 in.), or in some cases 300 mm (or 12 in.) in diameter. LWD deflection sensor offset distances depend on the pavement structure tested. One set of distances are required for testing on unbound materials only while another set is used for testing on a bound (asphaltic or cementitious) upper layer. 689

Figure 1.

The Carl Bro PRIMA 100 light weight deflectometer.

The DEB approach is different from conventional backcalculation in that only closed-form solutions are utilized and neither seed values nor multiple iterations are needed to derive the layered elastic stiffnesses of a pavement system. However—similar to conventional backcalculation—layer thicknesses must be known and all pavement layers must be “elastic” (i.e., no discrete particles with virtually no tensile strength). 2

DETERMINISTIC-EMPIRICAL BACKCALCULATION

Deterministic-Empirical Backcalculation, or “DEB”, was previously developed as part of a Federal Highway Administration (FHWA) study on FWD load-deflection data (Stubstad et al., 2006). However in this initial report, DEB was somewhat confusingly termed “forwardcalculation”. Eventually, this otherwise quite descriptive word caused considerable confusion and even some consternation, since the same term “forwardcalculation” historically referred to deriving deflections, stresses and strains from layer thicknesses, elastic moduli or stiffnesses (used interchangeably herein), and imposed surface loads on the pavement surface. DEB techniques were developed to generate two crucial layered elastic moduli—one for the surface course and one for the upper, and crucial portion, of the subgrade. These two values are derived through the DEB routines which are totally independent of one another, so that the empiricallyderived backcalculated values, even if one of them is somewhat too high or low, will not adversely affect the accuracy of the other. DEB involves the use of certain portions of the LWD deflection basin to derive a modulus or stiffness of the subgrade and the surface course using unique closedform solutions as opposed to an iterative process typically used in backcalculation. The LWD model that was used to generate the field data used to develop the DEB software is shown in Figure 1. As is the case with any backcalculation program, it is recognized that the subgrade modulus generally affects the deflections measured at larger distances from the load while the surface course modulus is primarily a function of the near-load deflections and/or the radius of curvature of the deflection basin—for both parameters along with the center deflection. The advantages of deterministic-empirical backcalculation are as follows: 1. Since the subgrade and surface course stiffnesses obtained are independent of one another, there is a unique solution for each deflection basin. 2. DEB is easy to understand and use whereas backcalculation is more of an art than a science. DEB can be performed by anyone, while traditional backcalculation requires expert engineering judgment along with the “art” of running the iterative software program of choice. This so-called “art form” lies in the evaluation of the reasonableness of the results as well as the proper selection of the models and the other input parameters used in traditional backcalculation. 690

3. The DEB techniques developed for the LWD produce considerably less scatter in point-by-point moduli (for the same layer and test section) than do conventional deflection basin matching techniques. On the other hand, nothing in pavement analysis comes without its drawbacks. As such, these drawbacks are not limited to backcalculation alone, for example: 1. Since the subgrade and surface course stiffnesses are calculated independently of one another, in combination the values obtained may not be perfectly consistent with respect to the total center deflection. 2. To obtain a third, intermediate layer stiffness (if present), such as a granular base sandwiched between a thin upper layer and the subgrade, one could assume that the surface and subgrade stiffnesses are correct and then “fit” the center deflection to the remaining unknown stiffness of, for example, a base course layer. If utilized, however, this approach would suffer from the same drawback as conventional backcalculation—one layer’s modulus is dependent on another layer’s, or layers’, analysis results—which all too often produces spurious results. 3. Accordingly, it is also possible to utilize a modular ratio between the subgrade stiffness calculated through DEB and then apply the modular ratio relationship for unbound base materials developed by Dorman and Metcalf. There is of course no assurance that this is strictly correct; however, one can still apply the test of reasonableness to the results. 4. Since the DEB methodology by its nature produces approximate values, these should only be considered as layered elastic property estimates, for example for quality assurance/ quality control (QA/QC) purposes. 3

THE SUBGRADE MODULUS

One method to ascertain the subgrade stiffness, or elastic modulus, directly under an imposed surface load is through the Hogg model (Hogg, 1944). The Hogg model is based on a hypothetical two-layer system consisting of a relatively thin “plate” or stiff layer on an elastic foundation. The method in effect simplifies the typical multilayered elastic system approach with an equivalent two-layer “stiff layer on elastic foundation” model. Depending on the choice of the deflection values along the deflection basin used to calculate subgrade stiffness, there can in fact be a tendency to either over- or under-estimate the subgrade modulus. Accordingly, the Hogg model utilizes the deflection at the center of the load plus one of the offset deflections. The offset distance where the deflection is approximately one-half of the deflection under the center of the loading plate was shown by Hogg to be quite effective at removing estimation bias. Variations in pavement thickness, the presence of an apparent hard or “stiff ” layer at some depth, and the ratio of the upper layer stiffness to the subgrade stiffness are all taken into account through the Hogg model (actually three different models were developed, depending on the boundary conditions (Stubstad et al., 2006; Hogg, 1944). The Hogg model, in fact, calculates the modulus of the subgrade or foundation support layer directly under the loading plate, not at some arbitrary distance from the load. So the typical subgrade non-linearity is automatically accounted for without reverting to complicated constitutive relationships. Since LWD load-deflection tests are generally performed on unbound materials, it was necessary to modify the Hogg model to fit these data. The Hogg model is described in detail in Stubstad et al. (2006). 4

THE SURFACE COURSE OR UPPER LAYER MODULUS

A viable method to determine the apparent surface course stiffness of the upper-most bound (or relatively stiff) unbound layer under an imposed surface load is, in part, based on the socalled “AREA” approach together with the use of the center deflection reading, as mentioned above. 691

This approach was first introduced in NCHRP Study 20–50 (09) (NCHRP, 2002). Meanwhile, the DEB equations originally suggested have been updated and calibrated for both AC, PCC, and—now in the case of LWD data—also unbound layered elastic surfaces with two different layers (i.e. the foundation support or subgrade layer and the upper unbound layer). Since LWD load-deflection tests are generally performed on unbound materials, it was necessary to modify the DEB models to fit these data. The AREA + center deflection-based surface course model is described in detail in Stubstad et al. (2006). 5

THE INTERMEDIATE LAYER MODULUS (IF PRESENT)

In cases where a relatively thin, bound surface course plus an intermediate base course layer exist, the modulus relationship developed by Dorman and Metcalf between two adjacent layers of unbound materials is used (Dorman et al., 1965). This relationship is shown by Equation 1. EBase = 0.2 ⋅ h20.45 ⋅ ESub

(1)

EBase = Dorman and Metcalf base modulus, MPa, h2 = Thickness of the intermediate base layer, mm, and ESub = Subgrade modulus, MPa.

where:

Although imperfect, it has been found through the LTPP database and discussed in detail in Stubstad et al. (2006) that the Dorman and Metcalf method is far more stable and produces more realistic results than any other form of backcalculation, whether these values are based on traditionally backcalculated values or on DEB-derived values for the subgrade and surface course (if bound). 6

ADVANTAGES OF DETERMINISTIC-EMPIRICAL BACKCALCULATION

The DEB methodology employed in both the LWD and FWD approaches appears to work quite well for typical pavement materials and moduli ratios. As mentioned in the foregoing, this approach is not totally rigorous but is—as the acronym suggests—based on empirical estimates of stiffnesses or moduli. Most importantly, DEB is based on real load-deflection data, not totally blind layered-elastic theory with its assumed perfectly continuous, homogeneous and elastic (whether linear or non-linear) materials. The approach can therefore be used to effectively approximate the stiffnesses of the subgrade and upper layers of a pavement section, for Q/C and comparative or routine testing and analysis purposes, and for deriving the stiffness of any existing unbound, intermediate layer based on the Dorman and Metcalf equation (Dorman et al., 1965). To reiterate, the main advantage of using the DEB approach is that empirical backcalculation techniques together with commonly used deflection-based quantities (such as AREA and the overall center deflection) are employed. Only the composite modulus, or stiffness, of the pavement system, the AREA, and the pavement thickness normalized to the diameter of the loading plate are needed to calculate the relative stiffness of the upper layer in the pavement while the center deflection and one key offset deflection, in addition to the composite modulus of the pavement system, is needed to derive the subgrade modulus. Finally, the intermediate layer modulus (if any) is straight-forwardly based on the subgrade modulus and, accordingly, is much more realistic and stable than intermediate layer moduli based on traditional backcalculation. 7

ARGUMENTS IN FAVOR OF DETERMINISTIC-EMPIRICAL BACKCALCULATION

The main argument for Deterministic-Empirical Backcalculation (DEB) is that this approach—far more often than not—results in both reasonable and believable backcalculated results—for all three pavement surface types (flexible, rigid and unbound) and for both LWD 692

and FWD load-deflection data. Traditional backcalculation, meanwhile, can also result in reasonable results based on FWD testing; however such results are achieved mainly as a result of FWD tests conducted on non-distressed flexible pavements or intact rigid pavements—in other words when there are no discontinuities and—if and only if—all pavement layers behave according to Hook’s law (i.e. elastically, with the same modulus in all directions and depths throughout any layer of material except the subgrade, if non-linear), and when these layers are both homogeneous and laterally continuous. As an example of this, fifteen USA-wide flexible pavement sections from the LTPP database were analyzed using both the DEB technique and traditional backcalculation using an earlier version of the MODCOMP computer program. All comparative subgrade moduli for these 15 test sections, for the same test points and drop heights, are shown in Figure 2. In this graph it can be seen that the two methods of analysis are correlated—but far from identical—for most of these data, and that the overall correlation is not very good (R2 = 0.39). A careful perusal of Figure 2 also reveals that a significant number of backcalculated outliers in fact caused the low r-squared value, and that these outliers are primarily due to backcalculated values that do not follow the overall trend. Note as well the use of a log-log scale, which makes the graph look better then would have been the case with a linear plot and regression analysis. In the plot shown in Figure 2, the Standard Error of the Estimate (SEE) of the regression constant 1.4493 was 1.158—nearly as large as the constant itself! Thus the SEE essentially says the same thing as the low r-squared value—the ability of one backcalculated result to predict the other is far from satisfactory. Meanwhile, the SEE of the exponent 1.0355 is an excellent 0.023, meaning that the exponent (slightly over 1) coupled with the SEE of the exponent shows that a simple linear regression could have been shown instead—except that it would have been impossible to plot all of the data shown in Figure 2 using a simple non-logarithmic plot of the data. Another way to view these data is to examine the overall USA-wide averages and the variability of each set of values. Certainly, variability in subgrade moduli is to be expected, both within sections and from region to region across the continent. In this case, we are examining some 15 different subgrade soils spread across several states and regions within the continental United States with expected and obvious differences. Spatial variability will also occur within any given 160 m test section. On the other hand, one would expect that both the averages and the overall variability for each method should be similar, since they are all based on precisely the same FWD test data, the same sections, and the same exact test points (approx. 20 test points and four load levels Backcalculated vs. DEB Subgrade Moduli for 15 AC Test Sections 10,000

Modulus Relationship

Backcalculated Modulus (MPa)

Power (Modulus Relationship)

1,000

100 y = 1.4493x1.0355 R2 = 0.3905

10 10

1 00

1 ,0 00

1 0, 000

Deterministic-Empirical Backcalculated Modulus (MPa)

Figure 2.

Backcalculated vs. DEB-derived subgrade moduli for 15 LTPP flexible test sections.

693

Table 1. Statistics for backcalculated and DEB-derived subgrade moduli for 15 flexible test sections.

Statistic

Hogg (DEB) subgrade Backcalculated modulus subgrade modulus

Median (MPa): 129 Arithmetic mean (MPa): 150 Std. dev. (MPa): 68 COV (%): 46%

236 320 493 154%

per test section). Table 1 summarizes the basic statistics for the two backcalculation methods employed. Based on the overall results shown in Table 1, it is apparent that the Hogg/DEB model results in a considerably smaller variability in subgrade stiffness (COV = 46%) compared to traditional backcalculation (COV = 154%). Keep in mind as well that some of the subgrade layers utilized by the traditional backcalculation routine (when more than one layer was classified as a subgrade material) were not included in this analysis. The subgrade layers that were not included in Figure 2 and Table 1 were in fact those with the poorest relationship to deterministic-empirical backcalculation. Finally, it should be noted that the median value is probably more indicative of a true USA-wide arithmetic average than the arithmetic means shown, which are artificially increased by a small but significant number of implausibly high modulus values in (especially) the backcalculated LTPP database. As shown in Table 1, the median value of the subgrade moduli from traditional backcalculation was nearly double that from the DEB/Hogg model. 8

SUMMARY AND CONCLUSIONS

A new method for analyzing Light Weight Deflectometer (LWD) load-deflection basins has been developed by the authors of this paper. Similar to previous developments in analyzing Falling Weight Deflectometer (FWD) data, the methodology is now called “DeterministicEmpirical Backcalculation” or DEB. DEB is different from traditional backcalculation in that unique stiffnesses or moduli values for both the upper (bound or unbound) layer and the subgrade are calculated using both the shape of the deflection bowl and the overall center deflection under the influence of an LWD impact load. The main argument for employing deterministic-empirical backcalculation is that the values so derived are less variable, more realistic, and therefore more accurate on a point-bypoint basis than traditional backcalculation. REFERENCES Dorman, G.M. and Metcalf, C.T. 1965. Design Curves for Flexible Pavements Based on Layered System Theory. Highway Research Record No. 1188, Washington, DC, National Academy Press, 1965: pp. 69–84. Hogg, A.H.A. Equilibrium of a Thin Plate on an Elastic Foundation of Finite Depth. Philosophical Magazine, Volume 35 (243), 1944: pp. 265–276. National Cooperative Highway Research Program (NCHRP). LTPP Data Analysis: Feasibility of Using FWD Deflection Data to Characterize Pavement Construction Quality. Project 20–50 (09), NCHRP Web Document #52, Washington, DC, National Cooperative Highway Research Program, 2002. http://trb.org/news/blurb_detail.asp?id=942, 2002. Stubstad, R.N., Jiang, Y.J., Clevenson, M.L. and Lukanen, E.O. 2006. Review of LTPP Backcalculation Results. FHWA-HRT-05-150, Washington DC, Federal Highway Administration, 2006. http://www. fhwa.dot.gov/pavement/pub_details.cfm?id=374

694

New and/or innovative techniques in compaction & construction

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Long-term in-situ measurements of concrete culverts with high fills J. Vaslestad, G.Y. Yesuf & T.H. Johansen Norwegian Public Roads Administration, Eastern region, Oslo, Norway

ABSTRACT: Four instrumented full-scale tests using geofoam (expanded polystyrene) for load reduction on buried rigid culverts are described. The culverts were built and instrumented in the period 1988 to 1990. The method involves installing a compressible inclusion (geofoam) above rigid culverts in order to reduce the vertical earth pressure. Three full scaletests have been performed on buried concrete pipes under rock fill embankment and one full scale test on a concrete box culvert beneath silt clay fill. The instrumentation consisted of hydraulic earth pressure cells, deformation and temperature measurements. The reduction of vertical earth pressure has been compared with the overburden pressure which is calculated from the depth and unit weight of the fill. The geofoam effectively reduces the vertical earth pressure, and long-term observations shows that the earth pressure is reduced to less than 30% of the overburden in the granular fill. The earth pressure is reduced to less than 50% of the overburden in the silty clay. The long term observations of earth pressure and deformation for more than 15 years show that the method using geofoam is stable over time. 1

INTRODUCTION

The earth pressure on deeply buried culverts is significantly affected by arching. Both the magnitude and distribution of earth pressure on buried culverts are known to depend on the relative stiffness of the culvert and the soil. The so-called induced trench method (also called imperfect ditch) involves installing a compressible layer above the rigid culvert. As the embankment is constructed, the soft zone compresses more than the surrounding fill, and thus induces positive arching above the culvert. Organic material (sawdust, hay, leaves) has traditionally been used as the compressible material, Spangler (1958), Sladen & Oswell (1988), McAffee & Valsangkar (2005). Terzaghi (1943) stated that the amount of arching can only be obtained by direct measurement under field conditions. Kang et al. (2007) concluded that the long-term effects on induced trench performance need to be studied further. Three instrumented field installations were built in Norway in the period from 1988 to 1990, two concrete pipes and one cast in place box culvert. In the later years, this method using geofoam to reduce earth pressure have also been used on concrete culverts below high fills in China, e.g. Yang et al. (2005) and Zhang et al. (2006). 2

INSTRUMENTED FIELD INSTALLATIONS

2.1 Field installation Eidanger The first field installation built in 1988 is a concrete pipe with diameter 1.71 m beneath a 15 m high rock-fill embankment. Standard expanded polystyrene(EPS) blocks 0.5 × 1.0 × 2.0 m were used. Six test specimens of EPS were tested in the laboratory, and showed an average compression strength of 98.3 kPa. The measured density was 20.3 kg/m3. The EPS 697

Figure 1.

Geometry of instrumented cross section, Eidanger.

blocks were placed when the backfill had reached 0.5 m above the top of the pipe. Laying of the blocks is very fast and simple, and there is no need for excavating a ditch above the pipe. The in situ soil was excavated to about 0.5 m below the culvert elevation, down to bedrock, and replaced by 0–16 mm sandy grave1. The same material (0–16 mm sandy gravel) was used for backfill, with an optimum dry density of 21.5 kN/m3 and optimum moisture content 9.3%. A minimum of 97% Standard Proctor was required. Field density tests showed an average of 100% Standard Proctor (15 tests). The backfill was compacted in 20 cm thick layers. The pipe with the extent of the backfill zone and the instrumentation is shown in Figure 1. The backfill extended 1 m out from spring line and 0.5 m over the top of the pipe. The remaining fill in the embankment was rock-fill that was placed in 3 m thick layers, and compacted with 6–8 passes with a 6 ton vibratory roller. Based on field experience this equals 95–97% Standard Proctor. The construction began in August 1988 and was finished June 1989. To evaluate the performance of the pipe and the EPS during construction and on a longterm basis, the pipe and the surrounding backfill were instrumented with hydraulic earth pressure cells of the G1oetzl type. In addition, settlement tubes were installed on top of the pipe and on top of the EPS to measure vertical deformation. The Gloetzl cells were 20 × 30 cm, and 4 cells were used. The location of the cells is shown in Figure 1. One cell was placed in spring line to measure the horizontal earth pressure on the pipe (cell 1). Two cells were placed 20 cm over the top of the pipe to measure the vertical earth pressure; one cell in centerline (cell 2), and one cell over spring line (cell 3). The last cell (cel1 4) was placed in centre line 2 m over the top of the pipe to measure the vertical earth pressure in the embankment. The temperature in the soil at the cell locations was measured with thermistors, and temperature corrections 698

300 Measured vertical earth pressure Cell 2 Measured vertical earth pressure Cell 3

2

Earth pressure (kN/m )

250

Calculated overburden pressure - Cell 2 and Cell 3

200 150 100 50 0 01.01.1988

01.01.1992 01.01.1996 01.01.2000 01.01.2004 01.01.2008 Date

Figure 2.

Measured earth pressure cells 2 and 3, Eidanger.

were made. Earth pressure and deformation measurements during construction are described in Vaslestad (1991). The measured earth pressure on cell 2 at the top of the pipe is shown in Figure 2. The earth pressure on cell 2 increases to 72 kPa in September 1988 when the fill height is 8.3 m. Further increase in the fill height to 13.7 m does not increase the earth pressure on cell 2. In the period from 1996 and until January 2008 the earth pressure on the top of the pipe is relatively constant around 66–68 kPa, which is 25% of the overburden. The calculated overburden pressure in all figures is γ H where γ is the unit weight of the soil [KN/m3] and H is the height of the fill [m] over the level of the earth pressure. The earth pressure on cell 3 at the end of construction is 161 kPa, see Figure 2. The earth pressure is varying between 161 kPa and 167 kPa in the next period of twenty years. This is 61–63% of the overburden. Only half of this cell is covered with EPS, and this explains why the earth pressure is larger than on cell 2. The measured horizontal earth pressure on the pipe spring line (cell 1) is shown in Figure 3. The earth pressure at the end of construction is 164 kPa. The earth pressure is increasing slowly, and after almost twenty years, the horizontal earth pressure is 211 kPa. This is 72% of the overburden. The horizontal earth pressure is 3 times the measured vertical earth pressure on top of the pipe. This is not desirable and shows that it is necessary to increase the width of the EPS to decrease the horizontal earth pressure to a value more equal to the vertical earth pressure. In spite of the relatively large horizontal earth pressure, the pipe has shown no sign of distress. The earth pressure on cell 4 above the EPS is shown in Figure 3. The earth pressure is 204 kPa at the end of construction, and increasing to 222 kPa after almost 20 years. The measured vertical compression of the expanded polystyrene is shown in Figure 4. The vertical deformation stabilizes around 140 mm after several years, and there is no further increase after almost 20 years of measurements. The deformation is 28% of the initial thickness of the EPS. 2.2 Field installation Sveio The culvert is a concrete pipe with inner diameter 1.4 m and outer diameter 1.71 m. The embankment above the pipe consists of 15 m of rock-fill. Based on experience from the first field installation at Eidanger and parameter studies with the CANDE-program, Vaslestad et al. (1993), the width of the compressible layer was increased to at least 1.5 times the outer 699

350

Earth pressure (kN/m2)

300

250

200

150 Measured vertical earth pressure - Cell 4

100

Calculated overburden pressure - Cell 4 Calculated overburden pressure - Cell 1

50 Measured horizontal earth pressure - Cell 1

0 01.01.1988 01.01.1992 01.01.1996 01.01.2000 01.01.2004 01.01.2008 Date

Figure 3.

Measured earth pressure cell 1 and 4, Eidanger.

Deformation (mm)

Earth pressure (kN/m2)

300 250 200

Measured deformation in EPS

150

Calculated overburden pressure

100 50 0 –50 –100 –150 –200 01.01.1988 01.01.1991 01.01.1994 01.01.1997 01.01.2000 01.01.2003 01.01.2006 01.01.2009

Date

Figure 4.

Measured deformation of the expanded polystyrene, Eidanger.

diameter of the pipe. Increasing the width of the EPS to 1.5 times the width of the pipe has a positive effect on the structural response of the pipe. This is also in accordance with the findings of Sladen and Oswell (1988). This will decrease the horizontal earth pressure on the pipe. The ideal situation is that the horizontal earth pressure is equal to the vertical earth pressure. For practical reasons the width of the EPS was 3.0 m, and blocks with thickness 0.5 m was used. The compression strength of the EPS was 100 kPa and density 20 kg/m3. The in situ soil consisted of dense moraine. Well graded sandy gravel in a thickness of 400 mm was used as the bedding. 700

Well graded sandy gravel (0–16 mm) was also used for backfill. The backfill was compacted in 20 cm thick layers and nuclear field density tests showed an average of 98.5% Standard Proctor compaction. The backfill extended 1 m out from the spring line and 0.5 m above the EPS. The remaining fill in the embankment was rock fill. The average unit weight of soil is γ = 20 kN/m3. The construction began in November 1989 and in February 1990 the embankment had reached 13.7 m above the pipe. The remaining fill was placed in the beginning of 1992. The pipe and the backfill were instrumented with 5 hydraulic earth pressure cells of the Gloetzl type. Two settlement tubes were installed on top of the EPS to measure the vertical deformation. The instrumentation is shown in Figure 5. The measured earth pressures on cells no. 1, 2 and 3 are shown in Figure 6. The measured earth pressure on cell 1 at the top of the pipe is 75 kPa when the fill has reached 15 m above the pipe. In February 2008 the earth pressure is 74 kPa. This is 25% of the overburden. The earth pressure on cell 2 is slightly larger. The earth pressure on cell 3 is 96–97 kPa in this period, see Figure 6.

Figure 5.

Geometry of instrumented cross section, Sveio. 350

Earth pressure (kN/m2)

300 250

Calculated overburden pressure - Cell 1 Measured vertical earth pressure - Cell 2

200 150

Measured vertical earth pressure - Cell 3 Calculated overburden pressure - Cell 1 and Cell 2 Calculated overburden pressure - Cell 3

100 50

0 01.01.1990

01.01.1994

01.01.1998

01.01.2002

Date

Figure 6.

Measured earth pressure cells 1, 2, and 3, Sveio.

701

01.01.2006

01.01.2010

The horizontal and vertical earth pressures on the pipe spring line (cells 4 and 5) are shown in Figure 7. The horizontal earth pressure is 45 kPa after full fill height, and increasing to 49 kPa in the next 15 years. The vertical earth pressure at the same level (cell 5) is 170 kPa after end of construction increasing to 191 kPa after 15 years. The average measured horizontal earth pressure coefficient is K = 0.27 at the pipe spring line. Compared to the measured vertical earth pressure at the top of the pipe, the average horizontal earth pressure is around 70%. This implies that the moments in the pipe are very small. This shows that increasing the width of the EPS reduces the horizontal earth pressure. The measured vertical compression of the expanded polystyrene is shown in Figure 8. The deformation is 65 mm at a fill height of 12 m and increasing to 88 mm at a fill height of 13.7 m. When the remaining fill up to 15.0 m was placed, the deformation increased to 131 mm. The next measurement 15 years after, shows that the deformation has increased to 190 mm. This is 38% of the initial thickness of 50 cm of the EPS. 350

Earth pressure ( kN/m2)

300

Measured horizontal earth pressure - Cell 4 250

Measured vertical earth pressure - Cell 5 Calculated overburden pressure - Cell 4 and Cell 5

200 150 100 50 0 11.01.1990

11.01.1994

11.01.1998

11.01.2002

11.01.2006

11.01.2010

Date

Deformation (mm) Earth pressure (kN/m2)

Figure 7.

Measured earth pressure cells 4 and 5, Sveio.

400 300

Measured deformation at the top of EPS

200

Calculated overburden pressure 100 0 –100 –200 –300 01.01.1988

01.01.1992

01.01.1996

01.01.2000

01.01.2004

Date Figure 8.

Measured deformation of the expanded polystyrene, Sveio.

702

01.01.2008

2.3 Field installation Hallumsdalen The culvert is a cast-in-place box culvert with width 2.0 m and height 2.55 m. It is a continuous culvert and has a total length of 385 m and is crossing a valley beneath an embankment of compacted dry crust clay up to 23 m in height. The subsoil consists of over consolidated silty clay with water content 25–30% and undrained shear strength 35–70 kPa. To investigate the time effects on the earth pressure in the cohesive fill in the imperfect ditch method, expanded polystyrene was placed above the culvert in a length of 20 m. The instrumented section of the culvert is situated in the counter fill that is built up with silty c1ay. The unit weight of the silty c1ay is γ = 20 kN/m3. Expanded polystyrene with thickness 0.5 m and width 2.0 m was placed above the culvert as shown in Figure 9. This section was instrumented with two hydraulic earth pressure cells of the Gloetzl type, cells 1 and 2. The deformation of the EPS was measured using a settlement plate. To compare the earth pressure on the imperfect ditch section with a conventional section, one earth pressure cell was placed above the culvert in a cross-section without EPS, cell 3, see Figure 9. The construction of the embankment began in July 1989. The measured earth pressure on cell 1 at the top of the culvert is shown in Figure 10. At completion of the fill in February

Figure 9.

Geometry of instrumented cross section, Hallumsdalen. 250

Earth pressure (kN/m2)

200

150

100

50

0 01.01.1989

Measured vertical earth pressure - Cell 1 Calcualted overburden pressure - Cell 1 Measured vertical earth pressure - Cell 2 Calculated overburden pressure - Cell 2

01.01.1993

01.01.1997

01.01.2001

Date

Figure 10.

Measured earth pressure cells 1 and 2, Hallumsdalen.

703

01.01.2005

01.01.2009

1990 the fill height was 10.8 m above the cell level and the overburden is 206 kPa. The measured earth pressure is 132 kPa at this fill height, which is 63% of the overburden. The earth pressure decreases slightly to 123 kPa in April 1991. There is a further decrease to 88 kPa in December 1991. This is probably due to stability problems and movements in the counter fills that occurred in April 1991. The earth pressure stabilises to around 100 kPa in 1993. The last measurement in July 2007 shows around 92 kPa. The measured earth pressure on cell 2 which is located in the fill 1 m above the EPS, is shown in Figure 10. At completion of fill in February 1990 the earth pressure is 144 kPa, which is 81% of the overburden. The earth pressure decreases to 128 kPa in July 1992. In July 2007 the earth pressure has decreased to 110 kPa. The earth pressure on cell 3, which is located on top of the culvert in a section without EPS, is shown in Figure 11. The fill height above the culvert is 9.8 m. At completion of the fill in February 1990 the measured earth pressure is 244 kPa. The overburden is 196 kPa, and the measured earth pressure is 1.24 times the overburden. Based on extensive finite element modeling, Tadros et al. (1989) proposed an expression for calculating the earth pressure on concrete box culverts. For silty clay soil, this expression gives an earth pressure of 1.17 times the overburden on top of the culvert. The measured earth pressure is 245 kPa in July 2007. The measured deformation of the expanded polystyrene is shown in Figure 12. The deformation is 60 mm when the overburden is 100 kPa, which corresponds to the compression

Earth pressure (kN/m2)

300 250 200 150 Measured earth pressure 100

Overburden pressure

50 0 01.01.1989 01.01.1993 01.01.1997 01.01.2001 01.01.2005 01.01.2009

Date Measured earth pressure cell 3, Hallumsdalen. Deformation (mm) Earth Pressure (KN/m2)

Figure 11.

300 200 100 0 Measured Earth pressure

–100

Measured deformation in the EPS –200 –300

01.01.1989

01.01.1994

01.01.1999

01.01.2004

01.01.2009

Date

Figure 12.

Measured deformation of the expanded polystyrene, Hallumsdalen.

704

strength of the EPS. The deformation is 220 mm at completion of the fill, when the overburden is 196 kPa. For the next four years the deformation is slightly increasing to 250 mm, which is 50% of the initial thickness of the EPS. The last measurement in July 2007 shows an increase to 269 mm, this is 54% of the initial thickness. This shows that the deformation of the EPS in cohesive fill is greater than in granular fills. The observed settlement of the culvert was between 70 and 110 mm in the instrumented sections in the observation period.

3

CONCLUSIONS

The long-term full scale tests described show that the induced trench method can be used to reduce the vertical earth pressure on rigid culverts. Expanded polystyrene blocks, used as the compressible material, are super light, easy to handle, and they simplify the construction procedure. Use of organic material in induced trench culverts is not recommended due to the possibility of decomposition and the difficulty of specifying the material characteristics. Two full scale tests on concrete pipes backfilled with well compacted sandy gravel beneath high rock-fills show that the vertical earth pressure on top of the pipes was reduced to less than 30% of the overburden. The long-term compression of the expanded polystyrene varied from 28 to 38%. Long-term measurements show that there is no marked increase in vertical earth pressure after end of construction. Based on the full scale tests and finite element analyses, it is recommended to use a width of the expanded polystyrene that is 1.5 times the outer diameter of the pipe. One full-scale test on a concrete box culvert backfilled with silty clay and situated below a silty clay embankment was performed. One section with expanded polystyrene and one without polystyrene were instrumented. The vertical earth pressure in the section with expanded polystyrene was reduced to less than 50% of the overburden. The vertical earth pressure on the section without expanded polystyrene was 1.24 times the overburden. The measured long-term compression of the expanded polystyrene was 54% of the initial thickness of 50 cm. Much of the deformation in the expanded polystyrene occurs during the construction phase and no problem has been observed on the road surfaces due the long-term settlement of the expanded polystyrene. The instrumentation also shows that the hydraulic earth pressure cells are still working after almost 20 years. Long-term arching on flexible steel culverts was measured with hydraulic earth pressure cells in a period of 21 years, Vaslestad et al. (2007).

REFERENCES Kang, J., Parker, F. & Yoo, C. 2007. Soil-structure interaction and imperfect trench installations for deeply buried concrete pipes. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 133, No 3: 277–285. McAffee, R.P. & Valsangkar, A.J. 2005. Performance of an induced trench installation. Transportation Reaearch Record, Journal of the Transportation Research Board, No. 1935, Transportation Research Board of the National Academies, Washington DC: 230–237. Sladen, J.H. & Oswell, J.M. 1988. The induced trench method—A critical review and case history. Canadian Geotechnical Journal, Vol. 25: 541–549. Spangler, M.G. 1958. A practical application of the imperfect ditch method of construction. Highway Research Board, Proceedings, volume 37. Tadros, M.K., Benak, Y., Abdel-Karin, A.M. & Bexten, K. 1989.Field testing of a concrete box culvert. Transportation Research Record, Journal of the Transportation Research Board, No. 1231, Transportation Research Board of the National Academies Washington DC, 1989, pp. 39–54. Terzaghi, K. 1943. Theoretical soil mechanics. John Wiley and Sons, Inc. Vaslestad, J. 1991. Load reduction on buried rigid pipes below high embankments. ASCE Specialty Conference, Pipeline Division, Denver, Colorado: 47–58. Vaslestad, J., Johansen, T.H. & Holm, W. 1993. Load reduction on rigid culverts beneath high fillslong term behaviour. Transportation Research Record, Journal of the Transportation Research Board No. 1415, Transportation Research Board of the National Academies, Washington DC: 58–68.

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Vaslestad, J., Kunecki, B. & Johansen, T.H. 2007. Twenty one years of earth pressure measurements on buried flexible steel structure, First European Conference: Buried flexible steel structures. Rydzyna: 23–24 April 2007, Proceedings Archives of Institute of Civil Engineering, 1/2007: 233–244. Yang, X., & Yongxing, Z. 2005. Load reduction method and experimental study for culverts with thick backfills on roadways in mountainous regions. China Civil Engineering Journal, Vol. 38, No 7: 116–121. Zhang, W., Liu, B. & Xie, Y. 2006. Field test and numerical simulation study on the load reducing effect of EPS on the highly filled culvert. Journal of Highway and Transportation Research and Development, China, Vol. 23, No 12: 54–57.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Research and applications of new pavement structure based on large stone porous asphalt mixture B. Yufeng & W. Songgen Shandong Bureau of Highway Administration, Jinan, P.R. China

G. Huber Heritage Research Group, Indianapolis, IN, USA

ABSTRACT: This paper analyzes the main reasons of premature failures of asphalt pavement with bound base and the use of Large Stone Porous Asphalt Mixture (LSPM) to prevent such failures. A systematic evaluation of the LSPM is presented covering rutting resistance, moisture susceptibility, permeability, reflection cracking and fatigue resistance. Based on this evaluation, a new pavement structure was adopted that includes LSPM. The oldest of these sections has been in use for five years and this paper reviews the field performance.

1

BACKGROUND

The total length of the Chinese highway network is more than 2 million kilometers, including 45,000 kilometers of expressway. Most of these highways were built using bound (pozzalanic) base because of its high strength, high bearing capacity, and low price. But this type of base has brittle behavior and reflection cracking occurs, as shown in Figure 1. Once cracked, water penetrates through the hot mix asphalt and accumulates on top of the relatively impermeable base. Pumping of fines and settlement failures follow. To prevent these failures, several techniques were tried, such as dense gradation hot mix asphalt to reduce the water intrusion, and a stress absorbing layer to reduce reflecting cracking, but the results were not satisfactory.

Figure 1.

Reflection cracking and failure on pavement with pozzalanic base.

707

Hot mix asphalt is a three-phase mixture that is relatively impermeable but still allows some water to intrude into the pavement. A porous material at the bottom of the HMA that has the ability to drain water and cracking resistance to prevent reflection of cracks from the cement-stabilized base would prevent pavement failure. Through six years work, research on Large Stone Porous Asphalt Mixture (LSPM) and its use in pavement structures has reached a satisfactory conclusion. Pavements containing LSPM have resisted premature failures. 2

INTRODUCTION OF LARGE STONE POROUS ASPHALT MIXTURE (LSPM)

Large Stone Porous Mixture (LSPM) is specified in three sizes, normally larger than 26.5 mm. The gradation consists mostly of coarse aggregate (26.5 mm–52 mm) and some fine aggregate. The content of top size aggregate is usually above 50%. The skeleton of the mix is mainly formed by the single sized aggregate that has many drainage voids. Air voids of the LSPM are in the range of 13% to 18%. High viscosity asphalt binder is used to drain down and provide adequate bitumen film thickness. They also resist rutting, reflection cracking, and fatigue cracking. The gradation and Marshall design properties are listed in Tables 1 and 2. 3

PROPERTIES OF LARGE STONE POROUS MIXTURES

Research on LSPM properties focused on high temperature deformation resistance, permeability, and fatigue or reflecting cracking. The design of LSPM tries to balance the different properties. 3.1 Rutting resistance LSPM is a mixture of single sized aggregate that has many drainage voids. Composed of limestone aggregate and MAC70# asphalt binder the coarse aggregate (>9.5 mm) content is more than 70%, which forms a very strong skeleton to resist deformation. Rut testing done

Table 1.

Gradation of large stone porous asphalt mixture.

Sieve size (mm) 52

37.5

31.5

26.5

19

13.2

9.5

4.75 2.36 1.18 0.6

0.3 0.15 0.075

LSPM-25 100 100 100 70–98 50–85 32–62 20–45 6–29 6–18 3–15 2–10 1–7 1–6 1–4 LSPM-30 100 100 90–100 70–95 40–76 28–58 19–39 6–29 6–18 3–15 2–10 1–7 1–6 1–4 LSPM-35 100 75–98 67–96 50–80 25–60 15–40 10–35 6–25 6–18 3–15 2–10 1–7 1–6 1–4

Table 2.

Marshall test criteria for large stone porous mixes.

Index

Unit

Standard

Mixture size Specimen size Marshal blows (per side) Air voids Thickness of bitumen film Schellenberg drainage test Cantabro test Recommended bitumen content

mm mm

≥26.5 mm ϕ152.4 mm × 95.3 mm 112 13–18 >12 ≤0.2 ≤20 3.0–3.5

% μm % % %

708

Table 3.

Figure 2.

Rutting test results on various mixtures.

Mixture type

Dynamic stability (repetitions/mm)

Deformation after 10,000 passes (mm)

LSPM-30 A HMA (25 mm) Superpave (25 mm) OGFC (16 mm) SMA (13 mm)

4630 820 2800 3750 5800

2.06 7.63 2.54 2.74 1.64

Relationship between air voids and permeability index.

according to Chinese specifications indicates that LSPM is very resistant to rutting. Results are listed in Table 3. Dynamic stability (the number of repetitions to cause one mm of rutting for the LSPM) ranks second in Table 3. Results indicate that the high temperature performance of LSPM is very good, surpassed only by SMA. 3.2 Permeability The main function of the LSPM is to rapidly drain water out of the pavement; therefore, permeability is a key property. Testing according to ASTM Method PS129-1 was done using the Karol-Warner permeameter. The results are shown in Figure 2. The permeability index increased with the air voids increasing from 13% to 18%. To drain water from the pavement, the permeability index should be at least 0.01. Figure 2 shows that once the air voids are 18% or greater, the permeability doesn’t increase anymore. Since excessively high air voids will lower mixture strength, the design air voids should be selected as low as possible while maintaining adequate permeability. From these reasons the air void specification was set to be 13% to 18%. At this air void level, the permeability index of LSPM is sufficient to allow effective drainage. 3.3 Cracking resistance In order to analyze the crack resistant of LSPM, the mechanical models of fracture mechanics were constructed with cross-section shown in Figures 3 and 4. Regardless of the symmetry of the load, the LSPM releases stress concentrations at the tip of upward growing cracks because of its large pores (13∼18%). Therefore, the mix has considerable ability to control the development of reflective cracking. 709

x

x

SMA

SMA

LSPM

LSPM Old asphalt pavement

Old asphalt

Old semi-treated base

Old semi-treated

z Figure 3.

Symmetric finite model.

z Figure 4.

Asymmetric finite model.

Crack in bound base LSPM blocks the crack

Figure 5.

Large stone porous mix preventing reflection crack.

The modulus of the LSPM is about 400–600 MPa, significantly lower than normal mixtures that are usually between 1000 to 1400 MPa. The stress concentrations at the tip of upward growing cracks will increase along when the asphalt mixture moduli increases. So LSPM can resist cracking better than regular HMA. Figure 5 demonstrates the effectiveness of LSPM to resist cracks from reflecting upward. 3.4 Fatigue resistance LSPM was tested in a beam fatigue test at 200, 300 and 600 micro-strain levels and compared to asphalt treated base (ATB) and Marshall hot mix asphalt (HMA). Figure 6 indicates that LSPM has a steeper slope. At high to very high strain levels, the LSPM has similar fatigue behavior as asphalt treated base (ATB) or HMA (AC20). The similar fatigue resistance combined with higher cracking resistance at high strains explains the ability to resist reflection cracking. The fatigue equation for LSPM used as the basis for design of an overlay is shown in Equation 1. If there is a large tensile stress in the LSPM layer, there are several ways to release the stress. Adjust the combinations in order to put the LSPM layer as far away from the tensile stress zone as possible. Add a thin anti-fatigue layer beneath the LSPM layer, which enhances the resistance to fatigue and seals the layer at the same time. Add a plastic grid beneath the 710

Figure 6. Fatigue property of LSPM (30 mm), asphalt treated base (ATB 30 mm) and hot mix asphalt (AC 20).

Figure 7.

Retained Marshall stability of the LSPM.

LSPM layer; the first and second method above has been applied in Shandong Province and satisfactory results were obtained. N = 1.2 ×10 −6 e 0.027VFA − 0.006 E (ε t )−3.6

(1)

VFA: voids of filled with asphalt εt: the strain of asphalt mixture 3.5 Water resistance Submerging asphalt mixtures under water can reduce adhesion between the bitumen and aggregate and causes the mixture strength to decrease. To improve resistance to water, LSPM should contain bitumen with high viscosity and bitumen modified by MAC and SBS. The modified bitumen produces a bitumen film thickness of 12 μm. The test method used to evaluate moisture sensitivity is retained Marshall stability. One set of specimens is tested for Marshall stability as per the design method. A second set is vacuum saturated and soaked in water at 60°C for 24 hours and then is tested. Typical test results are 711

Table 4.

Performance comparison of alternate mixtures.

Mixture type

AC

OGFC

SMA

LSPM

Structure

Dense

Skeleton

Va (%) Bit. content (%) Rutting resistance Fatigue resistance Water resistance Drainage capacity Reflection cracking resistance Workability Price

3–6 3.5–8.0 Poor Good Good Very poor Middle

>15 4–6 Good Poor Middle Very good Very poor

Skeleton and dense 3–4 5.5–6.5 Very good Very good Very good Poor Very good

“Single” size aggregate skeleton 13–18 3.1–3.6 Very good Middle Good Very good Very good

Easy Middle

Difficult Expensive

Fairy difficult Expensive

Easy Inexpensive

shown in Figure 7. At the design asphalt content of 3.2%, the soaked specimens retain 96% of the original stability, well above the specification limit of 85%. 3.6 Summary of properties The properties of Large Stone Porous Mixtures were compared with other mixes and the results are listed in Table 4. Attributes of the LSPM considered advantageous include drainage capacity and cracking resistance. In addition, LSPM is of lower cost and easy to construct. The evaluation of the LSPM yields a result that has balanced properties. Compared with other mixtures, the performance of LSPM is satisfactory. 4

PAVEMENT STRUCTURE DESIGN WITH LSPM

4.1 New pavement structures Existing Chinese standards for pavement structural design use pozzalanic bound base that creates two challenges to long-term performance. Cracking and poor drainability of the pozzalanic base causes cracking of the hot mix asphalt layers and pumping that causes pavement failures. A new pavement structure based on LSPM has been developed to take advantage of its drainage, rutting and cracking resistance. The LSPM layer provides stress relief between the asphalt layer and bound base. The new pavement design structure has been widely used on highways in Shandong Province. 4.2 Overlay design with LSPM on old asphalt pavement Large Stone Porous Mixtures have also been used during rehabilitation of existing pavements. LSPM is placed directly on the old pavement after repair of failed areas. The LSPM resists reflection of crack from the existing pavement and provides drainage for any water that enters the pavement. This approach allows full use of the remaining strength of the old pavement. The use of LSPM in pavement rehabilitation began in 2001. Nine different pavement structures were tested and monitored. LSPM has controlled premature failures and performance of the pavements were still very good after having been opened to traffic for 6 years. In 2003 LSPM was introduced to rehabilitate highways where the old asphalt pavement layer is removed from the stabilized base. Two approaches were used. LSPM was placed directly on the old stabilized base and new asphalt layers were placed above it. Alternately, a new layer of stabilized base was placed first and the LSPM and asphalt layers were placed on top. Both approaches have been successful and in 2007 LSPM is being used to rehabilitate 760 km of highways. 712

Asphalt top course 16–18 cm

Asphalt Intermediate course Asphalt bottom course

10–15 cm

LSPM Semi-rigid base

40–60 cm Semi-rigid type sub-base Soil Figure 8.

Typical new pavement structural design using LSPM.

Asphalt top course Asphalt Intermediate course

16–18 cm

Asphalt top course 8–10 cm

Asphalt bottom course 10–15 cm

LSPM

LSPM

8–10 cm

Old asphalt pavement

Old asphalt pavement

(a) Typical pavement rehabilitation using large stone permeable mix on highways and arterials.

(b) Typical pavement rehabilitation using large stone permeable mix on rural roads.

Figure 9.

5

Asphalt bottom course

Typical pavement rehabilitation using large stone permeable mix.

CONSTRUCTION GUIDELINES FOR LARGE STONE PERMEABLE MIX

Procedures have been developed for mixing, transport, placement and compaction of LSPM. 5.1 Mixing plant Normal operating procedures are used for the hot mix plant. Using normal practice for stockpile, cold feed controls the properties of the mix. Mixing temperature should be 160 to 170°C for the MAC70# and 170 to 180°C for the SBS modified asphalt. Mixing temperatures greater than 190°C should be avoided because of the risk of drain down. 5.2 Placement and compaction Research was conducted on placement of thicknesses in the range of 8 cm to 18 cm. It is recommended that compacted lift thickness be between 10 and 15 cm. The ratio of placement thickness to final compacted thickness is 1.2. Two pavers in echelon covering the full width of the road including the shoulders place the LSPM. The paver speed is 0.8–1.2 m/min (2.6–3.9 ft/min). 713

A vibratory steel-wheeled roller and a pneumatic-tired roller using the following typical rolling pattern are used for compaction: Four passes of vibratory steel wheeled roller traveling at 1.5∼2 km/h (1.0∼1.25 mi/h). Four passes of a pneumatic-tired roller traveling at 1.5∼2 km/h (1.0∼1.25 mi/h). One final pass with steel wheeled roller operating in static mode traveling at 3∼4 km/h (2.0∼2.5 mi/h). 5.3 Quality assurance Quality assurance testing requirements are listed in Table 5. 6

PAVEMENT PERFORMANCE COMPARISON

In July 2007, a pavement performance evaluation was done on the first project to be rehabilitated with LSPM. The performance of four research sections on Interstate Highway 204, Project 01 were evaluated and compared to the standard rehabilitation section. The structural cross-section of the research sections and the standard rehabilitation are listed in Table 6. Table 5.

Quality assurance of large stone porous mix. Tolerance

Items Thickness

Each layer Total thickness

Density

Expressway

Others

Test methods

Thickness >50 mm Every 2000 m2 Every 2000 m2

8% –5% 98% Marshall

10% –8%

In situ T 0912 T 0924, T 0922

5 mm 2.4 mm No less than design

7 mm 3.0 mm No less than design

T 0931 T 0932 T 0911

±0.3%

±0.5%

T 0911

Every 2000 m2 Random Continuously Each transaction Each transaction

Air voids Evenness (Max. bias) Evenness (σ) Width Transverse slope

Table 6.

Inspect frequency

Trial pavement structure on project 01.

SMA13 AC20I LSPM Treatment base

K27 + 000– K27 + 250

K27 + 250– K27 + 450

K27 + 250– K27 + 800

K27 + 800– K28 + 000

Other section of the road

4 cm 5 cm 8 cm

4 cm 5 cm 12 cm

4 cm 5 cm 15 cm

4 cm 5 cm 18 cm

4 cm 5 cm 30 cm

Old asphalt pavement

Table 7.

Summary of roughness data for projects 01, 02 and 03.

Project no.

01

Type Construction date Testing date IRI (m/km)

No LSPM 2001 2008 1.75

02 LSPM 2002 2008 1.27

No LSPM 2004 2008 1.17

714

03 LSPM 2004 2008 1.49

No LSPM 2005 2008 1.19

LSPM 2005 2008 1.13

Table 8. Rutting data collected from project 01. Project 01

Rutting depth (mm)

Section 1 Section 2

6–10 3–6

6.1 Resistance to reflective cracking Using the laser roughness tester (ARRB-5R2T), roughness data were collected and analyzed, and are provided in the summary Table 7. For two of the three projects, the pavement containing LSPM is smoother than the standard rehabilitation. 6.2 Rutting data collected from project 01 Interstate Highway 204, Project 01, carries 15,000 AADT. Rutting data collected at two of the sections are given in Table 8. 7

SUMMARY AND CONCLUSIONS

Premature damage of pavements in Shandong Province in China is caused by cracks that reflect from pozzalanic-bound base courses and the collection of water that intrudes and collects at the top of the base course. Large stone porous mixtures (LSPM) were introduced to new construction and as part of rehabilitation to resist both of these actions. The LSPM resists reflective cracking and the high permeability of the mix ensures that water does not collect under the hot mix asphalt layers. The LSPM sections of rehabilitated pavements were evaluated after five years of service and are found to be resistant to cracking and pumping. The following study findings can be listed: • Moisture damage from pumping is a prevailing cause of premature failures in China. These failures cannot be prevented unless moisture entering the pavement is controlled. • LSPM has good resistance to rutting and reflecting cracking, and good drainage properties. Application of the LSPM is one method to solve the premature failures. • The LSPM course provides a transition layer between the bound base that develops shrinkage cracks and the asphalt layer. The LSPM made good use of the advantages of the bound base such as high strength and cheaper price and so on. • A set of new structures based on the LSPM were recommended and widely used in rehabilitation, maintenance, and newly constructed highways, the long term performance is very satisfactory. • Mixing, placement and compaction procedures were developed to produce LSPM with good performance. A schedule of quality acceptance properties was developed based on research and evaluation. • The research and application of the LSPM has been formed into a new technology for pavement systems. REFERENCES Industry Standard of People’s Republic of China, “Standard Test Methods of Bitumen and Bituminous Mixtures for Highway Engineering” (JTJ052-2000) Beijing, China Communications Press, 2000. Industry Standard of People’s Republic of China, “Technical Specifications for Construction of Highway Asphalt Pavements” (JTJ032-94) Beijing, China Communications Press, 1994. Industry Standard of People’s Republic of China, “Specifications of Asphalt Pavement Design for Highway” (JTJ014-97) Beijing, China Communications Press, 1994. Industry Standard of People’s Republic of China, “Standard Test Methods of Aggregate for Highway Engineering” (JTJ058-2000) Beijing, China Communications Press, 2000.

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Industry Standard of People’s Republic of China, “Specifications of Drainage Design for Highway” (JTJ018-97) Beijing, China Communications Press, 1998. “Study of the Application of Large-stone Asphalt Mixes in Old Pavements Rehabilitation” Highway Bureau of Shandong DOT; Shandong Traffic Science Research Institute; Southeast University. NCHRP REPORT 386 Design and Evaluation of Large Stone Asphalt Mixes. Transportation Research Board National Research Coucil. 1990.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Fiber-reinforced concrete pavement design and material requirements A. Bordelon & J.R. Roesler University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

ABSTRACT: Fiber-reinforced concrete (FRC) has been applied to concrete pavements for years, but there has been slow acceptance of a standard design process and appropriate material specifications for FRC. Large-scale concrete slab tests were performed to demonstrate the increase in load capacity that FRC provides over plain concrete slabs. Flexural beam tests, based on ASTM C1609–07, determined that the increase in FRC slab flexural capacity over 150 , of the FRC. Several plain concrete was related to the equivalent flexural strength ratio, R150 reinforcement types available (steel fibers, synthetic fibers, and welded wire reinforcement) were compared in this study. An effective flexural strength (MOR*) which incorporates the toughness benefit of the fiber-reinforcement was suggested for implementation into existing design procedures. An example of a pavement design calculation is provided to show the 150 to account for the increased potential thickness reduction that occurs when using the R150 load capacity of FRC slabs. Altering joint spacing or use in concrete overlays can also be employed with FRC to accommodate pavement design constraints. 1

INTRODUCTION

1.1 Background Fiber-reinforced concrete (FRC) has been used in the construction of rigid pavements and slabs for several decades (Rice 1972, Parker 1974, Parkard & Ray 1984, Rollings 1986, Bentur 1990, Van Dam 1995). Discrete structural fibers improve the fracture resistance of concrete and limit crack width. In the past, structural fibers have been added to paving concrete to reduce the required slab thickness and increase the allowable joint spacing. Engineering judgment has primarily been used to specify the type and quantity of fibers required and to determine any concrete slab thickness reduction or joint spacing increase. Unfortunately, excessive reductions in thickness accompanied by large panel sizes, or FRC layers bonded to distressed concrete pavement have sometimes resulted in premature slab failures (Rollings 1993). Typical slab distresses were corner breaks, reflective cracks, late sawing of joints, excessive joint movements, and joint sealant damage. Slab curling which resulted from high cementitious contents, autogeneous and differential drying shrinkage, and lower aggregate volume percentages appeared to be one of the common problems in the slab failures (Rollings 1993). The lessons learned from these previous failures indicate that the effects of curling cannot be ignored in FRC pavements. Developments in admixture technology during the past decades have enabled easier batching, mixing, and placement of FRC. Research has also solidified the understanding that each fiber type performs differently for a given plain concrete mixture and this must be considered in designing and specifying the use of FRC. In addition, the improved structural properties of fiber-reinforced concrete slabs that have been documented in the literature have not been given serious consideration in existing design guidelines and specifications for concrete pavements. Since interest for a slab thickness design approach resides primarily with fiber manufacturers, there has been slow adoption of fibers by engineers in concrete pavement

717

applications. Furthermore, without being able to quantify the reduction in thickness or allowable slab size for a given fiber type and content, an accompanying cost-benefit analysis cannot be completed. Finally, an accepted standard testing method for determining the flexural toughness of FRC is needed so that the original design assumptions can be verified with the actual concrete materials proposed by the contractor. 1.2 Objectives The first objective of this paper is to demonstrate the structural benefit of fiber-reinforced concrete pavement over plain concrete pavement based on laboratory beam and concrete slab testing. The results of the laboratory testing and similar FRC slab data from the literature are used to propose a new methodology for designing concrete pavements containing fiberreinforcement based on the concept that fibers increase the cracking resistance in slabs despite the fact that this increased capacity is not demonstrated in standard beam tests. Finally, the paper will specify a post-cracking performance or toughness test process for fiber-reinforced concrete such that any fiber type can be used in the concrete pavement as long as it can meet the minimum specified performance requirement (toughness) and concrete flexural strength. 2

BACKGROUND ON FRC SLAB DESIGN

Much of the early published data on FRC pavement test and field sections reflect the use of fiber volume contents between 1 and 2 percent and significantly higher cement contents than typically seen in plain concrete pavements. Parker (1974) developed design thickness curves based on the United States Army Corps of Engineers (USACOE) fibrous concrete full-scale test sections, which were eventually implemented into the Army’s rigid pavement design manual in 1979. The design method utilized the concept of a working crack criterion rather than a first crack criterion, which recognized the increased cracking resistance of FRC slabs and the fact that cracks in FRC slabs deteriorate less rapidly than cracks in plain concrete. For high fiber volume fractions (up to 2%), Parker’s (1974) methodology showed FRC thickness reductions of 30 and 50 percent are possible. Recent applications of FRC to concrete pavements have targeted fiber contents of less than 0.5 percent for economic, handling, and constructability reasons. Experimental testing of slabs on ground has shown the significant improvement in the flexural and ultimate load capacities of FRC slabs over the plain concrete slabs (Sham & Burgoyne 1986, Beckett & Humphreys 1989, Beckett 1990, 1995, 1998, Tatnall & Kuitenbrouwer 1992, Falkner & Teutsch 1993, Beckett et al. 1999, Meda et al. 2003, Roesler et al. 2004, 2006) as originally reported by Parker. The majority of laboratory fatigue studies confirm that FRC is more fatigue resistant than plain concrete (Johnston & Zemp 1991, Ramakrishnan et al. 1989, Jun & Stang 1998), especially at higher volume fractions (i.e., greater than one percent). Lee and Barr (2004) show little difference in compressive fatigue results from a survey of the literature, but did conclude a difference exists between the flexural fatigue of plain and fibrous concrete. Some of the most notable and convincing work was Rollings’ (1986, 1989) research, which developed several fatigue algorithms for steel FRC materials based on the USACOE full-scale data. The fatigue curves clearly demonstrated an increased fatigue resistance of FRC over plain concrete pavements given the same stress ratio. Laboratory test results suggest the fatigue resistance of FRC to be dependent on the volume fraction, fiber type, and fiber geometry. The characterization of fatigue resistance of FRC based only on two-dimensional laboratory beam flexure testing does not always predict the increased cracking resistance obtained from large-scale slab tests (Roesler et al. 2004, 2008). The implication of such a conclusion is that laboratory tests for FRC must account for the added benefit (toughness) which fibers impart to plain concrete slabs and that thickness design methods must include this toughness performance parameter as an input. 718

3

LABORATORY TESTING OF FIBER-REINFORCED CONCRETE

A laboratory testing program was conducted to characterize the structural capacity of fiberreinforced concrete slabs and compare the results to beam flexural test performance. Similar slab testing with various slab and fiber geometries has been conducted by other researchers over the past 20 years (Sham & Burgoyne 1986, Beckett & Humphreys 1989, Beckett 1990, 1995, 1998, Tatnall & Kuitenbrouwer 1992, Falkner & Teutsch 1993, Beckett et al. 1999, Meda et al. 2003, Roesler et al. 2004, 2006) with emphasis on slab-on-ground applications for industrial floor systems. 3.1 Experimental plan The three fiber types used were a straight synthetic (polypropylene/polyethylene blend) fiber with 40 mm length and an aspect ratio of 90, a steel fiber with hooked ends with 60 mm length and an aspect ratio of 65, and a crimped steel fiber with 50 mm length and an aspect ratio of 40, each from different manufacturers. The volume fractions of synthetic fiber used were 0.32 and 0.48 percent, or 3.0 and 4.4 kg/m3, respectively. The hooked end steel fibers were introduced into the concrete mix at 27.3 kg/m3 or 0.35 percent by volume. The crimped steel fiber was added at a rate of 39.0 kg/m3 or 0.50 percent by volume. The fiber dosage levels (0.48% synthetic, 0.35% hooked end, and 0.50% crimped) was based on laboratory toughness testing of beams, such that similar beam toughness or equivalent flexural strength values (JCI 1983) were achieved between the different mixtures. The synthetic “macro” fiber’s mechanical properties and geometry are significantly different than other synthetic “micro” fibers, which are commonly used to control plastic shrinkage cracking. The concrete mixtures for all slabs constructed are shown in Table 1. The final waterto-cement ratios varied between 0.47 and 0.51. The coarse aggregate used in the mix was a crushed limestone with a maximum size of 25 mm and a specific gravity of 2.62. The fine aggregate was natural, siliceous sand with a specific gravity of 2.66. The coarse and fine aggregate gradations met the ASTM C33-02a (2002) guidelines for coarse (#57) and fine aggregates. Welded wire reinforcement (WWR) was also cast into one slab for comparison to fiber reinforcement in the concrete slab-on-ground testing. The slab with WWR (152 × 152 MW19 or 6 × 6 W2.9) was designed for a typical minimum temperature steel recommended for 130 mm thick slabs. 3.2 Slab testing results Concrete beam flexural strength test results have not been consistent with experimental slab test results given the same concrete material. There has been a considerable difference in the load carrying capacity between plain and FRC slabs reported in the literature (Beckett 1990, Beckett 1998, Barros & Figueiras 1998, Bischoff et al. 2003, Meda et al. 2003), which is not reflected in the plain and FRC beam strength tests. The objective of the large-scale concrete Table 1.

Concrete mixture constituents, proportions, and properties.

Materials (kg/m3)

Plain concrete and WWR

0.48% and 0.32% synthetic fibers

0.35% Hooked end steel fibers

0.50% Crimped steel fibers

Coarse aggregate Fine aggregate Cement Water Superplasticizer (ml/100 kg) Water-to-Cement ratio Air content (%) Slump (mm)

995 823 363 178 925 0.49 1.8 200

976 807 360 183 1,117 0.51 2.8 130

965 796 347 163 868 0.49 6.0 110

983 813 363 172 1,328 0.47 3.2 190

719

Figure 1.

Table 2.

Concrete slab testing configuration.

Experimental design and summary of slab testing results. Plain concrete

WWR

FRC

Reinforcement type

N/A

Steel

Crimped steel

Hooked end steel

Straight

Synthetic

Reinforcement volume (%) Slab thickness (mm) Flexural load at 1st crack (kN) Slab ultimate load (kN) Increase in flexural cracking load over plain (%) Increase in ultimate cracking load over plain (%)

0 139.7 108 135

N/A 133.4 122 201

0.5 131.8 167 220

0.35 131.8 141 228

0.48 131.8 143 195

0.32 131.8 135 174

–

13

54

31

32

25

–

49

62

68

44

28

slab testing, shown in Figure 1, was to determine the difference in flexural and ultimate capacity between plain and FRC slabs and the beam toughness parameter that could be used to predict the added benefit of fibers to plain concrete materials. The concrete slabs tested were 2.2 m by 2.2 m with a nominal thickness of 127 mm at approximately 56 days. The unique feature of each of the six slabs, which were tested under interior loading conditions, was the type of reinforcement: none (plain), crimped steel fibers, hooked end steel fibers, synthetic fibers, or welded wire reinforcement (see Table 2). Further details of the test setup, configuration, and loading can be reviewed in Roesler et al. (2004, 2006) as well as edge loading cases. The load versus deflection plot for the slabs is presented in Figure 2 for plain concrete, steel fibers, synthetic fibers, and WWR. The load-deflection responses of the slabs were similar up to the point where the first flexural crack occurred at approximately 2 to 3 mm of vertical deformation. The flexural capacity of the slab was defined when there was a sudden reduction in load carrying capacity of the slab. At this point, the bending resistance of the slab perpendicular to the flexural crack decreased dramatically. A second flexural crack developed at higher deformations, which can be seen as slab’s second peak load in Figure 2. The ultimate load capacity of the slab can be seen in Figure 2 as the maximum load achieved at any slab deformation level. The ultimate load was associated with either flexural cracking occurring on the top of the slab or punching shear failure. The load-deflection curves of the FRC slabs demonstrate an improved flexural and ultimate load capacity over plain concrete slabs as seen in Figure 2. The range of flexural load capacity of plain concrete slabs was increased between 25 and 54 percent with the addition of fiber-reinforcement, while the ultimate load capacity of the plain concrete slab was increased by 28 to 68 percent with fiber-reinforcement, as presented in Table 2. Even the WWR slab 720

250

225

Plain 0.48% Synthetic Fiber 0.32% Synthetic Fiber 0.35% Hooked End Steel Fiber 0.50% Crimped Steel Fiber

200

WWR

175

Load (kN)

150

125

100

75

50

25

0 0

1

2

3

4

5

6

7

8

9

10

11

12

13

Maximum Surface Deflection at the Slab's Center (mm)

Figure 2. Table 3.

Load versus deflection curves for interior loaded concrete slabs. Summary of strength and toughness results.

Compressive Strength (MPa) Flexural Strength (MPa) 150 (MPa) f150 150 R150 (%)

Plain concrete

0.50% Crimped steel FRC

0.35% Hooked end steel FRC

0.48% Synthetic FRC

0.32% Synthetic FRC

41.1

37.2

34.2

31.8

36.1

4.73

5.28

4.68

4.82

4.69

0

1.27

1.61

1.55

0.87

0

24.1

34.5

32.1

18.5

had a 13 percent increase in flexural capacity relative to the plain concrete slab. The slab with crimped steel fibers showed the greatest flexural cracking load, which was attributed to the high beam flexural strength (see Table 3). Altoubat et al. (2008) found that the normalized flexural and ultimate capacities, scaled for variations in concrete compressive strength and thickness, still showed the trends presented in Table 2. This significant improvement in the flexural and ultimate capacity of the fiber reinforced concrete slabs over plain concrete slabs can now be accounted for in the design of concrete pavements in terms of thickness reduction or longer joint spacing. 3.3 Concrete flexural beam and strength results Compressive strength cylinder (100 mm diameter × 200 mm) and flexural strength beam (150 × 150 × 450 mm) specimens were sampled at the same time the concrete slabs were cast as part of the previous study (Rieder 2003). The average 56-day strength results for each concrete mixture were re-analyzed and can be seen in Table 3. Despite the differences in w/c ratios and air content between the concrete mixtures, the peak flexural strengths were similar, 721

Figure 3.

ASTM C1609–07 flexural strength testing setup. 6 .35% Hooked End Steel Fiber

5

.50% Crimped Steel Fiber .32% Synthetic Fiber .48% Synthetic Fiber

Stress (MPa)

4

Plain

3

2

1

0 0

0.5

1

1.5

2

2.5

3

Beam Deflection (mm)

Figure 4. samples.

Beam flexural stress versus deflection curve for the plain and fiber reinforced concrete

with only 15 percent maximum variation between the mixtures. Previous findings have also demonstrated that there is no significant difference in the flexural strength of plain and fiberreinforced concrete (Shah et al. 1991); thus, an alternative performance-related quantity is required to demonstrate the toughness benefit of FRC over plain concrete in order to explain the FRC slab behavior. Figure 3 shows the loading configuration and specimen setup for the new ASTM C1609-07, which is the same configuration used for the previous FRC testing standard, ASTM C1018 (1997). Figure 4 presents the average flexural stress versus beam deflection curves for the plain, synthetic, and steel fiber-reinforced concrete beam specimens. The main advantage of FRC materials as measured by the beam test is in the post-peak softening response, as seen in Figure 4 for the various fiber types and volumes. Clearly, the plain concrete has little postpeak strength relative to the fiber-reinforced concrete mixtures. The behavior of the crimped 722

steel, hooked end steel, and 0.48% synthetic fiber mixtures are very similar in their post-peak performance. The improvement in the residual strength of fiber-reinforced concrete can be represented by the equivalent flexural strength, which was first defined in Japan (JCI 1983). The original load-deflection data acquired for this research was analyzed using ASTM C1018-97 and JCISF4 standards (Altoubat et al. 2008). The flexural beam data was re-analyzed with the new ASTM C1609-07 calculations and an explanation of the differences in the various standards can be found in Bordelon (2007) and Roesler et al. (2008). The equivalent flexural strength, 150 , from ASTM C1609-07 is defined as the post-cracking strength measured at a beam f150 deflection of 3 mm (for a 450 mm span). The equivalent flexural strength is calculated as follows: 150 f150 =

150 P150 S bh2

(1)

150 where, R150 is the load at a beam deflection of 3 mm, S is the span between the supports (mm), b is the width of the beam (mm) and h is the depth of the beam (mm). The equivalent 150 , has been defined by Roesler et al. (2008) and IDOT (2009) as flexural strength ratio, R150 150 the ratio between f150 and the concrete flexural strength (MOR): 150 R150 =

150 f150 × 100 MOR

(2)

150 physically represents the residual capacity of the fiber reinforced concrete after it R150 150 values for fiber-reinforced concrete specihas cracked relative to its peak strength. The R150 mens tested ranged from 18.5 to 34.5 percent, as seen in Table 3. Plain concrete fractures at approximately 1 mm beam deflection and therefore has an equivalent flexural strength value of zero. The equivalent flexural strength ratio value is conservatively correlated to the flexural load capacity of the slabs as seen in Table 2, especially when corrections are made for the strength and thickness of the concrete slab (Altoubat et al. 2008). The fiber types evaluated 150 150 values, except for the R150 value require different volume fractions to achieve similar R150 of 18.5% which was from the lower volume fraction (0.32%) of synthetic fibers. Altoubat et al. (2004) also have shown that the beam size chosen to do the testing can have a significant impact on the equivalent flexural strength ratio especially for steel fibers. Smaller specimen 100 (the superscript refers to the sample size 100 × 100 × 300 mm) values sizes show greater R150 and therefore overestimate the contribution of the fibers’ toughness to the plain concrete slab behavior.

4

DESIGN METHODOLOGY FOR FRC PAVEMENTS

Current design methods for concrete pavements (e.g., StreetPave 2005, FAA 1995, ARA 2007) calculate critical tensile stresses based on the Westergaard formulation (1926, 1948) or finite element analysis using medium thick plate theory assumptions. The thickness is selected based on limiting the ratio between the tensile stress in the slab and concrete’s flexural strength to an acceptable level for a given traffic level. The effect of fibers on the concrete’s MOR and compressive strength is minimal at volume fractions less than one percent (Gopalaratnam et al. 1991, Shah 1991). Therefore, the slab thickness for plain concrete and fiber reinforced concrete pavements would be the same given the same peak strength. A relatively new approach to include the effect of fibers in the design of pavement and slab-on-grade is to use a limit state design based on yield line analysis (Meyerhof 1962, Johansen 1972, Meda 2003) with safety factors to account for material and loading variability. The Concrete Society (2003) in Great Britain has published a design method based on yield line analysis for the design of slab-on-grade for industrial floors. FRC thickness design for concrete pavements based on yield line analysis is possible, but this is a radical change to the design methodology that pavement designers have used for decades. Furthermore, 723

other unsolved issues would need to be addressed in a yield line approach, such as how to adequately address fatigue, temperature curling stresses, and traffic wander. Finally, a new yield line approach would require significant work to implement into existing design guides and software. The new design approach suggested here modifies an existing input in any current concrete pavement design procedure, specifically MOR, to account for the known increase in the flexural capacity of FRC slabs over plain concrete slabs. Analysis of the results from the largescale tests and the beam flexural toughness tests (ASTM C1609-07) above suggested that the 150 value (Altoubat increase in the flexural capacity of the slab was directly related to the R150 et al. 2004). Table 2 summarizes the increase in flexural load capacity of the FRC slabs, 150 measured from beams in Table 3. This which correlate to the experimental values of R150 150 comparison suggests R150 is a reasonable indicator of the increase in the flexural capacities of the FRC slabs over those of the plain concrete, especially after a more rigorous analysis is performed to account for the variations in concrete strength and the thicknesses of the slabs 150 as a multiplier to the (Altoubat et al. 2008). The proposed design approach utilizes the R150 beam MOR value to obtain a new effective flexural strength for FRC (MOR*) that can be used as the material strength input in the design method: ⎛ R150 ⎞ MOR* = MOR × ⎜⎜1+ 150 ⎟⎟ 100 ⎠ ⎝

(3)

This proposed approach targets concrete pavement with low fiber volume fractions 150 between 15 and 50 percent, using 150 × 150 × 450 mm beams. (<0.5%) that produce R150 Further justification of this method can be found in Altoubat et al. (2008), Roesler et al. (2008), or Bordelon (2007). In order to demonstrate the effective strength approach effects on the thickness design of concrete pavements, a highway rigid pavement design example is presented using the AASHTO (1993) design guide. For the pavement design, a concrete MOR of 4.0 MPa at 28-days is assumed and synthetic fibers are added to the mixture to reduce the required slab thickness. A total of 0.45 percent of these same synthetic fibers by volume of concrete is 150 value of 30 percent. chosen to be added in order to achieve a R150 The design example inputs are the following: effective subgrade k-value of 54 MPa/m, 15 million design ESALs, load transfer coefficient of 3.0, drainage coefficient of 0.95, terminal serviceability of 2.5, reliability of 90 percent, standard deviation of 0.35, and concrete modulus of 28 GPa. The AASHTO method requires a slab thickness for plain concrete of 27.8 cm. With the effective strength approach, the design MOR* becomes 5.2 MPa 150 of 30 percent) and the required slab thickness is now 24.1 cm. The fibers have (for a R150 reduced the thickness requirements by 13 percent. An alternative view is that fibers can also increase the allowable ESALs to 37 million if the slab thickness is held constant at 27.8 cm. 150 value of 30 percent was also successfully run for The effective strength approach for a R150 several other rigid pavement design procedures, such as the FAA (1995) and PCA method for airports (Packard 1973), and gave approximately 15 percent thickness reduction. Increasing the flexural strength of the plain concrete (e.g., by reducing the water-to-cement ratio or increasing the cement content), could have also reduced the slab thickness. However, an increased flexural strength of the mixture would lead to a significantly more brittle structural system and would likely result in a higher probability of cracking relative to the FRC for the same thickness reduction. 5

FRC SPECIFICATION CONSIDERATIONS

There have been many fiber-reinforced concrete pavement projects designed and constructed over the past 30 years and several references discuss premature failures of FRC pavements (Packard & Ray 1984, Rollings 1993). Most reported failures in FRC pavements have occurred when engineers specified excessively large slab sizes, which resulted in premature 724

corner breakings, wide joint openings, and joint spalling. Pavement engineers need to perform a load–plus-curling analysis if fibers are going to be employed to increase the slab size. Furthermore, the maximum slab deflections and subgrade vertical stresses (Rice 1972) must be checked to avoid excessive deformations in the support layers that could cause other premature failure modes, especially when significant slab thickness reduction is realized. Punching shear must also be checked for thin slabs and small load contact areas (The Concrete Society 2003). The primary means for specifying FRC for the design of concrete pavements should be 150 value determined with ASTM C1609-07. Other toughness indices reported through the R150 in the literature have not been checked against field performances and will likely give dif100 value (equivalent ferent results than the method presented herein. For example, the R150 strength at 2 mm deflection measured on 100 × 100 × 300 mm beams) was shown to have much larger values for the three fiber types tested in this testing program (Altoubat et al. 2004) and thus would have resulted in larger reduction in the required slab thickness for the 150 values are recommended to be used in an effective strength examples given above. Only R150 150 value is a design design approach without further full-scale validation testing. The R150 parameter that should be obtained from a sufficient number of tests (minimum of three or four beam tests) to account for the statistical variation of the beam test results. With the proposed design procedure modifications, validation is currently under way using an accelerated pavement testing device. 6

CONCLUSION

Large-scale slab and flexural beam toughness tests have shown that structural fibers increase the flexural capacity of fiber reinforced concrete slabs compared to plain concrete slabs. Fiberreinforced concrete can be designed to have similar post-cracking performance regardless of 150 ) the fiber material, geometry or dosage alone. The equivalent flexural strength ratio ( R150 calculated from flexural beam toughness tests (ASTM C1609-07) conservatively predicted the increase in the flexural capacity of fiber-reinforced concrete slabs over plain concrete slabs. An effective flexural strength (MOR*) based on proportionally increasing the concrete 150 value was proposed to account for the contribubeam flexural strength (MOR) by the R150 tion of fibers to the concrete slab’s flexural capacity. The effective flexural strength approach incorporated into existing pavement design procedures allows for the benefits of fibers, primarily as a thickness reduction, but it could be utilized for modifying joint spacing. A design 150 value of 30 percent reduced the example showed plain concrete with fibers that has a R150 required slab thickness on a concrete pavement by 13 percent based on the AASHTO (1993) method. REFERENCES AASHTO. 1993. Guide for Design of Pavement Structures. American Association of State Highway and Transportation Officials. ACI Committee 360. 2006. Design of Slabs on Grade. American Concrete Institute, ACI 360R-06, Farmington Hills, MI. Altoubat, S., Roesler, J., Lange, D. & Rieder, K.-A. 2008. Simplified Method for Concrete Pavement Design with Discrete Structural Fibers. Construction and Building Materials 22(3): 384–393. Altoubat, S., Roesler, J.R. & Rieder, K.-A. 2004. Flexural Capacity of Synthetic Fiber Reinforced Concrete Slabs on Ground Based on Beam Toughness Results. Proceedings of The Sixth International Rilem Symposium on Fiber Reinforced Concretes-Befib 2004, Varenna, Italy 2: 1063–1072. ARA, (2007). Interim Mechanistic-Empirical Pavement Design Guide Manual of Practice. Final Draft. National Cooperative Highway Research Program Project 1-37A. ASTM. 1997. ASTM C1018-97: Standard Test Method for Flexural Toughness and First-Crack Strength of Fiber-Reinforced Concrete (Using Beam with Third-Point Loading). Annual Book of ASTM Standards, Section 4 Construction 02. Philadelphia, Pennsylvania: American Society for Testing and Materials International.

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ASTM. 2002. ASTM C33-02a: Standard Specification for Concrete Aggregates. Annual Book of ASTM Standards, Section 4 Construction 02. Philadelphia, Pennsylvania: American Society for Testing and Materials International. ASTM. 2007. ASTM C1609-07: Standard Test Method for Flexural Performance of Fiber-Reinforced Concrete (Using Beam with Third-Point Loading). Annual Book of ASTM Standards, Section 4 Construction 02. Philadelphia, Pennsylvania: American Society for Testing and Materials International. ASTM. 2008. ASTM C78-08: Standard Test Method for Flexural Strength of Concrete (Using Simple Beam with Third-Point Loading). Annual Book of ASTM Standards, Section 4 Construction 02. Philadelphia, Pennsylvania: American Society for Testing and Materials International. Barros, J. & Figueiras, J. 1998. Experimental Behaviour of Fibre Concrete Slabs on Soil. Mechanics of Cohesive-Frictional Materials 3: 277–290. Beckett, D. 1990. Comparative Tests on Plain, Fabric Reinforced and Steel Fibre Reinforced Concrete Ground Slabs. Concrete 24(3): 43–45. Beckett, D. 1995. Thickness Design of Concrete Industrial Ground Floors. Concrete 29(4): 21–23. Beckett, D. 1998. Thickness Design Methods for Concrete Industrial Ground Floors. Concrete 32(6): 12–16. Beckett, D. & Humphreys, J. 1989. Comparative Tests on Plain, Fabric Reinforced and Steel Fibre Reinforced Concrete Ground Slabs. Thames Polytechnic School of Civil Engineering, Report No. TP/B/1, Dartford. Beckett, D., Van De Woestyne, T. & Callens, S. 1999. Corner and Edge Loading on Ground Floors Reinforced with Steel Fibers. Concrete 33(3): 22–24. Bischoff, P., Valsangkar, A. & Irving, J. 2003. Use of Fibers and Welded-Wire Reinforcement in Construction of Slab on Ground. ASCE Practice Periodical on Structural Design and Construction, 8(1): 41–46. Bordelon, A. 2007. Fracture Behavior of Concrete Materials for Rigid Pavement Systems, M.S. Thesis, Urbana, IL: University of Illinois at Urbana-Champaign. Falkner, H., Huang, Z. & Teutsch, M. 1995. Comparative Study of Plain and Steel Fibre Reinforced Concrete Ground Slabs. Concrete International 17(1): 45–51. Falkner, H. & Teutsch M. 1993. Comparative Investigations of Plain and Steel Fibre Reinforced Industrial Ground Slabs. Institut für Baustoffe, Massivbau und Brandschutz, Technical University of Brunswick, Germany, No. 102. Federal Airport Administration. 1995. Airport Pavement Design and Evaluation, Advisory. Circular 150/5320-6D, Washington, DC: Federal Aviation Administration. Gopalaratnam, V., Shah, S., Batson, G., Criswell, M., Ramakrishnan, V. & Wecharatana, M. 1991. Fracture Toughness of Fiber Reinforced Concrete. ACI Materials Journal 88(4): 339–353. IDOT. 2009. Standard Method of Test For Flexural Performance of Fiber-Reinforced Concrete (Using beam and Third-Point Loading), Illinois Modified ASTM C 1609. Illinois Department of Transportation, Bureau of Materials and Physical Research. Japan Concrete Institute. 1983. Standard Test Method for Flexural Strength and Flexural Toughness of Fiber Reinforced Concrete. Japan Concrete Institute, Standard SF4: 45–51. Johansen, K.W. 1972. Yield line theory. London; C & CA Press. Johnston, C. & Zemp, R. 1991. Flexural Fatigue Performance of Steel Fiber Reinforced ConcreteInfluence of Fiber Content, Aspect Ratio, and Type. ACI Materials Journal 88(4): 374–383. Jun, Z. & Stang, H. 1998. Fatigue Performance in Flexure of Fiber Reinforced Concrete. ACI Materials Journal 95(1): 58–67. Lee, M. & Barr, B. 2004. An Overview of the Fatigue Behaviour of Plain and Fibre Reinforced Concrete. Cement and Concrete Composites 26: 299–305. Meda, A. 2003. On the Extension of the Yield-Line Method to the Design of SFRC Slabs on Grade. Studies and Researches, Vol. 24, Milano, Italy: Politecnico di Milano. Meda, A., Plizzari, G., Sorelli, L. & Rossi, B. 2003. Fracture Mechanics for SFRC Pavement. Concrete Structures: The Challenge of Creativity, CEB-FIP. Meyerhof, G. 1962. Load-Carry Capacity of Concrete Pavements. Journal of the Soil Mechanics and Foundations Division, Proceedings of ASCE 88(SM3): 89–116. Packard, R. 1973. Design of Concrete Airport Pavement. Engineering Bulletin EB050.03P, Skokie, IL: Portland Cement Association. Packard R. 1984. Thickness Design for Concrete Highway and Street Pavements. Skokie, IL: Portland Cement Association. Parkard, R. & Ray, G. 1984. Performance of Fiber-Reinforced Concrete Pavements. Fiber Reinforced Concrete. SP 81-16, American Concrete Institute, Detroit, MI: 325–349.

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Parker, F. 1974. Steel Fibrous Concrete for Airport Pavement Applications. Technical Report S-74-12, Vicksburg, MS: US Army Engineer Waterways Experiment Station. Ramakrishnan, V., Wu, G. & Hosalli, G. 1989. Flexural Fatigue Strength, Endurance Limit, and Impact Strength of Fiber Reinforced Concretes. Transportation Research Record 1226, Transportation Research Board: 17–24. Rice, J. 1972. Pavement Design Considerations. In Fibrous Concrete: Construction Material for the Seventies Conference Proceedings M-28. CERL: 159–176. Rieder, K.-A. 2003. unpublished beam data. W.R. Grace. Roesler, J., Altoubat, S., Lange, D., Rieder, K.-A. & Ulreich, G. 2006. Effect of Synthetic Fibers on Structural Behavior of Concrete Slabs on Ground. ACI Materials Journal 103(1): 3–10. Roesler, J., Bordelon, A., Ioannides, A., Beyer, M. & Wang, D. 2008. Design and Concrete Material Requirements for Ultra-Thin Whitetopping. FHWA-ICT-08-016. Urbana, IL: Illinois Center for Transportation. Roesler, J., Lange, D., Altoubat, S., Rieder, K.-A. & Ulreich, G. 2004. Fracture of Plain and Fiber-Reinforced Concrete Slabs under Monotonic Loading. ASCE Journal of Materials in Civil Engineering 16(5): 452–460. Rollings, R 1986. Field Performance of Fiber Reinforced Concrete Airfield Pavements. DOT/FAA/PM86/26, Washington, D.C: Federal Aviation Administration. Rollings, R. 1989. Developments in the Corps of Engineers Rigid Airfield Design Procedures. International Conference on Concrete Pavement Design, Purdue University, West Lafayette, IN: 405–418. Rollings, R. 1993. Curling Failures of Steel-Fiber Reinforced Concrete Slabs. ASCE Journal of Performance of Constructed Facilities 1: 3–19. Shah, S. 1991. Do Fibers Increase the Tensile Strength of Cement-Based Matrixes? ACI Materials Journal 88(6): 595–602. Sham, S. & Burgoyne, C. 1986. Load Tests on Dramix Steel Fibre Reinforced Concrete Slabs. A Report to Sir Frederick Snow and Partners, Consulting Engineers. Imperial College of Science and Technology, Department of Civil Engineering, Concrete Laboratories. StreetPave. 2005. American Concrete Pavement Association. Tatnall, P. & Kuitenbrouwer, L. 1992. Steel Fiber Reinforced Concrete in Industrial Floors. Concrete International 14(12): 43–47. The Concrete Society. 2003. Concrete Industrial Ground Floors—A Guide to Design and Construction. 3rd Ed. Technical Report 34. Van Dam, T. 1995. Use of Steel-Fiber Reinforced Concrete in Pavement Structures. Proceedings of the Transportation Congress, ASCE, San Diego, CA, 1: 477–488.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Using falling weight deflectometer data for new construction interactive design C.A. Lenngren Vectura Consulting, Borlänge, Sweden

ABSTRACT: The present paper is a case study of a new road construction project in Southern Sweden. Wet weather made static plate loading test impossible to conduct on the subgrade. Rather, FWD testing was carried out on unbound layer surfaces and the static plate load tests were then assessed from these tests. The conditions at the site continued to be wet and difficult and more tests were carried out on the subsequent layers. The asphalt bound base course was laid in June 2007. The final binder and wearing courses were placed in 2008 after a year in service. FWD tests were conducted at the site at no less than eight instances in different stages of the construction. The water present in the subgrade and subbase was found to slowly decrease over time. By backcalculating asphalt strain, the final asphalt layer thickness could be reduced without jeopardizing the strain criteria postulated in the code. 1

INTRODUCTION

1.1 Background Active design for road construction has been a much debated topic for well over two decades by now. The idea is to test as you build, adjusting for instance the thickness of an asphalt concrete base course layer. The reason for doing this may be that the contractor is more or less successful with finishing the unbound layers. More likely though is the fact that the natural soils and the environment vary much more than the design code can cope with. Typically, a soil is just categorized into a few types, like A to F for instance. Soil type, climate and perhaps drainage are the only parameters used for the design besides traffic. On the other hand, traditional contracts define a plethora of restrictions on the materials and methods being used. Just aggregates alone have restrictions of hardness, angularity, gradation, chemical properties et cetera. In the 1992 7th International Society for Asphalt Concrete conference, the key note speaker theme was “paving the gap” (ISAP 1992). The gap, having a wide interpretation range, could be perceived as different thinking amongst theorists and industry or users and administration. The gap could also be the difference between, the materials testing or component world on one hand; and the mechanistic or behavior world on the other. Certainly, the mechanistic tools have been around for some time now, but in the more than fifteen years that have passed since the abovementioned conference we have seen very little of active design in reality. It may have to do with the way contracts are made, referring to codes and regulations in use, leaving very little incentive for the contractor to do something different. The closest we get is through “functional criteria warranties” meaning that the builder or the builder’s associate maintain the road to an acceptable level for some time. Usually, the parameters used include roughness, rutting, and friction. Nevertheless, during the construction all the mandatory construction control procedures are present. Authorities are also prone to keep the regulations; after all it is human to play it safe. The best argument for a more mechanistic approach (and thereby foregoing control procedures) is actually for environmental reasons. Traditional codes imply so many redundant measurers that parts of the construction is “overdesigned,” i.e. it is heavier and demands more resources than called for. Still, the weakest part may fail prematurely so the “play it safe” method may not be enough anyway. 729

The present author has rather recently come across two interesting cases where alternate design was used. One involved much improved compaction on unbound layers allowing for reduced asphalt concrete thickness. It is described in a different paper. The other case is from a site where the conditions, rain on fine soils, rendered static plate loading (SPL) tests impossible. Rather, falling weight deflectometer (FWD) tests were used to backcalculate the former. The FWD data were also used to alter the design. Tests were made at no less than eight instances from the subbase to the finished surface. In addition careful evaluation of time history traces indicated excess water being present. 1.2 Design criteria The traditional mechanistic design criteria can be used for interactive design. However, one must be aware that the elastic model is rather crude and that you may have to deal with plastic deformation, moving water, and visco-elastic phenomena in the analysis. The classical criteria are always calibrated with a shift factor and situations far from the test bench may render erroneous results. Unlike active design controlling layer bearing capacity coefficients only, interactive design means that the whole structure is reconsidered as regarding critical strains and non elastic deformation. The ramifications for the model are important to understand. During construction subgrade strength is tested with a static load plate bearing test. It is to ensure that the foundation meets certain criteria as a minimum stiffness needed for the compaction of added layers. Since it is a load-deformation criterion it is easy to confuse this with the resilient modulus used for the mechanistic design. It is important to stress that it is not, the main reason being a different stress condition far from the elastic response. Further the conditioning of test interferes too much with the modulus derived from the test. As it is next to impossible to discern the various different deformation processes that occur, this type of test is not suitable for active design! Ideally, a test should simulate the built in-traffic conditions, but that is very difficult or expensive to simulate with overburden pressures et cetera. An FWD pulse is however close to loads caused by traffic and serves a better indicator of as-built subgrade strength than many other tests. By varying the load, stress sensitivity can be determined, and risks can be assessed for overloads and other scenarios. The design strains used in Sweden are the traditional ones. One for bound layer fatigue; and one for permanent deformation regressed to the top of subgrade strain. It is outside the scope of this presentation to discuss the validity of these criteria. The asphalt criterion is a modified Kingham relationship; the average temperature for either four or six season is used. For detailed information refer to the Swedish National Road Administration (SNRA) website, (SNRA 2009). 2

INTERACTIVE CONSTRUCTION

2.1 Marieholm bypass The project Marieholm bypass is an 8.5 km long rural two-lane undivided highway on National Route 17 in Scania in Southern Sweden. With a total length of 46 km Highway 17 is one of the shortest national routes in the country. It connects European highways 6 and 22 at a radial distance of 30–40 km north of Malmö. Most of the traffic consists of commuters from town Eslöv. Truck traffic is sparse, but occasionally high around harvest time. The design 10 ton traffic is 3.04 million axles. The location near the sea in southern Sweden means moderate temperatures in the summer and mild winters with a freezing index of about 50 degree days on the Celsius scale. For such conditions, the building code stipulates 500 mm of unbound material and 120 mm of hot mix asphalt concrete. The subgrade soil was classified as moraine clay. The engineering properties of this material are depending on the clay content. If the clay content is high enough usually a lime stabilization is called for. At this site the clay content reported was near but under the limit. A suggestion from the contractor to stabilize was turned down by the regional road authorities. 730

2.2 Early construction When the construction commenced in 2006 excessive precipitation in the summer rendered proper production control SPL testing on the subgrade impossible. Due to time constrains the contractor proceeded anyway; but as a backup extensive testing was done with an FWD on the subbase a few months later instead. The prepared surfaces seemed sufficiently even for the testing, even though a few percent of the tests had to be discarded. A segmented loading plate was used to further ensure an even pressure. Repeated loading at four different load levels ranging from 20 to 70 kN was performed and full time history samples were also recorded. Layer elastic moduli were backcalculated with CLEVERCALC 4.0 software. Thus, soil properties could be derived such as test results from other equipment could be simulated. The soil in this area consisted of clayey glacial till, which comes in a wide range of mechanical properties depending primarily on the clay content. Some of the earth from cuts was used as embankments. As it turned out the stiffness of the embankments was extremely low and the original design would not be sufficient from a bearing capacity point of view. There was a correlation between the stiffness of the subgrade and the subbase. This indicated that it is difficult to compact layers without sufficient support. The virgin subgrade however, turned out to be fairly stiff, so an assumption was made that the embankments would gain bearing capacity with time as the road materials dried up. So it was decided that more FWD testing should be done at least for each placement of a new layer. When the second test was carried out in November of 2006, it was evident that a section through a cut a showed better strength than the embankments. However, the embankments had improved their strength since the first test in October. The backcalculated moduli were still very low for the embankment and subbase and by analyzing time histories it was evident that free water was present in the soil. See Figure 2 showing a plot of load and deformation over time for two nearby sections but with different water contents. One is relatively drier then the other and the maximum deformation is about 2 mm for a 65 kN load. This corresponds to a 13 ton axle and the associated backcalculated moduli and strains are high but acceptable for the circumstance. The other section exhibited a very wet subbase and the peak deflection is over 5 mm. Note also how the peak deflection occurs some time after the load peak. The maximum load is also lower due to the yielding surface. Mind that the drop height is the same and thus the energy input is equivalent. More about the interpretation of time histories used in the present text can be found in (Hansson & Lenngren 2006).

Figure 1.

The first FWD test on the subbase showed very high deflections.

731

Figure 2.

Time histories of Do to reveal water present (large loop).

70 60 50 D0 D20 D30 D45 D60 D90 D120

Load [kN]

40 30 20 10 0 –500

500

1500

2500

3500

4500

5500

–10 Displacement [mu]

Figure 3. Time histories for seven sensors; note how sensor at 120 cm (leftmost curve) is pushed by moving water.

In Figure 3, plots of seven sensors are shown for the wet section. Outer sensors are actually pushed back upwards as the water is moving away from the loading plate. Needless to say it is rather meaningless to backcalculate elastic moduli with a layer model for such cases. If a linear layer elastic program is used anyway, the subgrade modulus (and strength) would be grossly overrated. The implications are of course large during such circumstances. It is also known from experience that roads across marshes and peat rich soils often exhibit very good performance. Thus, the liquid acts as damping deformation as a function of velocity. This is beneficial, but it goes beyond mechanistic design models used today. Software developers of pavement evaluation programs are recommended to check for time history curves that will reveal non linear behavior. Note also the rather rapid recovery after the maximum is reached, which may be affected by suction. 732

2.3 Recalculation of static plate load tests As mentioned in the introduction the contractor failed to take SLP tests on the subgrade needed for construction control. It was not possible to bring the equipment in question to the site due to rain and the slippery clay material. The test is performed by pushing a defined size metal plate by a regulated force towards the ground. A surface modulus Ev1 is then calculated as force per area unit. A second order power equation is used for given pressures. The procedure is repeated and a relation Ev2/Ev1 is taken as a measure of compaction. The procedure follows the German standards DIN 18134. The construction control stipulates a minimum surface modulus and on prepared surfaces also a minimum quotient. Five out of six samples must comply with stated criteria. There is a lot to discuss about the test which emanates from 1930’s Germany. Usually, a virgin mechanical test on anything has inherent test conditioning quirks. The specimen also has residual tensions from previous load history and there are several processes governing the behavior of deformation. Attempts have been made to correlate FWD data with SLP data, some successful others not. In addition to the conditioning predicaments, the latter cases are most likely due to dynamics and/or viscoelastic properties. Anyway, for the calculation of SLP tests on the subgrade measured as FWD tests on the subbase the following technique was used. The subbase layer and subgrade layer moduli were backcalculated. Four load levels were used as to check for stress sensitivity. The loads were repeated. The load was interpolated to correspond to the one from the SLP. Overburden of the subbase was calculated and the confining pressure was adjusted. The result was such as the subgrade likely would not have passed, or just barely passed the SLP test. It was evident that the original design would not suffice for the current conditions. The contractor then felt that more FWD testing should be done on all layers and a decision for a new design should be based on these data. 2.4 Design after bound base course being placed The western half of the 8.5 km project was scheduled to open for traffic in June 2007. Based on the FWD tests on the unbound base it seemed that about 220 mm of asphalt was needed to meet Swedish strain criteria. This was almost twice as thick as the original design stated (120 mm) and of course much more expensive than planned. At this point it was suggested to use a harder binder to better spread the load on the subbase and subgrade. It was also decided not to finish the surface with a wearing course, but let traffic on the binder course during the first year of traffic. There are two benefits to gain from this: 1. Traffic will do extra compaction where needed. 2. If unbound materials are indeed drying, a new thinner design can be determined later. There are risks involved here as well. Strains may be so large that a considerable amount of the fatigue life is used up during the first year; and the rutting rate may be too high so that ruts could be detrimental to traffic safety. Therefore, another FWD test was carried out after the placing of bound asphalt base layers. It showed that the bearing capacity was now adequate with a total asphalt concrete thickness of 180 mm, the reduction due to increased strength in the unbound layers. A thorough check ensured that the first year rutting would not be more than 13 mm, which is the rut depth when traffic safety is starting to be of concern. This check was based on the backcalculated top of the subgrade strain. This strain corresponds to a number of equivalent axle loads which was compared to the first year of traffic. As the road per definition is finished at 20 mm the rutting rate per axle can be decided. After assuming an initial rut depth of 3 mm the first year rutting could be determined by adding the two. In addition to the wait and see approach one 500 m long section was substituted with a polymer modified binder to check if the performance would improve. Other than that the additional 80 mm deficit (before placing the asphalt wearing course) remained. 733

3

BINDER COURSE TESTING

An FWD test was carried out in July 2007 on the bound binder course surface. This included the newly opened western part and the yet to open eastern part. It confirmed the deficit of 50 mm of asphalt previously established. On the eastern part there was a 60 m long stretch with very low bearing capacity though. 3.1 Embankment at risk On an embankment on the eastern half scheduled to open for traffic a month later in 2007 some very high deflections were recorded on the finished binder course. The embankment in conjunction with an underpass exhibited very poor bearing capacity. Not only were the deflections high, e.g. d0 almost 3 mm, but the subbase and base courses were too soft, likely due to poor support during compaction, see Figure 4. The values were so low that the contractor was recommended to replace a 60 m long section with new materials that should be carefully compacted to adequate values. Note that all sensors are behaving in the same fashion. A delayed response is followed by a sudden recovery. The material devoid of water is recovering and suction occurs. Likely, water at some depth from the surface is moving. Water near the surface would push the outer sensors up as shown in Figure 3. This was the only incident where placed material was removed, replaced, and redone. A rather costly operation, but based on the FWD data, the present author is quite convinced that this was definitely the location for such actions. The embankment was also a section where rutting likely could have exceeded 13 mm after the first year. Another spot was also identified further down the road but was left aside as it was a single occurrence. For more on early rutting detection refer to (Lenngren & Hansson 2004). The idea to finalize the design after the first year of traffic then stands out as quite attractive. If there indeed will be a stiffening of the materials, asphalt concrete can be spared for better purposes. If not, the negative aspects of having shallow rutting or some roughness could be adjusted properly anyway. A follow-up FWD test was scheduled for October. It would not only act as supporting the previous test, but it would also verify any seasonal variation of the materials. In addition, the asphalt concrete temperature would be much closer to the mean annual average. The test in July had to be done at night as there is an upper limit of 30°C pavement temperature for backcalculating bituminous materials in the Swedish test specifications, (SNRA 1998). The strains are calculated for an adjusted AC modulus at 15°C, or for the average

70

Load [kN]

50 D0 D20 D30 D45 D60 D90 D120

30

10

–100

400

900

1400

1900

2400

2900

–10

Deformation [mu]

Figure 4.

Extreme time history behavior forced some actions to be taken.

734

3400

of each of the six seasons. The length of the seasons is defined by dates. After the material was replaced the deflections decreased and no water affected the traces, see Figure 5.

4

WEARING COURSE DESIGN

The wearing course was planned to be placed in July of 2008 after a full year in service. The October 2007 FWD test was repeated in late April 2008 for the final design. The latter would also serve as a check-up of the development. In addition it would complement the seasonal variation data as the test would occur at the time closely after spring thaw. Figure 6 shows the backcalculated unbound layer moduli. E(2) is the subbase and unbound base combined and most of the basins exhibit wet, saturated material. The subgrade is also stiffer then for previous tests. The lowest values are found for embankments. 60

50

40 D0 D20 D30 D45 D60 D90 D120

Load [kN]

30

20

10

0 –100

0

100

200

300

400

500

600

–10

Deformation [mu]

Figure 5. 50-kN load on finished binder course on previously very wet sections; deflections are somewhat high but manageable. Rather wide but smooth curves indicate high damping in the unbound materials. 400 350 300

MPa

250 E(2) E(3)

200 150 100 50 0 24

1374

2625

4675 m

Figure 6.

Unbound layer moduli in October 2007.

735

7075

100

80

mm

60 Design AC 40

20

0 24

1374

2625

4675

7075

m

Figure 7.

Wearing course needed thickness of asphalt concrete based on October 2007 conditions.

Based on the backcalculated moduli asphalt concrete thickness design was established based on the design traffic. It is plotted in Figure 7. There is a significant difference between the western and eastern parts. The former, comprising sections up to about 2000 m need only a 40 mm wearing course, i.e. the 90 percentile is lower than 40 mm. The western part seems to need 80 mm though. The test in April did not change the result much. The asphalt concrete modulus was lower, but the mean temperature was higher. The modulus adjusted to the annual mean temperature (15°C) remained the same. The mean unbound layer modulus was also the same, but the subgrade modulus continued to increase from a mean of 150 MPa to 167 MPa. Based on this information it was decided to use a 40 mm thick wearing course and then use leveling masses diligently to make up for those sections that needed a thicker design. They coincided with those that were slightly rutted. A surface test showed up to 6 mm built on 400 m averages, on par with what to expect from bearing capacity analyses. 5

COMPLETION OF THE PROJECT

The final layer was laid in early July of 2008. A mandatory surface characteristics parameter test was done and only a few 20 m sections failed the 3 mm rut depth criterion for new roads. There were a few sections not meeting the International Roughness Index 1.785 mm/m criterion. All these were in conjunction with pavement joints. This result is quite normal for this type of project. 5.1 Final FWD test At the end of July in 2008 the FWD returned for the 8th time to do a final check-up of the three week old surface. The weather was hot and the measurement had to be done at night as was the case in July 2007. The result was quite astonishing as 100% of the 330 plus tests fulfilled the top of the subgrade criterion. 90% fulfilled the asphalt strain criterion which was set at 190 microstrain for the harder binder used for the base course. Of those failing, only four test points needed more than 30 mm and the worst section needed 64 mm. These results are actually quite normal for any project. It is rare that 100% fulfills all strain criteria at all times of the year. A distribution diagram is shown in Figure 8. The sections with the highest strains were identified and were traced to the embankment where the low subgrade support originally was identified. There was also an embankment nearby with strains slightly higher than the limit. These sections where inspected on a day after some heavy rain and standing water was found in the ditches, see Figure 9. It could be 736

80 60 40 20

mm AC

0 0.00 –20

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

–40 –60 –80 –100 –120 –140 –160

Figure 8.

Distribution of need for AC in mm; final outcome after completion.

Figure 9.

Standing water was found where bearing capacity was low.

that the subgrade is not regaining strength as soon as the other parts due to the water. Further testing could verify this, and maybe small drainage adjustments could help. 6

SUMMARY AND CONCLUSIONS

6.1 General thoughts Employing interactive design seems to be an appropriate and attractive alternative to traditional methods. It is not that easy to get full acceptance from all parties, regarding specifications, codes et cetera. Should all or just some material specs be fulfilled? It is possible to predict future properties of materials? Are all mechanistic criteria valid et cetera? For contract reasons it seems like some form of functional warranties are better 737

suited for this type of work procedure. Using classical strain criteria seemed to work fine with the present project. However, in this case only the asphalt strain became critical. The ill reputed top of the subgrade strain was not of concern here, and it might have been better to look at the deformation in each layer separately. 6.2 Equipment The present author recognizes the importance of validity of the equipment used for interactive design. When testing on subgrade and unbound layers care should be taken to calculate the stress levels correctly. The test must also be dynamic, considering the materials involved. Presently, the FWD is likely the best equipment for this purpose. On new roads inevitably there will be post-compaction by traffic. Test sequences must therefore be repeated several times to distinguish between type I and type II rutting. There is also a conditioning of test factor that has to be determined, which requires the test sequences to be repeated. Testing at different load levels is a great help in assessing not only material stress sensitivity, but also degree of compaction in unbound base layers. One experience derived from this project is that the FWD loading sequences should be done from lower to higher and higher to lower as well. The first sequences from low to high are for determining poor soil compaction. The high to low sequence is for a better assessment of stress sensitivity parameters. 6.3 Project specific The experience gained from the present project is that a thorough follow-up revealed changing conditions all the time. First, the original design seemed to be very far from the target strains needed for the specified amount of traffic. With exception for the spring tests, the subsequent FWD-tests showed the road gaining strength over time though. Although, the project incurred higher expenses than originally expected, the feeling is that the end product is indeed better. As regarding criteria, the asphalt strain criterion is conceptually direct and corresponded to conditions observed at the site. I.e. the highest strains calculated were found at the roughest and most rutted sections, even if the level was only little more than an initial one. The top of the subgrade criterion was not near critical in this particular case. It is probably the best single-parameter criterion for rutting, but with the more elaborated evaluation techniques and computer power available today, multi parameter input is possible and should be used. ACKNOWLEDGEMENT The author wants to express his gratitude to Rune Fredriksson at Svevia, Sweden who with great inspiration sponsored all eight FWD-measurements and evaluation. The latter fostered a new version of the software and has contributed to new ways of interpreting FWD data. REFERENCES Hansson J. and Lenngren, C.A. 2006 “Using Deflection Energy Dissipation for Predicting Rutting” Proceedings, 10th international Conference on Asphalt Pavements, Quebec, Canada. On CD-ROM available from ISAP. ISAP. 1992 “Proceedings of the 7th International Conference on Asphalt Pavements” Reports and Conclusion, Volume 5. Keynote Addresses, pp. 7–102. Lenngren, C.A. and Hansson J. 2004 “Comparing FWD Initial Tests with HVS Induced Initial and Long-Term Rutting”. Proceedings 2nd international Conference on Accelerated Pavement Testing, Minneapolis, MN USA. On CD-ROM. SNRA. 1998 Swedish National Road Administration “Deflektionsmätning vid provbelastning med fallviktsapparat” Metodbeskrivning 112:1998. Publikation 1998:80 [in Swedish, English translation available]. SNRA. 2009 Swedish National Road Administration Website http://www.vv.se/templates

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Appraisal of density-based field compaction control test validity J. Sadrekarimi & S. Seyyedi Department of Geotechnical Engineering, University of Tabriz, Tabriz, Iran

ABSTRACT: For many years, the usual method of soil compaction control has been the compaction test and density measurement. In this research, in order to assess engineering validity of the current control method, the deformability of equally compacted soil specimens were investigated. Fifteen samples of different soils were compacted to 100% according to standard Proctor effort and then consolidated one dimensionally. At each stress level, the odometer moduli of specimens were determined. Results show that under identical stress levels, there are significant differences in the deformability of various soils with equal degree of relative compaction. For stress levels below 400 kPa, 5 to 10 folds differences in moduli were observed. In clayey and sandy specimens, this difference increases to 7 folds. Results prove the necessity of modification of current standards in a way that the modulus and deformation characteristics of such soils are re-evaluated. 1

INTRODUCTION

One of the most important improvement methods of engineering properties of soils is compaction. The main purposes of compaction are to increase the bearing capacity through increasing the shear strength, reduce settlement, increase stiffness, and reduce permeability and potential against frost heave through reduction of void content. The most common way of compaction control is through comparing the field measured dry density to the laboratory maximum dry density. However, dry density and optimum moisture content are not necessarily indicators of soil mechanical properties. During compaction, soil mechanical porosities are improved by air removal. Many interpretations of the basic phenomenon have been put forward since Proctor did his pioneering studies. He stated that the effectiveness of any method of soil compaction is limited by the friction between the particles. His theory was that in a dry soil, a thin water film, held in place by surface tension, surrounds each particle. This capillary moisture develops frictional resistance between the particles making compaction difficult. The addition of water reduces the capillary forces, decreases friction, and causes slight expansion. Adding more water is thought to have a lubricating effect, aiding particle rearrangement. This effect continues until the moisture becomes just sufficient to fill almost all voids when compaction process is completed (Proctor, 1933). Proctor’s theory was put forward at a time when the concept of effective stress and the significance of pore fluid pressure were not widely known. Nowadays, the concept of lubrication as used by Proctor is no longer considered appropriate. Hogentogler (1936) and Buchonan (1942) accomplished some further researches based on proctor’s theory. Then pore water pressure and air pressure effect during compaction investigated by Hilf and Olson (1963), and finally soil micro structure effect at compaction process offered by Lambe (1958). Each of these theories states certain properties of soil compaction mechanism. However, with clay soils the soil structure effect is interesting. At equal densities, clays with flocculated structure have higher strength and greater penetration value than clays with dispersive structure. Dispersion counteracts the increase in strength gained with higher densities, which may explain why some soils lose strength when over-compacted (Lambe, 1958). Research studies carried out by Lambe and Whitman (1969), Hilf (1975), 739

and Mitchell (1976) showed that soil fabric and structure both affect soil compressibility such that a clay specimen compacted dry-of-optimum moisture condition is stiffer than the same specimen compacted wet-of-optimum moisture condition. In previous studies, compressibility and shear strength of sand was assumed independent of fabric and water content and restricted to compaction degree and void ratio (Mitchell et al. 1976), but new researches in this field indicate the more stiffness sand behavior at dryof-optimum condition as compared with wet-of-optimum condition under equal compaction degrees (David Carrier, 2000). Recently, new methods and research studies have been carried based on desired engineering properties of soil such as modulus and its stiffness; and tested practically, such as using soil stiffness gauge (Fiedler et al. 1998). Although these studies still are ongoing, it seems valuing of soil deformability and modulus is more suitable method for obtaining compaction purposes (Fiedler et al. 1998). It appears that specifying a defined degree of relative compaction for a field work in which soil is produced from different borrow areas is not reasonable enough, as there is no guaranty that equally compacted soils will perform similarly and produce the same deformability. This research aims to disclose extend of variations of mechanical performances of different soils compacted up to an identical relative compaction. 2

TEST PROCEDURE AND RESULTS

In order to comparing compressibility of equally compacted soils, 15 soil samples, produced from different borrow areas, were compacted to100% relative compaction according to standard Proctor method, and then were compressed one-dimensionally in an odometer apparatus for they deformability properties. The results of compaction tests and index properties are presented in Figure 1 and Table 1. To accomplish these tests, first at 1 kPa stress level, the swell potential due to inundation was determined by standard ASTM-method A. All clayey samples, except sample S4, swelled. Table 1.

Engineering properties of test soils.

Samples

Index

Soil name

S1

CL

S2

SP

S3 S4

SC CL

S5

CL

S6 S7 S8

SM ML CL

S9 S10 S11 S12

CH SM SM CL

S13

CL

S14 S15

SM SM

sandy lean clay poorly graded sand clayey sand lean clay with sand sandy lean clay silty sand sandy silt sandy lean clay fat clay silty sand silty sand sandy lean clay lean clay with sand silty sand silty sand

Amount of fine (%)

Amount of sand (%)

Liquid limit

Plastic index

Max dry density (kN/m3)

Optimum moisture (%)

66

33

37

21

15.7

17.5

6 45

94 55

– 51

– 30

15 14.7

5.4 22.8

73

27

44

26

16.5

20.4

60 45 68

40 55 34

32 32 22

16 8 3

17.1 15.1 15.5

15.0 23.8 17.0

67 94 23 33

32.6 6 77 65

35 55 – –

13 32 – –

15.2 16.2 16.5 17.8

22.5 17.6 16.8 14.5

70

30

37

19

16.8

19.5

71 48 30

29 52 70

34 26 –

15 3 –

16.3 16.1 16.6

19.0 19.0 11.9

740

1.8 1.75 1.7 Maximum Dry Density (gr/cm3)

S 11 S5

1.65 S 12

1.6 S 15 S 10

Gs = 2.8

1.55

S4

Gs= 2.7

S9

S 14

S 13

1.5

Gs= 2.6

S1 S7

1.45

S8

S2 S3

1.4

S6

1.35 1.3 2

4

6

8

10

12

14

16

18

20

22

24

26

28

Moisture Content (%)

Figure 1.

Compaction test curves of samples.

2.50 2.00

swell (%)

1.50 1.00 0.50 0.00 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

–0.50 –1.00

Samples Number

Figure 2.

Swell potentials of samples (Method A).

The results are depicted in Figure 2. Generally, swelling is observed at samples with plasticity index higher than 10%, but increasing plasticity index does not necessarily result in an increased swell. Having completed swell testing, the samples were consolidated up to 800 kPa normal stress and at each stress level the coefficient of volume compressibility mv was calculated. In order to compare compacted soils compressibilities, the Eo values were worked out using the following equation: E0′ =

1 mv

(1)

where mv and Eo are coefficient of volume compressibility and modulus of odometer, respectively. 741

v

1/m (kPa)

Figures 3a and b show the changes of odometer modulus 1/mv against stress. Figure 3a presents test results related to clayey soils (CL, CH, ML) and Figure 3b belongs to sandy soils (SM, SP, SC). It is observed that for clayey soil specimens, the ratios of maximum to minimum stiffness, corresponding to 25, 50, 100, 200, 400 and 800 kPa stress levels are 2.7, 2, 2.1, 2, 3, and 2, respectively. These ratios for sandy specimens are 7.3, 6.8, 2.7, 2.4, 3, and 3.3, respectively. The maximum and minimum odometer modulus values are shown in Table 2. In Figures 4a and 4b the ratios of mean to minimum odometer modulus and maximum to minimum odometer modulus of all 15 test soils, for 25, 50, 100, 200, 400, 800 kPa stress levels are shown. These ratios are 3.3, 2.3, 2.6, 1.8, 2.7, 1.7 and 10, 7.1, 6.5, 3.1, 5.1, 3.3, respectively. It is seen that at equal stress levels, there are considerable differences between test results, which indicate unequal deformability of identically compacted soils in practice.

Changes of 1/mv for clayey soils.

v

1/m (kPa)

Figure 3-a.

Figure 3-b.

Changes of 1/mv for sandy soils.

742

Table 2.

Maximum and minimum values of Eo.

Stress level (kPa)

Sample with Eomax

Sample with Eomin

25 50 100 200 400 800

S7 (16540 kPa) S7 (17210 kPa) S7 (17180 kPa) S10 (13140 kPa) S10 (18630 kPa) S10 (26690 kPa)

S15 (1650 kPa) S14 (2430 kPa) S1 (2640 kPa) S1 (4200 kPa) S13 (3650 kPa) S3 (8180 kPa)

4.0 3.5 3.0

Eave/Emin

2.5 2.0 1.5 1.0 0.5 0.0 25

50

200

100

400

800

stress (kPa)

Figure 4-a.

Ratio of Eave/Emin in samples.

12.0

10.0

Eave/Emin

8.0

6.0

4.0

2.0

0.0 25

50

200

100

400

800

stress (kPa)

Figure 4-b.

3

Ratio of Emax/Emin in samples.

SUMMARY AND CONCLUSIONS

It is shown that soil specimens compacted to an equal relative compaction do not necessarily manifest identical deformability. In most cases, equally compacted sandy samples show 743

higher stiffness than the clayey samples do. However, with sandy samples irregular behaviors may be observed particularly at stresses level below 200 kPa. Generally, the higher the stress level, the lower the stiffness difference. A logical relationship between the compressibility and index properties, maximum density and optimum moisture content, is not observed. It seems that soil fabric plays a dominant role during compaction. It seems that controlling compaction degree only through measuring of density is not a sufficient and well engineered criterion, because equal degree of relative compaction necessarily does not result in equal deformability. Accordingly, deformability based compaction control methods should be developed and utilized in modern engineering practice. REFERENCES Buchanan, S.J. 1942, “Soil compaction”. Proc. 5th Texas Conf. Soil Mechanics. David Carrier, W. 2000, “Compressibility of compacted a sand”. Journal of Geotechnical and Geoenvironmental Engineering, March 2000, pp. 273–275. Fiedler, S., Nelson, C., Berkman, E. and DiMillio, A. 1998, “Soil Stiffness Gauge for Soil Compaction Control”. Public Roads. Vol. 61, No. 5. Hilf, J.W. 1975, “Chapter 7: Compacted Fill”. Foundation Engineering Handbook, H.F. Winterkorn and H.Y. Fang, eds, Van Nostrand, New York, pp. 244–311. Lambe, T.W. 1958, “The engineering behavior of compacted clay”. Journal of the Soil Mechanics & Foundations Division, ASCE, vol. 84, N0 SM2, pp. 1655–1 to 1655–35. Lambe, T.W. 1958, “The structure of compacted clay”. Journal of the Soil Mechanics & Foundations Division, ASCE, vol. 84, N0 SM2, pp. 1654–1 to 1654–34. Lambe, T.W. and Whitman, R.V. 1969, Soil mechanics. Wiley, New York. Mitchell, J.K., Chatoian, J.M. and Carpenter, G.C. 1976, “The influence of sand fabric on liquefaction behavior”. Contract Rep. No. S76-5 to U.S army engineer waterways experiment station, Dept. of Civil Engineering university of California, Berkeley, Calif. Olson, R.E. 1963, “Effective stress theory of soil compaction”. Journal of the Soil Mechanics & Foundations Division, ASCE, vol. 89, N0 SM2, pp. 27–45. Proctor, R.R. 1933, “Design and construction of rolled earth dam”. Eng. News Record, pp. 245–248.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Continuous compaction control: Preliminary data from a Delaware case study F.S. Tehrani & C.L. Meehan Department of Civil & Environmental Engineering, University of Delaware, Newark, Delaware, USA

ABSTRACT: Continuous Compaction Control (CCC) and Intelligent Compaction (IC) systems show great promise for improving the efficiency of field compaction and revolutionizing the compaction control process. A number of recent studies on compacted granular soils have shown that real-time acceleration monitoring of vibratory compaction systems allows for effective evaluation of compacted soil stiffness, leading to improved field construction. Since vibratory compaction is generally not effective for fine-grained soils, machine drive power (MDP) compaction systems have been developed, and are in the process of being studied further. This paper presents preliminary results from a compaction field study performed in the State of Delaware using a MDP equipped CCC system. The effectiveness of continuous compaction control in this study will be assessed and compared with two in-situ evaluation techniques that are commonly used to measure soil modulus. 1

INTRODUCTION

Continuous Compaction Control (CCC) systems are data acquisition systems installed on compaction equipment that continuously collect real-time information about the operation and performance of the compactor (Thurner & Sandström 1980, Adam 1997, Adam & Brandl 2003). For vibratory compactors, the data that is often collected includes the vibratory frequency, the amplitude of the roller drum, and the speed of the roller (Adam 1997). For machine drive power based systems, the gross power that is applied by the compactor is typically recorded, in addition to other properties such as roller speed, roller acceleration, and the slope angle (White et al. 2005). Intelligent Compaction (IC) is a mechanism whereby CCC data is interpreted and used in real-time to adjust the operation of the compactor in an attempt to optimize the compaction process and to achieve more uniform soil compaction (Adam & Brandl 2003, Anderegg et al. 2006). Since the introduction of CCC and IC compaction equipment, several field studies have been conducted to evaluate the effectiveness and productivity of these new technologies (e.g. Thurner & Sandström 1980, Adam 1997, Adam & Brandl 2003, White et al. 2005, Peterson et al. 2006). In the early stages of development of these technologies, it was discovered that vibratory-based CCC and IC systems held significant promise for compaction of coarsegrained materials (e.g. Adam 1997, Adam & Brandl 2003). More recently, it has been noted that these vibratory-based continuous compaction control techniques are not as effective when dealing with finer-grained soils of the type that are commonly used in construction in many regions throughout the United States (White et al. 2005). As a result of this limitation, compaction equipment manufacturers have begun exploring the use of Machine Drive Power (MDP) technologies for real-time compaction control of fine-grained soils. Current MDP technology originates from the theory of terrain-vehicle systems (Bekker 1969), and utilizes gross engine power to determine the degree of compaction. This technology is advantageous because it does not rely on a vibratory mechanism for evaluation of compaction performance, which is more consistent with the way that fine-grained soils are commonly compacted (e.g. tamping compactors or sheepsfoot compactors). Given the potential promise of this new technology, it is possible that future IC/CCC equipment will contain both MDP and 745

vibratory-based measurement systems, which will allow for more effective compaction control in both granular and fine-grained materials. To evaluate the capability of recently developed MDP technology for quality control of road sub-base compaction, an experimental research study was conducted in the State of Delaware in the summer of 2008. Under carefully controlled conditions at a state borrow area site, a road sub-base test pad was constructed and compacted using a prototype Caterpillar CS56 vibratory smooth drum roller. This prototype roller was specially modified to allow for real-time MDP and CCV (Caterpillar Compaction Value) measurements, which permits independent and simultaneous evaluation of the degree of compaction of the soil. The soils utilized during this study were generally coarse-grained and well-graded in nature, with a general USCS classification of SW-SM. A variety of in-situ testing equipment was also used during construction of the road subbase test pad, to assess the effectiveness of each piece of test equipment, and to make recommendations regarding the use of this equipment for QA/QC when used in conjunction with CCC equipment. In-situ test equipment examined during construction of the test pad included the: light weight deflectometer (LWD), Geogauge, dynamic cone penetrometer (DCP), nuclear density gauge (NDG), electrical density gauge (EDG), and falling weight deflectometer (FWD). These in-situ tests were performed to provide independent validation of the CCC measurements, and to examine the relationships between the measured CCC data and in-situ tests that are commonly used during roadway sub-base construction. This paper presents preliminary results from the field study that was performed. For brevity, only a fraction of the measured data is presented herein, with a more comprehensive statistically-based analysis of this data to follow in future publications. Both MDP and CCV data are presented for each of the in-situ test locations. In-situ test results from the LWD and GeoGauge are also presented and discussed. Other in-situ test data are currently being analyzed, and will be presented and discussed in more depth in future publications. 2

MATHEMATICAL INDICATORS OF SOIL COMPACTION FOR IC SYSTEMS

According to Thurner & Sandström (1980), for vibratory IC systems the Compaction Meter Value (CMV) is calculated by dividing the amplitude of the first harmonic of the measured response acceleration at the compactor drum by the amplitude of the exciting frequency of compaction (Equation 1, Thurner & Sandström 1980). As the soil becomes stiffer, the amplitude of the first harmonic increases, causing a corresponding increase in CMV. For vibratory soil compaction, Caterpillar CCC equipment uses the Caterpillar Compaction Value (CCV), a commercially “branded” version of CMV (Equation 2, modified from Sandström & Pettersson 2004). Using C = 300 has become a commonly accepted and standardized approach for calculating CMV values from measured vibratory roller data (Sandström & Pettersson 2004, approach developed by Geodynamik). CMV = C

a (2ω0 ) a (ω0 )

(1)

where â(2ω0) = amplitude of the first harmonic of the acceleration response signal; â(ω0) = amplitude of the exciting frequency; and C = a constant value chosen to empirically scale the output CMV values to an easier-to-interpret range. ⎛ a ( 2ω0 ) ⎞ CCV = 300 ⎜ ⎜ a (ω ) ⎟⎟ 0 ⎝ ⎠

(2)

Machine Drive Power (MDP) is a mathematically-calculated value of power that isolates the internal resistance to compactor drum rolling that is provided by the soil (Equation 3, White et al. 2005, White et al. 2007). For a soil that is being compacted by drum rolling, as the degree of compaction increases, the underlying soil becomes denser, the energy consumed to propel the roller (the gross power needed) decreases, and the MDP decreases. 746

a MDP = Pg − WV (sinθ + ) − ( mV + b ) g

(3)

where Pg = gross power needed to move the machine; W = roller weight; V = roller velocity; θ = slope angle; a = acceleration of the machine; g = acceleration of gravity; m and b = machine internal loss coefficients specific to a particular machine). Equation 3 gives the traditional definition of Machine Drive Power, which will be referred to as MDP1 from this point on in this paper. As noted above, values of MDP1 get smaller with improved soil compaction, which is the opposite trend from what is observed with CCV values, as well as increasing values of dry density, modulus, percent Proctor compaction, etc. This downwards MDP1 trend with improved compaction has the potential to cause confusion for equipment operators and field engineers. Consequently, the prototype CS56 roller presents measured machine drive power values using MDP2, a Caterpillar proprietary relationship that is directly calculated from MDP1 values by the data acquisition system using Equation 4. In the prototype CS56 compactor, MDP2 values are displayed directly to the operator, and output in the resulting machine data file upon completion of compaction. In order to compare the results of this study with data collected by other researchers (e.g. White et al. 2007), MDP1 values were back-calculated from the machine output data (MDP2) using Equation 5. MDP2 = −

150 ⋅ MDP1 + 150 54.23 kW

⎛ 54.23 kW ⎞ MDP1 = ⎜ − ⎟ (MDP2 − 150 ) ⎝ 150 ⎠

3

(4)

(5)

PROJECT DESCRIPTION

The CCC field study described in this paper was conducted at Burrice Borrow Pit in Odessa, Delaware (USA) in July 2008. A 61 m long by 6 m wide (200 ft by 20 ft) embankment was built out of a well-graded sand with silt (SW-SM), a commonly used borrow material for the Delaware Department of Transportation, which conforms to DelDOT class G borrow specifications, Grades V and VI. This embankment was constructed to an approximate total final height of 0.9 m (3.0 ft), by compacting five 20.3 cm (8 in.) loose lift layers, in accordance with Delaware general specifications for road sub-base construction (DelDOT 2001). To construct each lift, a Caterpillar 980H bucket loader was used to place fill for spreading by the on-site bulldozer, as shown in Figure 1a. A Caterpillar D6K dozer was then utilized for spreading the material to an approximate loose-lift thickness of 15 cm (8 in), as shown in Figure 1b. The D6K dozer was equipped with a GPS system, which proved beneficial in establishing a more uniform loose-lift thickness. Two methods were used to verify the expected loose-lift thickness of each lift; during fill placement the dozer operator checked it via the GPS control system mounted on the dozer blade, after lift completion the thickness was confirmed by spot-checking elevations throughout the test pad area using a GPS rover unit. After spreading each lift, a water truck was driven through the test area as needed to adjust the moisture content of the fill material to achieve optimum compaction (see Figure 1c). Upon completion of loose lift soil placement and moisture conditioning, each soil lift was compacted using a Caterpillar CS56 vibratory smooth drum roller (see Figure 2). This prototype machine has been specially modified by Caterpillar research engineers to measure both MDP and CCV values simultaneously, while also using an on-board GPS system to accurately establish the location of the compactor as it makes in-situ measurements. The roller drum was 2.1 m (7 ft) wide with an operating weight of 11414 kg (25164 lbs). Compaction was performed using both low and high amplitude vibration (0.85 and 1.87 mm) at a vibratory frequency of about 31.9 Hz (1914 vibrations per minute). Typically, to speed up the compaction process, 747

Figure 1. Constructing the test pad; (a) placing the fill material for spreading, (b) spreading the fill material, and (c) adjusting the moisture content to optimize field compaction.

Figure 2. Caterpillar CS56 compactor; (a) front-left view, (b) side view, and (c) preparing to compact on the test pad.

high amplitude compaction was performed on the loose materials in the first pass for each layer, and the following passes were performed using low amplitude compaction. This approach was used to prevent overcompaction and to generate CCV values that were more representative of the layer that was being compacted (this was necessary because higher amplitude compaction causes the measured CCV values to be more affected by the stiffness of underlying soil layers). MDP and CCV values were collected approximately every 30 cm (1 ft) along the length of the test sections. The working speed of the roller was about 3.2 km/h (2 mph). Using the modified Caterpillar CS56 compactor, each lift was compacted in a series of passes using three side-by-side lanes (the roller width was 2.1 m (7 ft), the test pad width was 6 m (20 ft), which left approximately 15 cm (6 in) of overlap at the edges of each compacted soil “lane”). For each lift, between 6 and 9 compactor passes were performed to achieve the desired level of compaction (target dry unit weights > 95% of the maximum dry unit weight obtained from a 1-pt Standard Proctor test, used with a “family of curves” compaction approach). During compaction, a computer screen in the cab displayed real-time MDP and CCV measurements to the roller operator using a color coded map. Once relatively little change in MDP value was observed by the operator, compaction for a given lift was stopped. The number of compactor passes that were performed to achieve compaction in this study are consistent with the level of compactive effort that is typically required to meet the current DOT dry-density specifications, based on technician experience with this borrow soil at other field construction projects (DelDOT representative, personal communication). During this study, additional in-situ testing was performed for the base materials underlying the test pad and at the completion of the final compactor pass for each lift. In addition, for the 5th lift, in-situ tests were performed after the 1st, 2nd, 3rd, 5th and 7th passes (7 passes total for this lift). For each lift, 19 test stations were established at ≈ 3 m (10 ft) intervals along the centerline. For the 1st, 2nd, 3rd, and 5th passes of lift 5, a reduced in-situ testing plan was followed, to speed the rate of in-situ testing so the compactor could return to the lift quickly before a significant change in water content could occur. For each in-situ testing series, confirmation of in-situ test locations was performed using the GPS rover unit. Six types of in-situ tests were performed at various test locations during this study, including the: light weight deflectometer (LWD), GeoGauge, nuclear density gauge (NDG), electronic density gauge (EDG), dynamic cone penetrometer (DCP), falling weight deflectometer (FWD), and sand cone testing. Each test series was accompanied by disturbed soil sampling, for later 748

determination of the moisture content, particle size characteristics, and Proctor compaction curve. The order of in-situ tests was adopted based on the effect that soil disturbance could have on the in-situ test results. In general, the in-situ tests above are listed in the order in which they were performed at each location. To accomplish each test series a slight test location offset was performed with respect to previous test locations, to minimize the influence of prior soil sampling for underlying layers on the in-situ test results for the soil layer that is being tested. 4

RESULTS AND DISCUSSION

This paper presents preliminary test results from the field study that was performed. For brevity, focus will be given to presenting specific point data from the CCC equipment for the 5th lift, and the corresponding in-situ test data measured using the 300 mm LWD and the GeoGauge. Results from other in-situ tests will be presented in a future publication. For comparison with point-specific in-situ test data, CCC equipment outputs recorded within a 1-second time interval were spatially averaged to obtain a representative value using the approach shown in Figure 3. Using this approach, the first step was to identify the closest “Roller Measured Point” (a point where both CCV and MDP values were recorded) to a given in-situ test point. The next step was to identify other Roller Measured Values recorded within the same time stamp in the data file (a time stamp within 1 second), which are associated with the Roller Measured Point reading because of their extremely close proximity. The authors felt that these values, which were essentially recorded at the same time as the closest Roller Measured Point value, should be factored into the final Roller Measured Point value that was used for comparison with the in-situ tests. To address this issue, the series of Roller Measured Values recorded within the same second as the closest Roller Measured Point were averaged using the spatial averaging technique shown in Figure 3. The result was a single Roller Measured Point Value that was used for comparison with the in-situ test data. Figures 4 and 5 show the variation of MDP1 and MDP2 at each station for successive compactor passes of lift 5. As shown in these figures, additional compactive effort consistently decreased MDP1 and increased MDP2. This overall trend is consistent with what is predicted by the theory of MDP—as the soil compaction increases, the roller drum “sinkage” decreases, leading to less gross power consumption and lower MDP1 values with successive passes. For each pass, some variability in the recorded MDP values was observed, which may be caused by variability in the soil test pad, soil test point location, and possible variability and sources

Figure 3.

Spatial averaging approach employed for single-point analysis of CCC data.

749

of error in the machine input measurements that are used to calculate MDP. For the final pass (Pass 7), greater variability in MDP values was observed. This is almost certainly caused by variability in the soil test pad, which will be shown in more detail later in this paper. Figure 6 shows the variation of CCV at each station for successive compactor passes of lift 5. As noted in Section 3, during the first pass, high-amplitude vibration was applied to compact the soil. Passes 2 through 5 and Pass 7 used lower-amplitude vibration for more efficient compaction and measurement of more accurate CCV values. Higher amplitude vibration transfers compactive energy deeper into the subsurface; consequently, real-time measurements of vibratory compaction (in this case CCV) are more affected by the underlying soil conditions. For this site, the foundation soil was quite stiff, which caused the CCV values for Pass 1 to be higher than they would have been if a lower amplitude vibration had been used for compaction. Therefore, when interpreting the results from Figure 6, Pass 1 should be considered separately from Passes 2–7. If Pass 1 is neglected, the results from successive passes show a clear trend of increasing CCV value with increasing number of compactor passes. As was the case with MDP, some variability is observed in the measured CCV results, possibly caused by variability in the soil test pad or variability and sources of error in the machine input measurements that are used to calculate CCV. Figures 7 and 8 show the variation of modulus values measured using the 300 mm LWD and the GeoGauge at each station for successive compactor passes on lift 5. As shown in these 2 figures, modulus values measured using the GeoGauge are significantly higher than those

Figure 4.

Variation of MDP1 for sequential passes at lift 5.

Figure 5.

Variation of MDP2 for sequential passes at lift 5.

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measured using the 300 mm LWD. In addition, significantly more variability was observed with the measured GeoGauge data than with the LWD data, indicating that the test may be more sensitive to subtle factors such as operator experience (in the case of GeoGauge) or slight variability in the in-situ test location. It was expected that more compactor passes would result in a clear trend of higher in-situ modulus measurements for the LWD and GeoGauge. However, as shown in Figures 7 and 8,

Figure 6.

Variation of CCV for sequential passes at lift 5.

Figure 7.

Variation of LWD measured modulus for sequential passes at lift 5.

Figure 8.

Variation of Geogauge measured modulus for sequential passes at lift 5.

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this increasing trend was not as obvious for the in-situ test data as it was for the MDP and CCV values measured using the CCC equipment. This discrepancy may be due to increased sensitivity of the in-situ test equipment to the location of the in-situ test on the test pad (there was small variability in in-situ test location to minimize the effect of prior sampling on the measured results). Nonuniformity of compaction on the test pad, spatially varying water contents, and operator error may also contribute to the observed variability in measured results. Interestingly, the CCC equipment tends to give more consistent test results for pointspecific analysis of compaction for each pass than the in-situ test equipment does. This trend is consistent for both the MDP and CCV continuous compaction control techniques. A comparison between the measured in-situ test data and the compactor MDP1 value is shown in Figure 9. A comparison between the measured in-situ test data and the compactor CCV value is provided in Figure 10. At face value, it appears that a strong correlation between the in-situ tests that were conducted and the measured values of MDP and CCV does not exist. In any case, this relationship is certainly not linear in nature, and a more sophisticated statistically based analysis approach is warranted. Future data analysis will go in this direction, and will look to incorporate test results from the other in-situ tests that were performed to develop a clearer understanding of the phenomena involved. It is important to note here that continuous compaction control data will likely be better analyzed using broader statistical tools, given the large amount of spatially varying data that is recorded

Figure 9. lift 5.

Comparison of LWD and GeoGauge measurements with MDP1 for sequential passes on

Figure 10. lift 5.

Comparison of LWD and GeoGauge measurements with CCV for sequential passes on

752

Figure 11.

Continuous vs. spatially averaged MDP1 data for pass 7 on lift 5.

Figure 12.

Continuous vs. spatially averaged CCV data for pass 7 on lift 5.

by the compaction equipment. As an example of this variability, refer to Figures 11 and 12 for a continuous plot of MDP1 and CCV data along the centerline of the final pass for lift 5. For comparison purposes, the spatially averaged data points are included on these plots. (Note that deviations in test point values from those points located on the centerline are a result of the spatial averaging technique that was employed). Clearly, the effect of spatial variability is quite significant. These figures also illustrate the limitations of the point-specific data that is generated when conducting in-situ tests for compaction control. To understand this type of continuous compaction data better, more advanced techniques are needed; these techniques will be discussed further in future publications. 5

CONCLUSIONS

This paper describes an experimental study that was performed to evaluate the efficiency and reliability of CCC technology for compaction of a common Delaware borrow soil. This study included the construction of a test pad using a prototype “CCC compactor” that had been equipped with both MDP and CCV measurement systems. A variety of in-situ tests were also performed to evaluate their ability to be used as confirmatory tests for third-party compaction control of field projects that use continuous compaction control test equipment. Locations of the compactor measurements were established using precise GPS control, which allowed for accurate location-specific comparison with in-situ testing results. 753

This paper presents the CCC results from the final lift that was constructed, in conjunction with the corresponding LWD and Geogauge in-situ test results. Preliminary evaluation of test results shows a clear trend of decreasing MDP1 values and increasing MDP2 and CCV values with increasing number of compactor passes. This illustrates the potential effectiveness of both the CCV and MDP approaches for compaction control using this fill material. When interpreting CCC data, it is important to note that CCV values are affected by the amplitude of the input vibration, due to the effect of energy penetration to underlying soil layers. The LWD and GeoGauge in-situ test results showed more variability than the CCC results, and appeared to be more sensitive to the test location that was chosen. In general, modulus values measured using the GeoGauge were higher than those measured using the LWD. Additional analyses of the CCC data and in-situ test data are needed for a more comprehensive understanding of the complex interactions and behavior shown in each of the measured data sets. ACKNOWLEDGMENTS Funding for this research was provided by the Delaware Department of Transportation. The authors would like to express their deep gratitude to the Delaware Department of Transportation; Caterpillar, Inc.; Greggo & Ferrara, Inc.; Kessler Soils Engineering Products, Inc.; and Humboldt Inc., for supporting this study with valuable manpower and equipment donations. In addition, the authors would like to thank Jim Pappas, Nikki Ferrara, Jim Reynolds, Al Strauss, Dean Potts, Richard Costello, AJ Lee, Nick Oetken, Ken Kessler, Mario Souraty, Ed Hall, Adam Houghton, Dan Sajedi, and CJ Swank for their valuable assistance with the field study and associated data analysis. And finally the authors would like to express their gratitude to the geotechnical graduate students at the University of Delaware who patiently helped us to accomplish our field work in a timely fashion: Farshid Vahedi Fard, Majid Khabbazian, Yueru Chen, Baris Imamoglu and Fan Zhu. REFERENCES Adam, D. 1997. Continuous Compaction Control with vibratory rollers. GeoEnvironment 97, Rotterdam 245–250. Adam, D. & Brandl, H. 2003. Sophisticated roller integrated continuous compaction control. 12th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering.Vol: 1. Singapore: World Scientific. 427–430. Anderegg, R., von Felten, D. & Kaufmann, K. 2006. Compaction monitoring using intelligent soil compactors. Proc., GeoCongress 2006: Geotechnical Engineering in the Information Technology Age, February, Atlanta, CD-ROM. Bekker, M.G. 1969. Introduction to Terrain-Vehicle Systems. An Arbor, Michigan: the University of Michigan Press. DelDOT. 2001. Specifications for Road and Bridge Construction, August 2001. Prepared by The Delaware Department of Transportation, Nathan Hayward III, Secretary & Raymond M. Harbeson, Jr., Chief Engineer. Peterson, D.L. Siekmeier, J. Nelson, C.R. & Peterson, R.L. 2006. Intelligent soil compaction technology. Transportation and research record. Vol: 1975. 81–88. Sandström, A.J. & Pettersson, C. B. 2004. Intelligent systems for QA/QC in soil compaction. TRB 2004 Annual Meeting (CD-ROM). Transportation Research Board. Washington, D.C Thurner, H. and Sandström, Å. 1980. A new device for instant compaction control. Proc., Intl. Conf. on Compaction, Vol. II, 611–614, Paris. White, D.J. Thompson, M. & Vennapusa, P. 2007. Field Validation of Intelligent Compaction Monitoring Technology for Unbound Materials. March 2007. White, D.J. Jaselskis, E.J. Schaefer, V.R. & Cackler, E.T. 2005. Real-time compaction monitoring in cohesive soils from machine response. Transportation Research Record, Vol: 1936. 73–180. White, D. & Thompson, M. 2008. Relationships between in-situ and roller-integrated compaction measurements for granular soils.” Journal of Geotechnical. and Geoenvironmental Engineering, ASCE, Vol: 134. 1763–1770.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Geostatistical analysis of roller-integrated continuous compaction control data N. Facas & M. Mooney Division of Engineering, Colorado School of Mines, Colorado, USA

R. Furrer Division of Mathematics & Computer Science, Colorado School of Mines, Colorado, USA

ABSTRACT: This paper explores the univariate and geostatistical representation of roller integrated continuous compaction control data. Univariate statistical analysis shows how the selection of the evaluation area leads to asymmetry in the data distributions that is inconsistent with regression analysis and can lead to QA failure. Geostatistical analysis reveals the presence of anisotropy. 1

INTRODUCTION

It has long been understood that soil properties (e.g., roadway subgrade, embankment, slope, earth dam) vary spatially, and that a probabilistic approach to characterizing soil behavior and performing analysis of geostructures is more appropriate than a deterministic approach. One practical hindrance to the probabilistic approach has been the lack of sufficient geospatial data to properly characterize the variability in soil properties. In earthwork compaction, however, the combination of roller-integrated measurement of soil stiffness/ modulus coupled with GPS-based geo-location, together called continuous compaction control (CCC), provides extensive data and thus enables a probabilistic based approach to soil characterization and analysis. The statistical techniques to characterize the nature of geospatial data are fairly well developed (e.g., Cressie 1993, Chiles & Delfiner 1999) and have been used in geotechnical engineering (DeGroot & Baecher 1993, Baecher & Christian 2006). Geostatistical methods have also been applied to roller-integrated CCC data (Petersen et al. 2007, White et al. 2007). These efforts proposed the use of geostatistical representation of CCC data as a method to improve quality assurance of earthwork compaction. They posited that the variogram properties provide a useful representation of the data that can be used to measure the compaction quality. This paper explores the analysis of spatial data collected during soil compaction of multiple earthwork layers using roller-integrated CCC. The pertinent statistical characteristics behind roller measurement values (MVs) and GPS coordinates are explained, e.g., sampling and spatial resolution, error and precision. Univariate statistics are first used to characterize the data. Spatial structure of the data sets is examined using semi variogram analysis and statistical modeling. Spatial correlation, underlying trends in the structure and measurement error are explored. 2

ROLLER INTEGRATED CCC DATA

2.1 Instrumented rollers Two smooth drum vibratory roller compactors outfitted with vibration-based soil stiffness measurement systems and GPS-based positioning were used in this study (see Fig. 1). The principle behind the vibration-based measurement of soil stiffness for these two rollers is 755

Figure 1.

Summary of instrumented vibratory roller compactors and machine parameters.

described elsewhere (Kröber et al. 2001, Anderegg & Kauffmann 2004, Mooney & Adam 2007). Each roller was outfitted with a GPS receiver. Combined with a base station used on the project, real-time kinematic GPS with position accuracy on the order of 1–2 cm was achieved. 2.2 Spatial data The two rollers were used to compact a 12 m wide by approximately 250 m long section of earthwork material. One layer of subgrade soil (USCS CL) ranging in thickness from 200–300 mm was placed atop the subsurface (USCS CL) and compacted. A 150 mm thick layer of aggregate base (USCS SP) was then placed atop the subgrade. When compaction was complete, the two rollers were used to map (i.e., proof roll) the surface of each layer. Figure 2 presents the spatial data collected by the Ammann roller for three layers, namely the subsurface material beneath the placed subgrade, the subgrade, and the base course. Figure 3 presents the spatial data collected by the Bomag roller on the subgrade and base layers. These maps are divided into two areas, cell 1 and cell 2, because they were constructed separately and exhibited different characteristics. Figures 2 and 3 illustrate the discrete nature of roller-measured soil stiffness. Each value of ks or Evib is representative of an area equal to the width of the drum (2.1 m) by approximately 0.5–1.0 m in the direction of roller travel. The spatial characterization of these data will be described in Section 4. A few features are worth 756

Figure 2. Spatial map of Ammann roller-measured stiffness for (a) subsurface, (b) subgrade, and (c) base course.

Figure 3.

Spatial map of Bomag roller-measured stiffness for (a) subgrade and (b) base course.

highlighting here. First, roller MVs vary considerably across the site and are lower in cell 1 than in cell 2. Roller-measured stiffness reflect soil information to depths of 1.0 m or greater (Rinehart & Mooney 2009). Therefore, the low stiffness observed in the subsurface cell 1 carries through to the cell 1 subgrade and base course stiffness maps. 757

3

UNIVARIATE STATISTICS

Compaction QA specifications using roller-integrated CCC data often involve regression-based relating of spot test data (e.g., density, plate load test modulus) to roller MV in a calibration area. The resulting relationship between roller MV and spot test value is then used in a larger production area to perform QA. Acceptance is based on a comparison of roller MV statistics (mean, standard deviation) with target criteria. It is implied that the statistical nature of roller MV data in the production section is similar to that in the calibration area. When performing the calibration, a classical regression analysis requires symmetric errors around zero and, hence, the roller MV data in both the calibration area and the production evaluation sections should be checked for symmetry around the mean. Over large spatial areas, MV data can become right skewed as shown in Figure 4a. This skewed distribution results from the large scale stiffness change from cell 1 to cell 2 (Figure 2). However, when considering individual cells, the data is often close to symmetric, often even close to normal distributed, as illustrated in Figures 4b and 4c. Table 1 provides the mean and standard deviation of roller MV data sets for subsurface, subgrade and base layers. The COV for combined cells 1 and 2 can often be quite large as a result of the large scale structure. The COVs for combined cells range from 20–35% (average = 32%) and can result in QA failure, e.g., the COV must be less than 20% in the ISSMGE recommended specification (Adam 2007). On the other hand, the more symmetric individual cells exhibit less variation, e.g., average COV = 22%. Univariate statistics help to identify individual very low (or high) MVs—so-called outliers— that should be eliminated from the analysis (see for example, Figure 2, subgrade cell 2). The very low values in the right part of the lower most pass of base cell 2 are clearly reflected in Figure 4c. Addressing such particular features is of interest. When ignored, the mean and standard deviation decreases and increases, respectively, and hence the quality of the overall cell seems much lower, i.e., the entire cell may fail quality assurance compared to a small subset only.

Figure 4. Table 1.

Histograms (points) and PDF (lines) for Ammann (a) Subsurface (b) Subgrade (c) Base. Means and standard deviations for the individual layers and for different cells. Ammann ks (MN/m) Cell 1

Bomag Evib (MPa)

Cell 2

Cell 1+2

Cell 1

Cell 2

Cell 1+2

Layer

μ

σ

μ

σ

μ

σ

μ

σ

μ

σ

μ

σ

Subsurface Subgrade Base

30 21 19

4 4 3

38 34 28

7 6 8

35 25 24

7 8 7

28 40

11 9

54 66

9 21

42 57

17 22

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4

GEOSTATISTICS

4.1 Background The visual representation of roller MV data in the x-y plane presented in Section 2.2 provided a first impression of spatial structure of roller MV data. We now discuss a quantitative approach to characterize the spatial relationship within the data. The structure of a spatial field can be quantified through the similarity between two spatial locations, as for example defined by the difference of the observed MVs. For a spatial field consisting of random elements Z(x) where x is the spatial domain (in our case an individual layer), similarity is given by the semi variogram function γ(h) as: γ(h) = Var(Z(x) – Z(x+h))/2

(1)

where Var( ) denotes the variance. Practically, if we have a set of n observations z(x1), …, z(xn), we plot the square difference [z(xi) – z(xj)]2/2 versus the distance between xi and xj. The empirical (or experimental) semi variogram (or simply variogram) is a best fit smooth line through this scatter-plot as shown in Figure 5. The quantifiable and useful semi variogram parameters include the range, sill and nugget effect. For small distances h, we expect a small values of γ(h). In fact, γ(0) = 0 and γ(h), as h approaches 0, is a quantification of the measurement error (which can only be directly estimated in the case of repeated measurements). Therefore the nugget effect or nugget provides some measure of precision and repeatability in the roller MV data. Since the minimum spacing between roller MV points is often at least several centimeters, the nugget must be estimated by extrapolating the best fit line or curve through h = 0. The minimum distance where γ(h) reaches its maximum (or at least 95% thereof ) is called the range and the value of the maximum itself is called the sill. For second order stationary fields Z(x) the variogram levels off for large distances. If this is not the case, it is often an indication that a trend or large scale structure exists in the spatial field. If the variogram depends only on the length of the distance (h) but not on the direction of the differences then the spatial field is isotropic, otherwise it is anisotropic (for a detailed discussion, see Section 2.3 of Cressie 1993). To test for anisotropy one calculates the empirical semi variogram for pairs of observations that are (at least approximately) aligned in predetermined directions. Here, these directional semi variograms can be performed in the direction of roller travel and perpendicular thereof.

Figure 5.

Empirical semi variogram.

759

4.2 Analyses of data A closer look at the raw roller MV data often shows very low MVs at the start or end of a single path. These values are considered a recording artifact and need to be addressed in the variogram estimation by either careful elimination or by using robust estimation procedures (e.g., Genton 1998). Figures 6 and 7 show different empirical semi variograms for subgrade cell 1, base cell 1 and 2 for both Ammann and Bomag data. More specifically, Figure 6 shows the x-directional variograms obtained from each individual path/lane (thin dashed lines), the (pooled) x-directional (thick solid) as well as the omni-directional variogram (thick dashed). As expected, the pooled variogram is often representative of the individual ones. As the omni-directional variogram has a much shorter range and a higher sill we suspect anisotropy. To confirm our hypothesis, Figure 7 shows the y-directional variograms for the three cells for both rollers. There is strong evidence that the compacted fields are anisotropic with respect to the x and y directions. This existence of anisotropy has important implications on geospatial acceptance criteria and on further statistical analysis, e.g., geostatistical modeling, kriging, and merits future research. Note there is evidence that the base has slightly larger ranges than the subgrade. Table 2 provides the sill, range and nugget effect for a weighted least squares fit of the x-directional empirical variogram by a spherical variogram (see Section 2.6 of Cressie 1993 and Figure 5 for a qualitative description thereof ). The observed ranges are of the order of 20 m and larger for Ammann ks compared to Bomag Evib. Conversely, Bomag Evib data exhibits larger sills (greater variability) than Ammann ks. Notice the pronounced difference in the spatial structure between base cell 1 and 2, confirming the in Section 3 advocated need to separate the cells for an analysis. The resulting measurement errors (standard deviations)

Figure 6.

Variogram analysis of Ammann ks (a–c) and Bomag Evib (d–f ).

760

Figure 7. Comparison of x and y direction variograms (a) Ammann ks (b) Bomag Evib (thick lines indicate y-dir. and thin lines indicate x-dir.). Table 2.

Variogram parameters for different cells. Ammann ks (MN/m)

Bomag Evib (MPa)

Parameter

Subgrade cell 1

Base cell 1

Base cell 2

Subgrade cell 1

Base cell 1

Base cell 2

Range Sill Nugget effect

24.8 7.7 1.3

52.0 15.4 1.2

30.0 15.8 1.6

15.5 66.3 11.6

12.5 79.4 1.2

28.3 226.7 16.8

for Ammann ks and Bomag Evib data sets were found to be 1.1–1.3 MN/m and 1.1–4.1 MPa, respectively. These values are consistent with those observed during repeatability studies in similar contexts. 5

CONCLUSIONS

Roller MV combined with GPS-based locations provides a rich set of data for geostatistical analysis. As with many non-text book datasets careful modeling is needed and the paper highlights several important steps thereof. By treating individual cells, the data can in many cases be modeled with a normal distribution. However, the mean and standard deviation (and hence as well as the coefficient of variation) depend on the individual cells as well as on the roller. A functional dependency of the former in terms of the latter would be highly desirable but it is not clear if achievable. The data explored in this paper exhibits clear spatial structure within the driving direction (shown by x-directional variograms). For the direction orthogonal to driving, the structure is different to the driving direction and it seems that there is no significant spatial structure. ACKNOWLEDGMENTS Partial financial support was provided by NCHRP. The writers would like to thank Bomag and Ammann for the use of their rollers and Mn/Road for providing test areas. REFERENCES Anderegg, R. and Kaufmann, K. 2004. Intelligent compaction with vibratory rollers: feedback control systems in automatic compaction and compaction control. Transp. Research Record 1868, 124–134. Adam, D. 2007. Roller integrated continuous compaction control (CCC) technical contractual provisions & Recommendations, Design and Construction of Pavements and Rail Tracks: Geotechnical Aspects and Processed Materials, CRC Press, Correia, A.G., Momoya, Y. and Tatsuoka, F. (eds), 111–138.

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Baecher, G.B. and Christian, J.T. 2006. The influence of spatial correlation on the performance of earth structures and foundations. Proc. Geocongress, Atlanta, GA. Cressie, N.A.C. 1993. Statistics for Spatial Data. New York: Wiley, revised reprint. Chiles J.-P. and Delfiner P. 1999. Geostatistics: Modeling Spatial Uncertainty. New York: Wiley. DeGroot, D.J. and Baecher, G.B. 1993. Estimating autocovariance of in-situ soil properties. J. Geotech. Engineering, ASCE, 119(1), 147–166. Genton, M.G. (1998). Highly robust variogram estimation. Mathematical Geology, 30, 213–221. Kröber, W., Floss, R. and Wallrath, W. 2001. Dynamic soil stiffness as quality criterion for soil compaction. In Geotechnics for roads, rail tracks, and earth structures, Balkema, Lisse. Mooney, M.A. and Adam, D. 2007. Vibratory Roller Integrated Measurement of Earthwork Compaction: An Overview, Proc. International Symposium on Field Measurements in Geomechanics, September 24–27, Boston, MA. Petersen, D., Erickson, M., Roberson, R. and Siekmeier, J. 2007. Intelligent Soil Compaction: Geostatistical Data Analysis and Construction Specifications. Transportation Research Board 86th Annual Meeting, Washington, D.C. Phoon, K.-K. and Kulhawy, F.H. (1999). “Characterization of Geotechnical Variability.” Canadian Geotechnical Journal, 36(4), 612–624. Rinehart, R.V. and Mooney, M.A. “Measurement Depth of Vibratory Roller-Measured Soil Stiffness,” Géotechnique, 2009, in press. White, D., Thompson, M. and Vennapusa, P. 2007. Field Validation of Intelligent Compaction Monitoring Technology for Unbound Material. Minnesota Department of Transportation. St. Paul, Minnesota.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Author index

Abu Abdo, A. 295, 305 Adhikari, S. 321 Affleck, R. 1019 Agrawal, S.K. 25 Ahmed, M.U. 669 Akbulut, H. 359 Akpinar, M.V. 1117 Aksnes, J. 285, 513 Al Nageim, H. 205, 225 Allou, F. 155 Al-Qadi, I.L. 1039 Álvarez Loranca, R.L. 653 Alves, A.R.D. 1133 Angelone, S.M. 275 Anochie-Boateng, J. 1029 Antunes, M.L. 503, 1231 Apeagyei, A.K. 879 Araújo, N. 125 Arellano, D. 981 Aursand, P.O. 1091 Aurstad, J. 249, 1177 Avsar, C. 65 Azevedo, A.M. 571 Bacci, R. 387 Baek, J. 1039 Bakløkk, L.J. 285 Balay, J. 1405 Baltzer, S. 443, 859 Bandara, N. 29 Barbati, S. 1493 Barbosa, Á.S. 37 Barna, L. 1019 Barrett, X. 1485 Barros, M.A.L. 37 Bayomy, F. 295, 305 Beduneau, E. 479 Bento, B.B. 37 Berge, T. 513 Berntsen, G. 819, 1177 Bilodeau, J.P. 145 Bisht, R. 669 Bonneau, D. 479 Bordelon, A. 717 Brar, H. 57

Brill, D.R. 1383 Brito, L.A.T. 3 Bryson, L.S. 1219 Büchler, S. 339 Butt, A. 237 Caldeira, L. 1311, 1331 Cao, X. 79 Cardone, F. 1493 Cardoso, R. 1291 Carlsson, H. 1125 Cavalcante, F.P. 1465 Cavalheiro, A. 197 Ceratti, J.A.P. 1393 Cetin, E. 107 Ceylan, H. 661, 869 Chai, H. 551 Chazallon, C. 155 Chehab, G. 931 Chowdhury, T. 419 Christie, D. 5 Clec’h, P. 377 Coenen, A.R. 117 Connor, B. 89 Cortez, P. 597 Cottineau, L.-M. 467 Cox, B.R. 1143 Cruz, R.T.G. 571 Cunha, J. 1303 Curry, B. 1143 da Silva Pontes Filho, I.D. 1465 Dahlhaug, J.E. 1177 Dargenton, J.-C. 459 Dawson, A.R. 3 de Carvalho Filho, C.R. 1465 de Carvalho, M.H. 37 de Medeiros Brito Cavalcante, C. 1465 De Myttenaere, O. 963 Delgado, J. 1311, 1331 Deniz, D. 1187 Dethy, B. 215 Detry, J. 215 763

Di Benedetto, H. 377 Diefenderfer, B.K. 419, 879 Diyaljee, V. 1455 Dombrow, W. 1349 Domingos, P. 503 Dong, C. 1001 Donovan, P.R. 619 Doré, G. 145 Du Plessis, L. 1415 Dupriet, S. 479 Edil, T.B. 1011 Eide, E. 1053 Elias, M.B. 117 Emery, S.E. 543, 1475 Erlingsson, S. 1101 Fabre, C. 1405 Facas, N. 755 Fairclough, R. 409, 849 Fengchen, C. 427 Ferne, B. 409, 849 Ferreira, T. 1291 Ferri, S. 571 Fleming, P.R. 809 Fortes, R.M. 37, 137 Fortunato, E.C. 1231 Fredriksson, R. 799 Frost, M.W. 809 Furrer, R. 755 Gallego, J. 487 Garg, N. 57 Geng, L. 495, 907 Ghaboussi, J. 679 Giannakos, K. 1263 Gieselman, H.H. 45 Goh, S.W. 315 Gomes Correia, A. 125, 197, 215, 597, 1303, 1311, 1331 Gonçalves de Macêdo, J.A. 1465 Gonzalez, C. 607 Gopalakrishnan, K. 869

Graczyk, M. 1063 Graziani, A. 1493 Grazioli, M.J. 29 Grégoire, C. 215 Griffiths, D.V. 1273 Guillard, Y. 467 Guler, E. 107 Gungor, A.G. 65 Guo, E.H. 531, 1383 Gure, A. 107 Gurer, C. 359 Hachiya, Y. 269 Hakim, H. 1125 Halahmi, I. 1159 Halsted, G.E. 1445 Han, J. 1159 Hao, L. 427 Hao, P. 1169 Harasim, P. 769 Harvey, J. 1415 Hazirbaba, K. 89 He, Y. 1197 Heckel, G. 179 Heinkele, C. 467 Hejlesen, C. 859 Hoff, I. 1053 Horak, E. 543, 1475 Hornych, P. 155 Horvli, I. 1091 Hou, X. 435 Hu, S. 1197 Huang, H. 619, 1349 Huber, G. 707 Hyslip, J.P. 1341 Indraratna, B. 5 Ioannides, A. 1433 Ishikawa, T. 1207 Jakobsen, P.E. 859 Jansen, D. 789 Jersey, S. 607 Ji, Y. 897 Jia, X. 551 Johansen, R. 819 Johansen, T.H. 697 Johanson, L. 45 Jung, S.J. 305 Kamei, T. 1207 Ker, H.W. 941 Kern, J. 237 Khoury, C. 71 Khoury, N. 71

Kim, S. 869 Kohler, E. 1415 Kolisoja, P.J. 3 Korsgaard, H.C. 689, 859 Kumar, T. 931 Kvasnak, A. 1373 Kwon, J. 1321 Lalagüe, A. 1053 Lambert, J.P. 809 Langdale, P. 409 Lange, D. 1425 Larkin, A. 57 Leandri, P. 387 Lechner, B. 1243 Lee, Y.H. 941 Lees, H.M. 1283 Lenngren, C.A. 729, 799, 829, 839 Lerat, P. 1405 Lerfald, B.O. 249, 285 Leshchinsky, D. 1159 Levenberg, E. 1361 Li, D. 1341 Li, X. 435 Li, Z. 79, 1001 Lièvre, D. 459 Lin, J.D. 941 Little, D.N. 3 Liu, Y. 315 Liu, Y. 589 Liu, Y.B. 941 Liu, Y.-S. 1425 Livneh, M. 777 Loizos, A. 451, 643, 1263 Lopes, F.M. 571 Losa, M. 387 Lu, L. 1197 Ma, S. 435 Maekawa, R. 269 Mahmoud, E. 367 Maina, J.W. 543, 561, 1475 Maranha das Neves, E. 1331 Marcelino, J. 1311 Marques, R. 597 Martínez, F.O. 275 Martins, J. 1311, 1331 Masad, E. 367 Maser, K.R. 661 Mathisen, L.U. 167 Matsui, K. 561 Mazars, A. 1405 McCartney, J.S. 1143 McCleary, T. 97 764

McDaniel, C.R. 1341 McGrath, L.A. 661 Mechowski, T. 769 Medero, G. 1273 Meehan, C.L. 745 Mehta, Y.A. 921 Menetti, N.C. 37 Merighi, J.V. 37, 137 Metzker, K. 327 Miller, B.C. 661 Miradi, M. 633 Mishra, D. 237 Molenaar, A.A.A. 259, 633 Molenaar, S. 633 Mollamahmutoglu, M. 1113 Mollenhauer, K. 327, 339, 349 Mooney, M. 755 Morian, D.A. 931, 1433 Mork, H. 521 Motumah, L. 1415 Muraya, P.M. 259 Muriel, K.M. 921 Muzet, V. 467 Nantung, T.E. 897 Nazarian, S. 367 Nener-Plante, D.J. 397 Neves, J.M.C. 503, 1133 Nielsen, R. 305 Nimbalkar, S. 5 Nunez, W.P. 1393 Ohnishi, Y. 1207 Olard, F. 479 Olsen, K. 689 Ozawa, Y. 561 Padilla, E. 915 Paige-Green, P. 1505 Paixão, A.M. 1231 Papavasiliou, V. 643 Parsons, R.L. 1159 Pauli, D.R. 37 Pedersen, J.P. 689 Pekcan, O. 679 Penman, J. 1321 Pérez, I. 487 Petit, C. 155 Pierre, P. 145 Plati, C. 451 Pokharel, S.K. 1159 Popovics, J.S. 1187 Powell, B. 1373 Pradhan, S. 1253

Puppala, A.J. 1253 Qian, Y. 1159 Qin, W. 581 Ramos, L.F. 1311 Refsdal, G. 819 Reis Ferreira, S.M. 197 Reiter, J. 1433 Ren, J. 1243 Renken, P. 339 Ribeiro, F.V. 37 Roesler, J.R. 717, 1079 Roque, A.J. 197 Rose, J.G. 1219 Round, N. 409 Ryerson, C. 1019 Saba, R.G. 285, 513 Sadasivam, S. 931, 1433 Sadrekarimi, J. 739 Saghafi, B. 225 Said, S.F. 1125 Sanati, G. 661 Santagata, E. 1493 Santi, M.J. 295, 305 Santos, C.R.G. 571 Saride, S. 1253 Sauber, R.W. 921 Sauzéat, C. 377 Schwartz, C.W. 951 Seignez, N. 479 Sekine, E. 1207 Sert, T. 1117 Seyyedi, S. 739 Shekharan, R.A. 419 Sheng, Y. 589 Shoop, S. 1019 Siekmeier, J. 45 Simonin, J.-M. 459, 467

Sinhal, R. 849 Siraj, N. 921 Sitharam, T.G. 1253 Songgen, W. 707 Stark, T.D. 981 Stoffels, S.M. 931, 1433 Straube, E. 789 Stubstad, R.N. 689 Su, K. 269 Sun, L. 269 Suzuki, C.Y. 571 Svanekil, A. 1053 Sybilski, D. 769 Taddesse, E. 521 Tan, Y. 1073 Tarefder, R.A. 669 Tehrani, F.S. 745 Teixeira, P.F. 1291 Terrosi Axerio, A. 387 Theisen, K.M. 1393 Titi, H.H. 117 Toledano, M. 487 Tran, N. 1373 Turner, P. 1373 Tutumluer, E. 237, 619, 679, 1029, 1187, 1349

Walker, B. 543 Wang, D. 1079 Wang, H. 1169 Wang, L. 589 Wang, M.C. 581 Wang, X. 581, 973, 1073 Wang, Z. 581 Weaver, T. 305 Wells, R. 1485 Wells, T. 1485 Wen, H. 1011 West, R. 1373 White, D.J. 45 White, G.W. 889 Wistuba, M. 327, 339, 349 Wood, C.M. 1143 Woodward, P.K. 1273 Xiang, R. 1243 Yan, Z. 551 Yeh, L. 1433 Yesuf, G.Y. 697 Yildiz, A. 359 Yilmaz, Y. 65, 1113 Yiqiu, T. 427 You, Z. 315, 321 Young, C. 1143 Yufeng, B. 707

Uthus, N.S. 249 van Bijsterveld, W.T. 653 van de Ven, M.F.C. 259, 633 Van Geem, C. 963 Vaslestad, J. 697 Vennapusa, P.K.R. 45 Victorino, D.R. 1393 Visulios, P. 205

765

Zejiao, D. 427 Zhang, K. 1169 Zhang, L. 973 Zhang, X. 1073 Zheng, Y. 551 Zhong, Y. 495, 907 Zofka, A. 397 Zohrabi, M. 991 Zou, J. 79

PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON THE BEARING CAPACITY OF ROADS, RAILWAYS AND AIRFIELDS, CHAMPAIGN, ILLINOIS, USA, JUNE 29–JULY 2, 2009

Bearing Capacity of Roads, Railways and Airfields Editors Erol Tutumluer & Imad L. Al-Qadi Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

VOLUME II

Structural evaluation & performance prediction

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of effectiveness of FWD use for assessment of pavement interlayer bond D. Sybilski, T. Mechowski & P. Harasim Road & Bridge Research Institute, Warsaw, Poland

ABSTRACT: Bond between pavement layers (specifically asphalt layers) became one of the most important issues last years. Pursuing the rutting resistant asphalt pavements leads to asphalt mixtures of lower binder content, and thus asphalt layers of lower “semi-binding” potential. Such asphalt layers do not provide proper bond between pavement layers after compaction. It results in ineffective stresses and strains transfer from upper to lower layer under the traffic loads. In such working conditions, pavement does not work as monolithic structure and exhibits much shorter fatigue life. Use of non-destructive FWD method for assessment of pavement interlayer bond is very interesting and useful. Paper will present the basic conditions of testing using FWD for evaluation of interlayer bond and testing results of asphalt road pavements for various traffic categories and of various pavement structure thickness as well as material properties. 1

INTRODUCTION

Interlayer bonding is one of the most important factors influencing proper asphalt pavement performance, to a large extent underestimated until recently. Interaction of layers in pavement structure depends on interlayer bonding, and it influences pavement durability. Livneh & Shklarsky (1962) concluded that the case when friction coefficient between the asphalt carpet and the rigid base is small is critical, while rigid base does not interact with asphalt layer, and critical point, where fatigue cracking is initiated, is located at the bottom asphalt layers not of rigid base. Lack of or weak interlayer bond causes that layers do not interlock and pavement load is not properly transferred from upper layer to lower layer. It results in higher stresses at bottom of upper layer and higher strains in unbounded base. Life of pavement may be shorter by up to 40–70% (Hakim 1996 & Judycki 2003). Deterioration of road pavement due to insufficient interlayer bond is known for years, testing of this pavement property was undertaken only some 20 years ago. Interlayer bond between two asphalt layers is derived from two main factors: the first— gluing both layers with bituminous binders being constituents of both layers or with intentionally applied tack coat, and the second—interlocking of mineral grains of both layers. Shear strength of interlayer bond depends on gluing potential of both layers, thickness of interlayer tack coat, grade of bituminous binder, binder’s properties and composition, kind of modifier (polymer) and its content, shear rate (Judycki 2003). It was noticed that due to healing properties of bituminous binder, the bond which was destroyed at lower temperature may regenerate at higher temperature, e.g 40°C. The second factor of interlayer bond—interlocking depends on: • temperature of bottom layer—the best results may be obtained in case of Kompaktasphalt technology (two layers in one paving operation), • binder content—more binder better bond (at certain limit, of course), • binder grade—harder binder more difficult creation of bonding but if bonded then stronger shear strength,

769

• mineral mixture grading—finer mixtures ease creation of better bond, • layers’ stiffness—stiffer layers lesser interlocking, • surface cleanness—asphalt layer covered with clay or dust cannot create bond with other layer. Laboratory testing at IBDiM (Road & Bridge Research Institute) (Zawadzki et al. 2002, 2003) led to conclusions that Leutner test is a proper available laboratory test method for evaluation of interlayer bond. Shear strength depends on the sample origin and method of preparation. Range of shear strength at 20°C is as follows: • samples cored from road pavement, 0.9 ÷ 2.4 MPa • laboratory cylindrical samples compacted with hammer, 0.85 ÷ 1.6 MPa • laboratory cylindrical samples cut from plate compacted with roller compactor, 1.0 ÷ 2.4 MPa. On the basis of laboratory test results and field validation it is recommended that interlayer shear strength of sample cored from pavement should be not less than 1.3 MPa (Zawadzki et al. 2004). Problem described became even more frequent topic of research in the world. New test methods are being developed. This paper presents the trial to develop testing procedure with use of FWD (Falling Weight Deflectometer). The procedure shall allow estimation of interlayer bond in the real pavement on the basis of interpretation of FWD measured pavement deflections. 2

INTERLAYER BOND EVALUATION TEST METHODS

Several test methods exist for evaluation of interlayer bond. Best known and frequently applied are: • laboratory tests – Leutner Test – Shear Box Test • field tests – FWD—Hakim et al. (1998, 2002) – Impulse Hammer Test developed at Nottingham University. Field test method developed by Hakim et al. (1998) will be described here closer, being similar to method presented in this paper due to use of FWD. 2.1 Use of FWD by Hakim et al. Falling Weight Deflectometer FWD generates creation of deflection bowl on the pavement surface (Fig. 1). Deflection values at points of measurement are used as input data for calculation of stiffness moduli of pavement layers. It was a main and basic application of FWD. It is indisputable however that quality of interlayer bond influence deflection test results of FWD. Method developed by Hakim et al. (1998) allows additionally for evaluation of interlayer bond. The algorithm of this method is as follows: • gathering test data of deflection bowl, pavement construction (layer thickness and type), estimation of Poisson ratio, • calculation of pavement deflections with assumption of layers’ stiffness moduli (back calculation) and full interlayer bond (shear or bonding stiffness at interface Ksi = 105 MN/m3), • multiple regression analysis aiming for achievement of deflection bowl having the less error compared to measured deflection bowl, 770

• stiffness moduli obtained from back calculated deflection bowl are used in analysis of pavement structure, • it is assumed that stiffness modulus is constant for layers below asphalt layers being evaluated (between which interlayer bond is evaluated), these moduli were calculated earlier, • calculation of stiffness moduli of asphalt layers according to previous steps with assumption of varying values of shear stiffness at interface (interlayer bond quality) from Ksi = 105 MN/m3 (full bonding) to Ksi = 10 MN/m3 (no bonding), • calculation of real values of stiffness moduli taking into consideration interlayer bonding in the pavement during deflection measurements. Using the values obtained in further calculations, more precise evaluation is possible e.g. harmful stress concentration or pavement fatigue life expected. 3

FIELD ROAD SECTION TESTS

Test results from 12 road pavement sections were taken for analysis presented in this paper. The test road sections chosen exhibited both weak and proper interlayer bonding between asphalt layers. Following steps in evaluation of pavement were performed: pavement structure diagnosis, coring samples for laboratory testing, measurement of deflections with FWD. Road sections set chosen includes wide spectrum of roads of various structure. All upper courses (wearing and binder) are made of asphalt, lower layers present an overview of courses of various age, and made of various materials (paving clinker, asphalt concrete, set of various asphalt mixtures, cement bound base layers, unbound base layers). In two cases geosynthetics— textile or geocomposite (textile and polyester grid) were used in asphalt layers. Test sections were located on roads of various function and traffic loading, i.e. national, secondary, local roads, urban streets (in large cities), parking lots near market centers. Some of the test sections exhibited clear signs of fatigue cracking and deterioration. Leutner test for evaluation of interlayer bond was performer on the samples taken from the test sections pavements. Shear strength ranged from 0 (complete de-bonding) to 3.1 MPa. Due to limitation of paper’s volume, detailed presentation of test sections will not be presented in the paper. 4

TEST RESULTS & ANALYSES

The basic assumption for development of test method for evaluation of quality of interlayer bonding was use of full capabilities offered by FWD. Computer software usually offer calculation of pavement layers; stiffness moduli, and further pavement fatigue life. For these calculation, deflection bowl created from maximum values of deflections measured at individual geophones is used. Analysis presented in this paper was performed with use of software MODDYN developed at IBDiM. MODDYN is based on theory of wave propagation in multi-layer structures and makes use of full range of run of pavement deflections and value of contact stress on pavement surface from starting point of loading until de-loading. On the basis of long time experience with FWD deflection measurements, one may conclude that besides measuring pavement bearing capacity, this equipment may be applied for testing pavement interlayer bonding. Analysis of the methods listed above leads to conclusion that the most useful from practical point of view might be Impulse Hammer Test. In case of FWD measurement such a “hammer” is dynamic loading generated by FWD, and geophones (deflection sensors) act as receivers. Development of suitable testing procedure is needed to convert deflections measurement results to enable determination the interlayer bonding quality. Analysis of results of deflection measurements on test sections indicates difference in deflection characteristics of pavement with proper or weak interlayer bond. Figures 1–2 present 771

Figure 1.

Deflection and loading run in time, point of proper interlayer bond.

Figure 2.

Deflection and loading run in time, point of weak interlayer bond.

run of deflections and loading, from the beginning of loading until end of de-loading, in two points on the same test section. Figure 1 presents point of proper pavement interlayer bond, and Figure 2 presents point of weak bond. For better comparison of both charts, values of deflections and loads are normalized to the maximum values. Both charts present clear differences in the run of deflections in points of proper and weak bond. Even better presentation is given on Figure 3, which shows deflections at central sensor only—the point in the centre of loading plate. 772

1,2

Normalised deflection

1 0,8 0,6 0,4 0,2

562

522

482

442

402

362

322

282

242

202

162

122

82

42

2

0 –0,2 Time, ms Weak bond

Figure 3.

Proper bond

Deflection run in time at central sensor, points of proper and weak interlayer bond.

1,2

Normalised deflection

1 0,8 0,6 0,4 0,2

562

522

482

442

402

362

322

282

242

202

162

122

82

42

2

0 –0,2 Time, ms Df1

Figure 4.

Df2

Df3

Df4

Df5

Df6

Df7

Deflection run in time, point of no interlayer bond.

Difference in deflection charts is even better seen in Figure 4 showing results from another test section with no interlayer bond. On the chart presenting deflection run in point of proper bond, two points of curve bending are observed (see Figure 1)—the first one during increasing loading on the pavement and the second during un-loading. On the chart presenting deflection run in point of weak or no bond (see Figures 2, 4) additional point of curve bending may be observed. 773

1,2

Normalised deflection

1

D max

0,8 0,6 0,4 0,2

Dend

0

D min

–0,2 Time, ms

Figure 5. Variation of pavement deflection in time under central sensor with marking of characteristic points.

Analysis of all the charts of deflections run in time of all test sections led to conclusion that in case of pavements of weak or no interlayer bond proved in laboratory testing, deflection run in time charts present the same shape (as seen on Figures 2 or 4). In case of pavements of proper interlayer bond, the shape of deflection run in time chart is as shown on Figure 1. For qualitative evaluation of the observed phenomenon, the Interlayer Bond Index Ibond is proposed, calculated from Equation 1: I bond =

Dend − Dmin i 100% Dmax

(1)

where Ibond = Interlayer Bond Index; Dend = deflection value at the end of run registered (after 600 ms); Dmin = the lowest deflection value; and Dmax = the highest deflection value. In case when the lowest deflection value Dmin (third curve bending point) is not observed, for instance in case of good interlayer bond, value of Dmin is to be take equal to Dend. Values indicated in Equation 1 are presented on Figure 5. All FWD measurement results from test sections where used for calculation of Interlayer Bond Index Ibond. Results and statistical characteristics are given in Table 1. The evaluation notes given in Table 1 are the result of both values of Ibond and of Leutner test or field observation during sample coring. The note “undefined” concerns the case when interlayer bond is varying—its quality cannot be clearly evaluated for the whole length of test section with clear confirmation from laboratory tests. On the basis of deflection measurements with FWD and confirmation from laboratory tests as well as evaluation of samples taken from pavements of test sections, the following classification of pavement interlayer bond is proposed: • • • •

Ibond = 0 0 < Ibond ≤ 4 4 < Ibond ≤ 8 Ibond > 8

full interlayer bond, good interlayer bond, weak interlayer bond, no interlayer bond. 774

Table 1. Values of the Ibond Interlayer Bond Index of the evaluated road pavement sections.

5

Mean value

Standard deviation

The lowest value

The highest value

Interlayer bond evaluation

9.1 4.0 4.1 0.0 0.5 2.7 1.6 0.0 9.8 11.6 10.4 7.9 7.3 1.7 0.8 5.7 6.6 1.5 1.2 0.1 0.8 12.5 4.4 6.8 5.5 14.7 7.8

8.0 3.5 3.3 0.0 1.1 2.9 1.4 0.0 6.3 5.0 5.0 4.7 4.8 2.9 1.6 3.5 5.0 2.5 2.2 0.3 2.4 5.6 5.5 8.9 1.8 3.4 5.1

1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.9 3.0 0.0 0.8 0.0 0.0 1.7 0.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 3.4 10.0 0.0

27.8 10.9 10.7 0.0 3.6 9.0 4.0 0.0 24.1 24.0 22.3 17.4 17.8 8.2 5.2 12.6 14.4 6.4 6.1 1.1 7.7 18.2 14.9 16.9 9.2 21.0 18.6

weak undefined undefined good good undefined undefined good weak weak weak weak weak undefined undefined undefined undefined good good good good weak undefined undefined undefined weak weak

CONCLUSIONS

Tests and analysis allow for following conclusions: • measurements results with use of dynamic deflectometer FWD (full deflection run in time) may be successfully used for evaluation of road pavement interlayer bond quality, • method presented for evaluation of interlayer bond quality, consisting in calculation of Interlayer Bond Index Ibond or analysis of deflection run in time provides fast and simple tool for initial estimation of interlayer bond quality, • FWD operators should in a greater extend make use of capabilities of FWD—during measurement the software in a real time visualize pavement deflections—it is recommended that operator would register unusual, unexpected deflections run, • it cannot be clearly defined on this stage of research, which layers exhibit weak bond, weak correlation was found between results of deflection measurements and depth of weak bond, • method for calculation stress and strain in the pavement structure considering interlayer bond more effectively, • evaluation of bonding with FWD should be supported with use of ground penetrating radar, while image analysis of pavement structure provides to mark places or sections of weak interlayer bond. ACKNOWLEDGMENTS Authors would like to express their gratitude to General Directorate of National Road and Motorways of Poland—the sponsor of this research work as well as to co-workers executing the tests: Adam Kowalski, Jacek Kusiak and Radosław Borucki. 775

REFERENCES Hakim, B., Al Nageim, H. & Pountney, D.C. 1996. Reflection of the interface condition modelling error on backcalculated moduli and pavement remaining life. Proc. 1st Eurasphalt & Eurobitume Congress, Paper E & E 8.215. Strasbourg, France. Hakim, A., Armitage, R. & Thom, N. 1998. International Conference on Bearing Capacity of Roads and Airfields. Pavement assessment including bonding conditions: case studies. Trondheim. Hakim, A. 2002. The importance of good bond between bituminous layers. Proc. 9th International Conference on Asphalt Pavements. Copenhagen, Denmark. Judycki, J. 2003. Bonding between pavement asphalt layers. (Sczepność między warstwami asfaltowymi nawierzchni, in Polish.) Drogownictwo 9/2003. Livneh, M. & Shklarsky, E. 1962. Proceedings of the First International Conference on the Structural Design of Asphalt Pavements The bearing capacity of asphalt concrete surfacing. University of Michigan, Ann Arbor: 345–353. Zawadzki, J., Skierczyński, P. & Pałys, M. 2002. Bonding between asphalt layers—test method and requirements. (Połączenie między warstwami nawierzchni asfaltowej—metoda badania i wymagania, in Polish.) VIIIth International Conference Durable and Safe Road Pavements. Kielce. Zawadzki, J., Skierczyński, P. & Mechowski, T. 2003. Influence of interlayer bonding on asphalt pavement durability. (Wpływ połączenia między warstwami asfaltowymi na trwałość nawierzchni, in Polish.) IXth International Conference Durable and Safe Road Pavements. Kielce. Zawadzki, J., Sybilski, D. & Skierczyński P. 2004. Recommendations for use of geosynthetics in asphalt layers of road pavements. (Zalecenia stosowania geosyntetyków w warstwach asfaltowych nawierzchni drogowych, in Polish.) Information and Instructions, IBDiM, Booklet 66.

776

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The use of impact-stiffness modulus outputs from FWD measurements to determine PCN in Israel M. Livneh Transportation Research Institute, Technion-Israel Institute of Technology, Haifa, Israel

ABSTRACT: This paper describes the Israel Airports Authority’s (IAA’s) experience with airport-pavement bearing-capacity evaluation through the Pavement Classification Number (PCN) system. Various technical studies around the world indicate that pavement-surface deflections can be considered a predictor of pavement life. Therefore, impact-stiffness modulus values, defined as the ratio of the Falling-Weight Deflectometer’s (FWD’s) impact load to its consequent central deflection, can be used to evaluate the PCN of a particular flexible pavement. To recall, the PCN numerical value is determined from the allowable load rating (i.e., bearing strength) of the pavement. The latter may be calculated by applying the principles contained in ICAO Doc-9157-AN/901, Part 3—Pavements. In determining the allowable load rating, such factors as frequency of operation and permissible stress levels should be taken into account. Once the allowable load is established, the PCN value is determined by converting the rating to a standard relative number. For the present study, use is made of the old Dynamic Stiffness Modulus (DSM) procedure developed by the USCOE; this procedure is correlated with various FWD measurements conducted on four major runways or taxiways in Israel, together with in-situ borings. The results obtained were also checked against the relevant results made available from the full-scale trafficking tests conducted by the FAA at the National Airport Pavement Test Facility (NAPTF) in Atlantic City, New Jersey. Finally, the paper concludes with a recommendation as to the use of impact-stiffness modulus outputs from FWD measurements in order to determine the PCN of a flexile pavement directly and on the basis of local experience. 1

INTRODUCTION

In 1981, the ACN/PCN (Aircraft Classification Number and Pavement Classification Number) method was introduced by the International Civil Aviation Organization (ICAO) as a simple method of reporting pavement strength [ICAO, 1995]. According to this method, ACN is a number that expresses the relative damage caused by an aircraft to a given pavement and is calculated according to a prescribed technical procedure. In the same manner, PCN is a number that expresses the relative load-carrying capacity of a pavement in terms of standard single-wheel load. In contrast to ACN, however, PCN assignment is not fixed by a prescribed technical procedure. In other words, ICAO has not specified regulatory guidelines as to how an airport authority is to arrive at a PCN and has left it up to each authority to perform this task. The aim of this paper is to describe the Israel Airports Authority’s (IAA’s) experience with airport-pavement bearing-capacity evaluation through the PCN system. It is well accepted that the most conventional method to assign a PCN value to a given runway is by conducting an in-depth field study along the runway. However, it is not always possible to keep a runway occupied for an extended duration with exploration and boring activities. Thus, a quick PCN assignment is sometimes essential. In this connection, various technical studies around the world indicate that pavement-surface deflections can be considered a predictor of pavement life. Therefore, impact-stiffness modulus values, defined as the ratio of the Falling-Weight Deflectometer’s (FWD’s) impact load to its consequent central deflection, can be used to evaluate the PCN of a particular flexible pavement. However, a 777

correlation study is required in order to calibrate these two methods. Thus, the objectives of this study are as follows: • to summarize the concepts of PCN and to evaluate some PCN factors; • to outline the method used by the IAA to assign PCN values by the field-exploration (boring) method; • to utilize international findings regarding PCN evaluation by measuring central deflections with various types of dynamic equipment, such as the U.S. Army Corps of Engineers (USCOE) 16 Kips Vibratory Machine or any conventional FWD device; • to correlate the outputs of the aforementioned two methods utilizing field-exploration studies and measurements carried out by the IAA at Israel’s Ben-Gurion International Airport and by the FAA at the National Airport Pavement Test Facility (NAPTF) in Atlantic City, New Jersey; • to suggest a routine evaluation procedure for future assignments of PCN values. The process of meeting these five objectives will now be detailed.

2

THE PCN CONCEPT

According to ICAO, the PCN number expresses the relative load-carrying capacity of a pavement in terms of a standard single-wheel load. Specifically PCN, which is the basis of reporting pavement strength, is defined as twice the single-wheel load (in tons) operating with a tire pressure of 1.25 MPa that can still perform 10,000 coverages on a given pavement. Any design aircraft that is assigned by calculating its ACN value, as defined elsewhere (see, for example, Figure 1), should be less than or equal to the given PCN value. The manner in which PCN values are determined is left to each user. This “freedom” of choice is possible because, as mentioned, the method is not and does not pretend to be a method of pavement design or evaluation. Thus, there are two main groups of methods for determining a PCN value for a given runway. The first group consists of technical evaluation methods, and is labelled “T” in the reported PCN. The second group, labelled “U,” is based on utilizing the experience of existing aircraft. Further information concerning the technical evaluation methods can be found in the technical literature. In the technical evaluation method, the PCN numerical value for a particular pavement is determined through the allowable load-carrying capacity of the pavement. This may be evaluated from the application of one or both of the following techniques: (a) non-destructive testing techniques; (b) direct sampling and semi-destructive or destructive testing techniques. Once the allowable gross weight (AGW) is established, the determination of the PCN value is a process of converting that weight into a standard relative value, as explained in the next paragraph. The allowable gross weight used for the pavement evaluation is the maximum allowable gross weight of the most critical (dominant) aircraft that can use the pavement for the number of equivalent departures expected to be applied for its remaining life, as will be discussed later. The process of converting the allowable gross weight (AGW) into a PCN value follows. When the critical aircraft and its equivalent departures (which is not the same as equivalent coverages), together with the allowable gross weight, have been established from the results of the pavement evaluation, the pertinent relationship between gross weight and ACN must be attained (for the proper pavement type and subgrade class, see Figure 1, for example). Now, the matching ACN value is to be determined by entering the proper relationship with the allowable gross weight of the critical aircraft. This ACN value is equal to the PCN value. The evaluation method in which the allowable gross weight of the critical aircraft and its equivalent departures are determined is essentially the reverse of the design method. As in this paper, the design method is based on USCOE’s conventional CBR design method or the FAA’s conventional CBR design method; use can also be made of the PCASE program (Traffic and Evaluation Commands) or the COMFAA program (by trial-and-error iteration). The inputs for the PCASE program (Walker & Adolf, 2005) are (a) the in-situ CBR values of 778

120 B747-400 Aircraft Flexible pavement

ACN Values

100

y = 0.322x –26.1 Subgrade Category

80

y = 0.263x – 24.8

D y = 0.199x – 14.5

60

C B

y = 0.172x – 10.5 A

40

20

0 200

225

250

275

300

325

350

375

400

Aircraft gross weight [ton]

Figure 1. ACN values versus gross weight of the B747-400 acting on flexible pavements, based on subgrade categories A, B, C & D. Note: The figure and the other computations in this paper are based on the old load-repetition factors (alpha factors); new alpha factors are now available from ICAO (Hayhoe, 2006).

the pavement’s subgrade and granular layers, (b) the in-situ strength of asphalt layers, (c) the total thickness of the pavement structure, including the base course and the asphalt-layer thicknesses, and (d) the definition of the critical aircraft and its equivalent departures. The inputs for the COMFAA program (Kawa & Hayhoe, 2002) are (a) the in-situ CBR values of the pavement’s subgrade, (b) the total thickness of the pavement structure, corrected for existing thicknesses of the base course and asphalt courses (as shown later on), and (c) again, the definition of the critical aircraft and its equivalent coverage. As an example, the procedure for calculating PCN described above leads in the singlewheel airplane case (with 10,000 coverages) to the following equations: 0.878 1.25 − 0.01249 × CBR A pE PCN = 2 × Q × 0.878 − 0.01249 CBR A

(1a)

2

⎛H ⎞ 1 ×⎜ E ⎟ 100, 000 ⎝ α1 ⎠ Q= 1 1 − 0.5692 × CBRE 32.035 × pE

(1b)

where Q = load on one of the two one-wheel landing gears, in tons; HE = existing total effective equivalent thickness of the pavement, in mm.; α1 = load-repetition factor for a one-wheel landing gear and any given number of coverages; CBRE = existing subgrade CBR, in %; pE = existing tire pressure, in MPa; and CBRA = ICAO-designated CBR determined according to the existing subgrade CBR (CBRE) in the following way: CBRA = 3% (Code Designation D) for CBRE less than 4%, CBRA = 6% (Code Designation C) for CBRE equal to 4% and above but less than 8%, CBRA = 10% (Code Designation B) for CBRE equal to 8% and above but less than 13%, and CBRA = 15% (Code Designation A) for CBRE equal to 13% and above. (Note: the term “effective thickness” will be explained later on.) 779

3

EVALUATION OF SOME PCN FACTORS

The PCN definitions shown in the previous section lead to the important conclusion that for any given pavement, its PCN value is not a constant value. One of the factors affecting the PCN value is the number of coverages of the design airplane. For the single-wheel airplane case, use is made, again, of Equations 1a and 1b for different values of α1, depending of the given number of coverages. These values have been computed from the equations that serve the old COMFAA program. With the aid of Equations 1a and 1b, it can be shown that PCN values decrease as the number of design-aircraft coverages increase. A second PCN factor that affects the PCN value is the number of wheels in any main landing gear, including the gear configuration. To illustrate this effect, Figure 2 shows the variation of the PCN ratio with aircraft coverages. This PCN ratio is the ratio of the PCN value calculated for a single-wheel aircraft to the PCN value calculated for a B747-400 for any given number of coverages (with the aid of the old COMFAA program). In this figure, HE is equal to 1,500 mm. and CBRE is equal to 2% and 4%. For the single-wheel airplane, the tire pressure is equal to 2.1 MPa. Figure 2 indicates that the PCN values associated with the B747-400 are less than those associated with the single-wheel airplane. More specifically, the figure indicates that the PCN ratio as defined above is more than 1. For a given total pavement thickness, this ratio decreases with the increase in the number of coverages or with the increase in the subgrade CBR value. Thus, Figure 2 indicates that it is essential that the airplane type, characterized by the number of wheels and their gear configuration, should also be reported along with the PCN value. At this juncture, it should be pointed out that some of the technical literature fails to take into account the effects on PCN values of the aircraft type and its number of coverages. As a result, their PCN outputs are unfortunately always ambiguous; see, for example, (Antunes & Pinto, 1990; Grätz & Riedl, 2006). By contrast, however, the American Air Force, for example, recognizes the importance of airplane type and its traffic and, therefore, dictates that the PCN evaluation should be regularly performed for 50,000 departures of the C-17 aircraft (USCOE, 2001) in order to compare facilities around the world. The Israel Airports Authority also dictates that a PCN evaluation for Ben-Gurion Airport should be performed regularly for 120,000 departures of the B747-400 aircraft.

2.00 Ratio of PCN for Single-Wheel Aircraft to PCN for B747-400 Aircraft

Ratio of PCN

1.75

CBR = 2%

1.50 CBR = 4%

1.25 CBR = 2% CBR = 4%

1.00 3.0

3.5

4.0

4.5

5.0

5.5

6.0

Log coverages

Figure 2. Ratio of PCN for a single-wheel aircraft to PCN for the B747-400; total thickness of the pavement is 1,500 mm.

780

160 140

B747-400 Aircraft 120,000 Departures CBR = 100%

PCN values

120 100

CBR = 80%

y = 1.648x – 92.64 80 60 y = 0.0176x2 – 3.295x + 206.68 40

CBR of granular base 80% CBR of granular base 100%

20 90

100

110

120

130

140

150

160

Thickness of asphaltic layers [mm]

Figure 3. PCN values versus total thickness of asphalt layers and the CBR of the granular base course (203 mm thickness) for 120,000 departures of the B747-400.

Finally, an additional parameter should be discussed. This parameter is defined by the total thickness of the upper asphalt layers and the CBR value of the crushed-granular base course. These two values affect the PCN value, as shown in Figure 3, for 120,000 departures of the B747-400 aircraft. (The data in this figure was calculated with the use of the PCASE program [Traffic and Evaluation Commands].) Obviously, the final PCN value is the lesser of the two calculated values obtained, one according to HE and CBRE as defined earlier, and the other according to Figure 3. 4

DERIVATION OF PCN FROM CENTRAL DEFLECTION

In 1970, an improved vibratory loading device was developed by the USCOE (the so-called WES NDT tool in order to assist the NDT evaluation procedure (FAA, 1976; Green & Hall, 1975). In this connection, it should be noted that the primary effort of the USCOE was directed at developing a procedure based on measuring the dynamic stiffness modulus (DSM) of the pavement system and relating this value to pavement-performance data. The aforementioned WES NDT tool contains a loading device that exerts a static load of 16 kips on the pavement surface and is capable of producing 0–15 kip vibratory loads at a frequency of 15 Hz. This load is applied to the pavement surface through an 18-in. diameter steel loading plate. At each test site, the loading equipment is positioned, and the dynamic force is varied from 0 to 15 kips at 2 kip intervals and a constant frequency of 15 Hz. The deflection of the pavement surface, measured by the velocity transducers, is plotted against the applied load. The DSM (ton/mm) is the inverse of the slope of the deflection versus load plot at the linear portion of the curve. The measured DSM value is to be corrected to the standard DSM value, for which the asphalt temperature is 21°C. This is done with the aid of a multiplier factor TC, called the temperature adjustment factor, which is given in (FAA, 1976). Nowadays, the use of the WES NDT tool is rare; in most cases, it is replaced by the Falling-Weight Deflectometer (FWD). Therefore, impact-stiffness modulus (ISM) values, defined as the ratio of the FWD impact load to its consequent central deflection, substitute for the DSM values. This substitution is performed with the aid of the following correlation, obtained from the data and references shown in Figure 4: For ISM ≥ 20 ton/mm. (a dashed line in the figure): DSM = 0.7147 × ISM + 16.2 781

(2a)

120 y = 0.7147x + 16.2 R = 0.975

60

Equations Limit

80

Linear Equation Zone

2

Power Equation Zone

DSM-WES NDT [ton/mm]

100

y = 4.6109x0.6315 R = 0.974 2

40 Wiseman et al., 1985 Bush & Alexander, 1981 (Dynatest) Bush & Alexander, 1981 (WES) Bush & Alexander, 1981 (PCS)

20

0 0

20

40

60

80

100

120

140

ISM-FWD [ton/mm]

Figure 4. DSM measured by the WES NDT equipment versus the ISM measured by any FWD device according to various published experimental data.

For ISM < 20 ton/mm. (a solid line in the figure): DSM = 4.6109 × ISM0.6315

(2b)

where DSM = dynamic stiffness modulus of the pavement, measured by the WES NDT, in ton/mm.; and ISM = impact-stiffness modulus of the pavement in ton/mm., measured by any FWD device. Figure 4 is based on in-situ measurements performed with various types of FWD devices. As mentioned before, the sources of these measurements are shown in the figure. The investigation carried out by (Green & Hall, 1975) with the WES NDT tool led to the following experimental relationship (see experimental data in Figure 5): ASWL = 1.110 × DSMS

(3)

where DSMS = dynamic stiffness modulus of a pavement with an asphalt temperature of 21°C, in ton/mm.; and ASWL = allowable single-wheel load, with 254 sq. in. of tire contact area for 24,000 departures, in tons, obtained from in-situ exploration and drilling and the CBR equation (i.e., Equation 1b with the appropriate values of pE and α1). Figure 5 shows the scatter of the data. This scatter leads to a standard error of estimate of 8.1 tons for the ASWL value. 5

EXPLORATION STUDIES

At Ben-Gurion Airport, field exploration and boring studies included determinations of (a) thicknesses of various layers; (b) in-situ strength of the various pavement layers, including subgrade; (c) the deterioration factor for each pavement layer. The results obtained are presented in Table 1. This table also includes the total equivalent thickness, as will now be explained. Total equivalent thickness, or equivalent pavement thickness layers, includes an asphaltic layer of exactly 125 mm. and a granular base of exactly 225 mm., with the remainder of these two layers to be added to the existing sub-base layers by implementing the following substitution ratios: (a) 1 unit of asphalt = 1.3 units of granular base and (b) 1 unit of asphalt = 1.9 units of granular sub-base. In addition to the thickness and CBR data, the remaining life factor of the existing pavements was estimated from visual inspection of the pavement damage, thereby enabling a calculation of the deterioration factor (DF). Knowledge of the DF allows one to calculate 782

100 Airbase S Airbase N Airbase P Airbase W Airbase B Airbase NV

ASWL [ton]

80

Allowable Single-Wheel Load with 254 sq. in. of Tire Contact Area for 24,000 Departures

60

y = 1.110x

40

20

0 0

10

20

30

40

50

60

DSM-WES NDT [ton/mm]

Figure 5. ASWL with 254 sq. in. of tire contact area for 24,000 departures versus DSM of a pavement with an asphalt temperature of 21°C, according to WES experimental data (Green & Hall, 1975). Table 1.

Ben-Gurion Airport and NAPTF pavement details (L.C.I, 2006; Garg & Marsey, 2002).

Item ID Taxiway K1–K3 Taxiway N Runway 03–21 Runway 12–30 NAPTF: LFS NAPTF: LFC NAPTF: MFC NAPTF: MFS

Asphaltic layer [mm.]

Crushed Asphaltic granular base [mm.] base [mm.]

Total equivalent Subbase thickness [mm.] [mm.]

Total effective equiv. thickness [mm.]

Design in-situ CBR [%]

150

–

550

1,001

1,730

1,540

5.0

105(1) 100(1)

– –

450 440

1,497 1,459

2,030 1,990

1,700 1,670

6.0 5.5

350

–

200

890

1,631

1,631

5.0

127

124

753

1,360

1,360

4

130

–

197

924

1,243

1,243

4

130

–

198

308

628

628

8

127

124

216

576

576

8

–

–

(1) These thicknesses are rather small, which probably necessitates the use of similar calculations as those in Figure 3 for the PCN calculation of their accompanying pavements (see also the paragraph following Table 2).

the total effective equivalent thickness, this being the actual thickness multiplied by DF, as shown in Table 1. It should be noted, furthermore, that the data from the NAPTF trial sections in Table 1 were taken from (Garg & Marsey, 2002). The same source also submitted the deflection measurements performed on these trial sections prior to their being opened to traffic (see Table 2). Thus, in this case, the existing total thickness of the trial sections equals the total effective thickness. Table 1 is supplemented by Table 2, which present the FWD deflection data. All the data given in Table 2 enable a calculation of the relevant DSM values. Note that additional NAPTF experimental data given in this table (i.e., coefficient of variation of central deflection and mean asphalt temperature) were taken from www.airporttech.tc.faa.gov/naptf. 783

Table 2. Ben-Gurion Airport and NAPTF asphalt temperature and central deflection FWD measurements.

Item ID Taxiway K1–K3 Taxiway N Runway 03–21 Runway 12–30 NAPTF: LFS NAPTF: LFC NAPTF: MFC NAPTF: MFS

Mean Dynamic central load deflection [ton] [mm.]

Coefficient of Asphalt Temperature DSM at 21°C variation of Design ISM temperature correction [ton/mm.] deflection [%] [ton/mm.] [°C] [TC]

7.5

0.27

29.1

24.7

30

1.25

38.9

7.5 7.5

0.32 0.35

8.9 9.9

21.5 19.6

30 30

1.25 1.25

36.3 34.8

7.5

0.21

13.6

31.9

30

1.25

44.9

16.3

0.53

8.1

28.5

13

0.69

25.2

16.3

0.97

10.8

15.2

12

0.86

23.3

16.3

1.02

12.8

14.2

12

0.87

22.9

16.3

0.51

3.7

30.8

15

0.69

26.4

Notes: (a) The design ISM values were determined from the 85th percentile of the central deflection, which is equal to the sum of its mean and standard deviation values. (b) The temperature correction, TC, is according to (FAA, 1976].

120

Allowable Single-Wheel Load with 254 sq. in. of Tire Contact Area for 24,000 Departures

100

ASWL [ton]

80 y = 1.8182x R = 0.8715

60

2

40

IAA: CBR = 5–6% FAA: CBR = 4% FAA: CBR = 8%

20

0 0

10

20

30

40

50

60

DSM -FWD [ton/mm] S

Figure 6. ASWL with 254 sq. in. of tire contact area for 24,000 departures versus the DSM measured by the FWD apparatus and corrected for an asphalt pavement temperature of 21°C, according to local and NAPTF experimental data.

The data in Table 1 allowed to calculate ASWL for 24,000 departures by utilizing Equation 1b, for which α1 = 0.94. For Taxiway N and Runway 03-21, however, the ASWL values obtained should be corrected by the ratio of two PCN values obtained from the PCASE program for single-wheel load aircraft (AF Group 03, the tire contact area for which equals 241 sq. in., which is very close to the required area of 254 sq. in.) in the following manner: one PCN value for asphalt thickness as given in Table 1, and the other PCN value for an asphalt thickness of 150 mm. These calculations lead to the relationship given in Figure 6. In this relationship, the two points of CBR = 8% seem to be exceptional. 784

PCNH for 120,000 Departures of B747-400

120

100

80

y = 2.1352x R2 = 0.9705

60

40

20

IAA: CBR = 5-6% FAA: CBR = 4% FAA: CBR = 8%

0 0

10

20

30

40

50

60

DSMS-FWD [ton/mm]

Figure 7. The calculated PCNH values for 120,000 departures of the B747-400 versus DSM measured by the FWD apparatus and corrected for an asphalt pavement temperature of 21°C, according to local and NAPTF experimental data.

It is important to note that the multiplier value of the regression line shown in Figure 6 (1.818) is higher than that of Figure 5 (1.110). This discrepancy may be due to the use of mean DSM values in Figure 5, in contrast to the 15th percentile DSM values in Figure 6. Furthermore, the regression line constructed in Figure 5 covers the entire tested range of subgrade CBR values, whereas the regression line constructed in Figure 6 covers only a limited range of subgrade CBR, from 4% to 6%. In the same manner as Figure 6, the relationship between the PCNH values to the DSMS measured values can be calculated. The output of these calculations is shown in Figure 7. For the calculations of this figure, PCNH denotes the calculated PCN value on the basis of the thickness and CBR data in Table 1 for 120,000 departures of the B747-400. Again, the two points of CBR = 8% in this figure seem to be exceptional. In order to cover all the data tested (including the two points of CBR = 8%), an additional regression was carried out in which the independent variable DSMS is replaced by a new independent variable, DSMS/CBR0.5. This new independent variable includes the square root of the CBR value, which yields the highest value for the coefficient of determination (R2). The output of these regression calculations is shown in Figure 8 and Equation 4. It is important to note that Equation 4 below enables a determination of PCN values only on the basis of non-destructive measurements, without the need to conduct any in-depth field explorations. This is also true of the subgrade CBR value, which can be obtained from the FWD deflection measurements, utilizing the vertical deflection measured at a lateral distance of 1.8 meters and leaving the total pavement thickness as an unnecessary input value as suggested by the 1993 AASHTO guide for the design of pavement structures, and others [e.g., Sides et al., 1992]. Finally, the formulation of Equation 4 is as follows: 1.5536

⎛ DSMS ⎞ PCN H = 1.0188 × ⎜ 0.5 ⎟ ⎝ CBR ⎠

(4)

where PCNH = calculated PCN value on the basis of the thickness and CBR data in Table 1 for 120,000 departures of the B747-400. To conclude, for routine use involving sites other than those tested in this paper, the validation of Equation 4 should be explored for other structures, subgrades, and aircraft traffic. 785

PCNH for 120,000 departures of B747-400

120

100

80 y = 1.0188x1.5536 R2 = 0.9238

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Figure 8. Calculated PCNH values for 120,000 departures of the B747-400 versus DSMS/CBR0.5 measured by the FWD apparatus and corrected for an asphalt pavement temperature of 21ºC, according to local and NAPTF experimental data.

6

SUMMARY AND CONCLUSIONS

This paper describes the Israel Airports Authority’s (IAA’s) experience with airport-pavement bearing-capacity evaluation through the Pavement Classification Number (PCN) system. Various technical studies around the world indicate that pavement-surface deflections can be considered a predictor of pavement life. Therefore, impact-stiffness modulus values, defined as the ratio of the Falling-Weight Deflectometer’s (FWD’s) impact load to its consequent central deflection, can be used to evaluate the PCN of a particular flexible pavement. For the present study, use was made of the old DSM procedure developed by the USCOE to guide the suggested FWD procedure. For that reason, a correlation was made with various FWD measurements conducted on four major runways or taxiways in Israel, together with in-situ borings. The results obtained were also checked against the relevant results made available from the full-scale trafficking tests conducted by the FAA at the National Airport Pavement Test Facility (NAPTF) in Atlantic City, New Jersey. The conclusions drawn from the present study are as follows: • Based on existing data in the technical literature, a reasonable correlation has been found between the Dynamic Stiffness Modulus (DSM) measured by the WES NDT tool (a loading device as described earlier) and the ISM measured by various FWD devices, thus allowing the existing DSM findings to guide the FWD measurements. • For the range of a subgrade CBR of 4%–6%, it is recommended that the new ASWLDSMS correlation of Figure 6 (i.e., a multiplier of 1.818) be adapted for practical PCN calculations instead of the USCOE given in Figure 5 (i.e., a multiplier of 1.110), as the latter correlation is based on a broader range of subgrade CBR, yielding a significant scatter of the data. • For any range of subgrade CBR, Equation 4 (see also Figure 8) enables a determination of PCN values only on the basis of non-destructive measurements, without the need to conduct any in-depth exploration field study, and thus allows a quick PCN assignment where it is essential. Finally, it should be emphasized that the results reported above apply specifically to the traffic and pavements listed, including the very narrow CBR range. Thus, for routine use for other sites than those tested in this paper (i.e., those that express the local experience), the validation of Equation 4 should be explored for additional structures, subgrades, and air traffic volumes. 786

ACKNOWLEDGMENTS The paper is based on engineering studies conducted for the Israel Airports Authority, and thanks are therefore due the Authority. The paper was prepared with the assistance of Mr. Arieh Aines, graphics editor of the Transportation Research Institute at the Technion, to whom thanks are also due. REFERENCES Antunes, M.L.B.L. & Pinelo, A.M.S. 1990. Airport Pavement Evaluation and ACN-PCN Classification. Proceedings of the Third International Conference on Bearing Capacity of Roads and Airfields, the Norwegian Institute of Technology, Trondheim, Norway. Bush III, A.J. & Alexander, D.R. 1981. Pavement Evaluation Deflection Basin Measurements and Layered Theory. U.S. Army Corps of Engineers Waterways Experiment Station, Vicksburg, MS. FAA. 1976. Use of Nondestructive Testing Devices in Evaluation of Airport Pavement. FAA Advisory Circular AC 150/5370-11, Federal Administration Aviation, Office of Airport Safety and Standards, Washington, DC. Garg, N. & Marsey, W.H. 2002. Comparison between Falling Weight Deflectometer and Static Deflection Measurements on Flexible Pavements at the National Airport Pavement Test Facility (NAPTF). Proceedings of 2002 Federal Aviation Administration Airport Technology Transfer Conference, Atlantic City, NJ. Grätz, B. & Riedl, St. 2006. Structural Maintenance of Airfields-Calculation and Evaluation of Pavement Classification Number (PCN) on the Basis of Dynamic Measurements of the Load Carrying Capacity”, Proceedings of the Second International Conference on Airports: Planning, Infrastructure & Environment, Sao Paulo, Brazil. Green, J.L. & Hall, J.W. 1975. Nondestructive Vibratory Testing of Airport Pavements: Vol. I. Experimental Test Results and Development of Evaluation Methodology and Practice. Report No. FASARD-73-205-1, U.S. Army Corps of Engineers Waterways Experiment Station. Prepared for the FAA, U.S. Department of Transportation. Hayhoe, G.F. 2006. Alpha Factor Determination Using Data Collected at the National Airport Pavement Test Facility. Report No. DOT/FAA/AR-06/7, Airport Technology Research and Development Branch, AAR-410. ICAO. 1995. International Standards and Recommended Practices, Aerodromes. Annex 14 to the Convention on International Civil Aviation, Vol. 1, Airodrome Design and Operation, 2nd Edition, International Civil Aviation Organization. Kawa, I. & Hayhoe, G.F. 2002. Development of a Computer Program to Compute Pavement Thickness and Strength. Proceedings of the 2002 Federal Aviation Administration Airport Technology Transfer Conference, Atlantic City, NJ. L.C.I. 2006. Determination of PCN Values for Several Runways and Taxiways at Ben-Gurion Airport. Internal Report submitted to the Israel Airports Authority by L.C.I-Transportation Engineers Consultants. Sides, A., Bonjack, J. & Zoltan, G. 1992. Overlay Design Procedure for Pavement Management Systems. Transportation Research Record No. 1374, Transportation Research Board. USCOE, 2001.Airfield Pavement Evaluation. United Facilities Criteria, UFC 3-260-03, U.S. Army Corps of Engineers. Walker, R.S. & Adolf, M.J. 2005. Pavement-Transportation Computer Assisted Structural Engineering (PCASE): User Manual, Version 2.08, U.S. Army Corps of Engineers, Engineer Research and Development Center. Wiseman, G., Greenstein, J. & Uzan, J. 1985. Application of Simplified Systems to NDT Pavement Evaluation, Transportation Research Record No. 1022, Transportation Research Board.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Temperature correction of falling weight deflectometer measurements E. Straube & D. Jansen University of Duisburg-Essen, Essen, Germany

ABSTRACT: In order to design pavements it is important to know the bearing capacity of the pavement. The bearing capacity can be derived from deflection measurements by a Falling Weight Deflectometer (FWD). The deflections next to the load center on asphalt pavements are strongly influenced by the temperature of asphalt layers. To get comparable results, the measured deflections have to be corrected to a reference temperature. The aim of the presented research project was to develop a function for temperature correction of FWD deflections which is suitable for the conditions in Germany. For this, two existing asphalt pavements were instrumented with temperature sensors in the asphalt layer, which continuously log the asphalt temperatures. FWD deflection basins were measured on the instrumented test sections at different temperatures and seasons. In addition, 20 more test sections with different thicknesses and asphalt materials were measured by FWD at different temperatures and seasons. 1

INTRODUCTION

The shape of deflection basins measured by a Falling-Weight-Deflectometer (FWD) is influenced by several conditions which are not directly related to the overall bearing capacity of the FWD testing point. These conditions can be for example the current water-content of the unbound layers and the temperature of the asphalt concrete (AC) layer. An FWD test only displays the current conditions of the testing point and may change when testing a few hours later. Therefore a consideration of the current nonpermanent surrounding conditions has to be done before data evaluation and interpretation. This is done by correcting the measured data to standard reference conditions. FWD deflections near the load center are highly dependent on the AC layer temperature. Several international approaches exist to correct the measured FWD deflections to a reference AC layer temperature, e.g. (Chen, Bilyeu, Lin, Murphy 2000) (Kim, Hibbs, Lee 1995) (Park, Kim, Park 2002). In Germany only an algorithm for the temperature correction exists which was developed for Benkelman Beam measurements (Schulte 1984). The transfer of this function to FWD deflections is not possible. Internationally existing algorithms often cannot be transferred without being evaluated, because of differing climatic conditions and construction principles in Germany. In order to derive a temperature correction algorithm with an empirical approach a wide database is necessary, which contains the temperature situation in the AC layer at a wide range of ambient temperature and weather situation and which also describes the “deflection basin” to “AC layer temperature” relationship at several AC layer temperatures and in different seasons. 2

INFLUENCE ON THE BEARING CAPACITY OF AC PAVEMENTS

The bearing capacity of AC pavements can be described by the FWD deflection basin. The absolute value of the deflections depends on the distance to the load center and the properties 789

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Influence of AC layer temperature on FWD deflection basin and calculated AC elastic

and conditions of the bounded and unbounded layers, the subgrade and the combination of these. The deformation behaviour on the surface can be derived from the elastic modulus, the layer thickness and the Poisson number of each layer. As the thickness of each layer depends on the FWD testing station and the Poisson ratio can be assumed constant on uncracked pavements, the elastic modulus is influenced by climate and traffic. The elastic modulus of the layers is therefore influenced by – in case of AC layers – load frequency – layer temperature – in case of unbound layers and subgrade – water content – layer temperature (in case of temperatures <0°C) These factors have to be considered for the interpretation of FWD testing. In order to be able to neglect the influence of the load frequency all FWD systems measure with a constant load frequency of approximately 10 Hz (Straube, Beckedahl, Huertgen 1996). In order to be able to neglect the water content and the layer temperature of unbound layers, FWD testing in Germany is normally done outside the freeze and thaw period. So the only variable factor which influences the interpretation of the FWD testing is the AC layer temperature. FWD testing in Germany is limited from 5°C to 30°C AC layer temperature by an official paper (FGSV 2003). To give an example for the influence of the AC layer temperature, several FWD tests were done at the same position. Figure 1 (left) shows the testing results and the temperature dependency of the AC elastic modulus (right). In this example the AC layer temperature creates a center deflection range of 40% of the maximum value. Figure 1 (right) shows the temperature and frequency dependency of the AC elastic modulus demonstrated by calculated values. In order to consider the AC layer temperature for the interpretation of the FWD testing, the deflections influenced by the AC layer temperature needs to be corrected to a reference temperature. For the climatic conditions in Germany a reference temperature of 20°C can be chosen (FGSV 2005). 3

FIELD TESTING

In order to examine and evaluate the qualitative and quantitative influence of the AC layer temperature on the deflection basins measured by the FWD, several field tests were done over 790

more than one year. In order to continuously measure the AC layer temperature gradients, two existing asphalt pavements were instrumented with thermocouples in the asphalt layer, which continuously log the asphalt temperatures. FWD deflection basins have been measured on the instrumented test sections at different temperatures and seasons. In addition 20 more test sections with different thicknesses and asphalt materials have been measured by FWD at different temperatures and seasons. Meteorological data and results from drill core evaluations make the analysis complete. Furthermore all measured data will be used for other research projects concerning pavement design. All chosen test sections had to meet several demands: – specific AC layer thickness (five test sections each): 18, 22, 26 and 30 cm (± laydown tolerance) – flexible pavement: AC layer and subbase on subgrade (no hydraulically bound layers/no overlays) – Surface course: asphalt concrete or stone mastic asphalt – minimum length of each section: 500 m – classified roads, freeways – roads built in recent years, maximum age of 10 years – no distinctive surface distresses – no exceeding traffic impact during FWD measurements Two test sections were chosen for the installation of the thermocouples. They had to meet additional demands: – – – –

homogenous field conditions on a length of 50 m each no random shading of the section (for example: parking vehicles) no longitudinal gradient no embankment, cut or cut and fill profile

About 50 test sections were first looked up into a national database, visited and at last reviewed if they could fulfill the mentioned demands. 3.1 AC layer temperature logging stations Thermocouples were installed in different depths of the AC layer at two test sections to measure the AC layer temperature gradients. The total AC layer thickness of the test sections were 22 cm (Station 1) and 28 cm (Station 2). The thermocouples were installed in depth range from 0 to 20 cm and 28 cm respectively. The horizontal position of the thermocouples is midlane. The test sections are located in the northwest of Germany and have a linear distance of 94 km to each other. Figure 2 shows the local details of each test section. The thermocouples were installed in April 2007. In order to install the thermocouples, two overlapping drill cores were taken and the thermocouples were fixed with thermoconducting glue into a channel which was vertically milled into the drill hole. Afterwards the drill cores were put back into the hole, fixed with installation foam and sealed at the top. The data logger, connected with a wire to the thermocouples, is placed at the side of the road and logs the temperature in a text file on a SD-Memory card every minute. The data logger runs on battery. The thermocouples were built for the special needs of the project. They basically consist of an aluminum head in a non-thermo conducting compound, see Figure 3. The AC layer temperature is only measured at the tip of the aluminum head, so that the influence of the installing drill core is as little as possible. 3.2 FWD testing The FWD testing was done at different AC layer temperatures and in different seasons (spring, summer and autumn). Repeating measurements were done next to the temperature logging station (TLS) and at the 20 test sections. 791

Thermocouple positions 0 cm 2 cm 4 cm 5 cm 7 cm 9 cm 14 cm 20 cm

Figure 2.

Thermocouple positions 0 cm 2 cm 5 cm 7 cm 9 cm 14 cm 20 cm 28 cm

Test site location and inventory data of the Temperature-Logging-Stations (TLS).

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6 polyurethane compound

Thermocouple and TLS.

Testing Point 4

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Figure 4.

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Figure 3.

15.0 m

Test setup for repeated FWD testing next to TLS.

The FWD testing next to the TLS were done at four testing points (TP 1–4), see figure 4. The spacing between the positions was chosen so that the towing vehicle did not shade the next testing position when standing at the one before. The FWD testing next to the TLS was done with three 50 kN drops followed by three 90 kN drops. The FWD testing on the 20 test sections was done with 25 m spacing between the testing positions. The first testing position 792

of each test section was marked. Each test section has 21 FWD testing points. Each testing position was tested with three 50 kN drops. The AC layer temperature was recorded at the beginning of each test section with a mobile temperature logging system. This system consists of five thermocouples which were put into small drill holes (diameter 8 mm) at 4, 8, 12, 16 cm depth and at the surface. The temperature data was recorded with a notebook. 4

DISCUSSION OF RESULTS

4.1 Temperature measurements The AC layer temperature gradient measurements were done continuously from April 2007 to April 2008 and beyond. The measured spectrum and frequencies of the AC temperatures in 0, 5 and 20 cm depth are shown in figure 5. One of the main questions to be answered was, if the temperature gradients significantly depend on the AC layer thickness. Therefore the recorded temperatures from the two stations, AC layer thickness 22 and 28 cm, were compared to each other in different ways. First the daily curves of each station and depth were compared to each other, see figure 6, and then the temperature gradients of each station were compared to each other. The slope of the gradients is nearly the same regardless of the AC layer thickness. Even though the stations have a distance of 94 km to each other and have different surrounding conditions, the daily curves look fairly similar, so that the measured data can be assumed as plausible. In combination with the meteorological database the daily temperature curves of the AC surface temperature can be characterized. There are three typical daily curves of the AC surface temperature, see figure 7 and figure 8. The three types can be described with the maximum and minimum daily AC surface temperature, daily sunshine duration and daily global radiation. 4.2 FWD testing The FWD testing next to Station 1 and Station 2 were done at a temperature range from 5 to 30°C (at 5 cm depth). The measured deflection basins next to Station 1 and Station 2 (TP 1) are shown in figure 9. The analysis of the deflection basins (TP 1–4) shows that the relative influence of the AC temperature on the deflections is independent from the AC layer thickness, see table 1.

30 FWD testing range 25

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Figure 6.

Comparison of daily curves at 7 cm—sunny period and temperature gradients.

Type 1 Figure 7.

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Types of AC surface temperature daily curves.

Several questions have to be answered in order to derive a temperature correction algorithm for FWD deflections: What has to be done to get the actual AC layer temperature? Does the temperature correction have to be dependent from the FWD load level and from the AC layer thickness? Up to which distance from the load center should the deflections be corrected to the reference temperature? 4.2.1 In situ AC layer temperature measuring The best way to describe the AC layer temperature is to measure the whole temperature gradient from the top to the bottom at every FWD testing position. In case of the usual proceeding of FWD actions it is not possible to integrate this kind of detailed temperature measurement. To check how the actual AC layer temperature can be measured best during FWD actions, AC layer temperature measurements in small drill holes (diameter 8 mm) were done next to the TLS. Several parameters have been tested. The results show that there is no difference in using water, glycerol or measuring in a dry hole when the thermocouple is placed close to the bottom of the drill hole. No sealing at the top is necessary if the thermocouple has nearly the same diameter as the drill hole. To be on the safe side, one has to wait at least 15 minutes until the AC temperature measurement is no longer influenced by the drilling heat, or until the temperature reading has been stable for over more than a minute. Additional measurements, up to two hours after drilling a hole, have shown that the open drill hole can be still be used if one allows the thermocouple about five minutes to reach the temperature of the drill hole. To derive a representative depth for the temperature probe a regression analysis of the measured temperature and deflection data was done. The analysis showed that there is a strong correlation (≥97%) of the AC temperatures measured from 5 to 9 cm depth and the center deflection. With a view to practicality the AC temperature at 5 cm was chosen as a representative depth. The AC temperatures above are significantly influenced by sudden changes of weather while it is difficult to make drill holes at deeper layers at low temperatures. 794

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Example of AC surface temperature types. Absolute and relative influence of the AC temperature on center deflection. Relative influence of AC temperature on center deflection at a AC temperature range of 25°C (5–30°C) (100% = center deflection at 30°C)

Station

Testing point

Spectrum of center deflection (AC temperature range of 30°C at 5 cm depth)

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Δ = 118 μm Δ = 132 μm Δ = 195 μm Δ = 93 μm

66% 63% 70% 72%

2

TP 1 TP 2 TP 3 TP 4

Δ = 21 μm Δ = 21 μm Δ = 20 μm Δ = 37 μm

60% 62% 67% 62%

4.2.2 Load level dependency Figure 10 shows the measured load center deflections at 50 kN and 90 kN at different AC layer temperatures. There is a linear dependency between the deflections without an AC layer temperature influence. Therefore a temperature correction of deflections can be done independently from the FWD load level. 4.2.3 AC layer thickness dependency To evaluate whether the temperature correction of FWD deflections has to be dependent from the AC layer thickness, the measured deflection basins at the two TLS were compared to each other. Even if the absolute, temperature dependent, change of the center deflection at Station 2 (AC layer thickness = 28 cm) is much smaller than at Station 1 (AC layer thickness = 22 cm) the relative change is similar, see figure 9 and table 1. Therefore the AC layer thickness can be neglected in case of temperature correction of deflections. 4.2.4 Distance to load center As seen in figure 9 the impact of the AC layer temperature on the deflection basin decreases with increasing distance to load center. A graphical analysis and correlation analysis of the 795

Position of geophone [mm]

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data measured at Station 1 and 2 was done to define the influenced distance to load center. Only distances to the load center which are typical for FWD testing in Germany were analyzed (0, 200, 300, 450, 600, 900, 1.200, 1.500 and 1.800 mm). The correlation analysis (AC temperature at 5 cm to deflection at various distances) showed that there is a strong correlation of 91 to 95% up to 600 mm from the load center. The analysis of the measured deflections bowls at different AC temperatures, see figure 9, showed that the deflections at 600 mm are still influenced by the AC temperature while the deflections at 900 mm or more are not influenced. The correlation analysis and graphical analysis showed that the deflections up to a distance of 600 mm from the load center needed to be considered for temperature correction. 5

TEMPERATURE CORRECTION OF FWD DEFLECTIONS

The temperature correction formula for FWD deflections was derived from the measured data at Station 1 and Station 2 and afterwards verified by the measured data from the mentioned 20 test sections. The chosen reference AC layer temperature was 20°C. Regression analysis was used to get a reference deflection at 20°C for every testing position next to Station 1 and Station 2 and for every distance to the load center up to 600 mm. Then a temperature correction factor was calculated for every single deflection using the data from Station 1 and Station 2, see figure 11. Afterwards several regression analyses were done to get 796

a temperature correction formula for each geophone position up to 600 mm. These analyses showed that there is a linear relationship between the AC layer temperature and the FWD deflections. The analyses also showed that higher significance could be achieved when using separate functions for the AC layer temperature range below and above 20°C. Furthermore the analyses showed that separate functions for small deflections below 20°C are necessary to enhance the significance. For the temperature correction of FWD deflections the measured deflections are multiplied with a temperature normalisation factor to get deflections at the reference temperature of 20°C: D20,i = A ⋅ DT ,i = (a + b ⋅ T ) ⋅ DT ,i

(1)

D20,i = Deflection of geophone i at 20°C [μm] A = temperature normalisation factor a, b = Factors depending on – geophone position – AC layer temperature range (<20°C or >20°C) – small or large deflections (criterion depends on geophone position/only <20°C) T = AC layer temperature at 5 cm [°C] DT,i = measured FWD deflection at AC layer temperature T of geophone i [μm] Example 1: → <20°C AC temperature at 5 cm = 11°C Measured deflection = 175 μm → >140 μm (criterion for large deflections) Geophone position = 0 mm D20,1 = (1.3052 − 0.0152 ⋅ 11) ⋅ 175 = 199 μ m Example 2: → >20°C AC temperature at 5 cm = 28°C Measured deflection = 289 μm → no differentiation (small/large) necessary Geophone position = 450 mm D20, 4 = (1.2303 − 0.0110 ⋅ 28) ⋅ 289 = 267 μ m

1,6 Regression for small deflections (large factors)

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Temperature at 5 cm depth [°C] Figure 11.

Correction factors [Station 1 (TP 1) and Station 2 (TP 1)] with regression lines.

797

40

6

CONCLUSIONS

In this paper the empirical procedure of the continuous measurement of temperature gradients within two different asphalt pavements for over more than one year and the analysis of these temperature gradients concerning their effect on the FWD bearing capacity measurements is presented. The discussion of results shows that the daily temperature curves can be characterized into three types and that the temperature gradients are independent from the AC layer thickness. These results will be part of a following research project concerning, amongst others, typical temperature distributions for the design of AC pavements in Germany. From the results of this investigation, the following conclusions were made concerning the temperature correction of FWD deflection basins: The temperature correction of deflection basins can be made without the knowledge of the AC layer thickness. Deflections up to a distance of 600 mm from the load center are influenced by the AC temperature. The FWD load level has no impact on the temperature dependency of the deflections. The AC layer temperature at a depth range from 4 to 9 cm strongly correlates with the FWD deflections. The AC temperature at 5 cm was chosen to correct the measured deflections to a standard temperature of 20°C. A new function for temperature correction of FWD deflection basins has been presented. The function is dependent on the geophone position, the AC layer temperature range and the size of the deflections. REFERENCES Chen, D.H., Bilyeu, J., Lin, H.-H. & Murphy, M. 2000. Temperature correction on Falling Weight Deflectometer measurements. Transportation Research Record 1716: 30–39. FGSV 2003. Arbeitspapier Tragfaehigkeit, Teil B2 FWD: Beschreibung, Messdurchfuehrung, Cologne: FGSV-Verlag. FGSV 2005. Arbeitspapier Tragfaehigkeit, Teil C1 Benkelman-Balken: Auswertung und Bewertung von Einsenkungsmessungen, Cologne: FGSV-Verlag. Kim, Y.R., Hibbs, B.O. & Lee, Y.-C. 1995. Temperature correction of deflections and backcalculated asphalt concrete moduli. Transportation Research Record 1473: 55–62. Park, H.M. & Kim Y.R. 2002. Temperature correction of multi-load level Falling Weight Deflectometer deflections. Transportation Research Record 1806: 3–8. Schulte, W. 1984. Analyse des Temperaturgeschehens im Straßenoberbau und dessen Einfluss auf Ergebnisse von Einsenkungsmessungen nach Benkelman, Bonn: Federal Ministry of Transport. Straube, E., Beckedahl, H. & Huertgen, H. 1996. Begleitende Forschung zur Einführung des FallingWeight-Deflectometer (FWD) in der Bundesrepublik Deutschland, Straßenbau und Straßenverkehrstechnik. Bonn: Federal Ministry of Transport.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Nature resources and functional road design criteria C.A. Lenngren Vectura Consulting, Borlänge, Sweden

R. Fredriksson Svevia, Borlänge, Sweden

ABSTRACT: In many countries, efficient use of mechanistic-empirical methods in pavement design is hampered by rigorous construction control often by component. Little effort is given to the performance of the road as a whole. Some of the tests used are outdated and incorrectly tailored to pavement performance prediction. This seems to work in a conservative way as more and hard to get material is needed for the construction. The present paper discusses some aspects of functional criteria and how natural resources may be utilized better. A case study is presented where unbound material was compacted to a high degree so that the overall quality could be improved. Findings include that functional criteria are well suited to be accepted by industry and authorities alike. Strain criteria for bound layer fatigue is useful for assessing salvage values and remaining life. The top of subgrade strain criterion however, is actually too generic and needs to be revised. 1

INTRODUCTION

1.1 Background The present paper discusses predicaments about using mechanistic-empirical (ME) criteria and presents a new road construction in Sweden where base layers were too thin according to the code. However, the bidding process was primarily governed by functional criteria, with an eight year extended warranty. Surface characteristics parameters rutting and roughness must be kept at bay throughout this time. Prior to the construction, some full scale tests were done with a heavy vehicle simulator (HVS) and a larger subbase aggregate grading was tried. Falling Weight Deflectometer (FWD) tests showed that the bearing capacity was adequate for an alternative thinner design. The current code does not properly consider the benefits of a strong subgrade, which is certainly the case here. If this situation is common, thousands of tons of materials are being wasted each year due to conservative design parameters. The trend towards functional user criteria and contractors taking an extended responsibility for roads including maintenance bodes well for sustainable road construction alternatives. Thus, it is possible to shift focus from fulfilling detailed criteria to unnecessary over-design including life cycle costs. The environmental impact from road construction could be reduced considerably by taking a few simple steps and disregard some old outdated criteria. When the ME concept for the Swedish Road Design Code was introduced some time ago, the traditional layer thickness design tables were abandoned. Like elsewhere strain maximum criteria were introduced governing the layer thickness. This can be regarded as moving into a more analytical way of determining the design. As is common, a response model has to be used that involves a load and elastic properties of the materials. The latter vary with temperature and season. In the code they are tabulated for the six seasons specified for common road construction materials. A pragmatic entrepreneur may think perhaps that one design table is substituted with another and there is nothing new about the mechanistic concept. The present authors tend to agree but there are some important aspects of the mechanistic design that makes it attractive for functionally driven criteria. 799

• New materials are easier to incorporate once their properties are determined • Better and more accurate models could be introduced, the benefit being reduced uncertainties about the construction • Cruder models, requiring less testing could still be used, but with the drawback of an increased uncertainty resulting in a thicker design Working with the ME model it is important to understand that there is still a calibration involved in the design. For instance, in the Swedish design code, the various layers are attributed a stiffness according to the season. The unbound subbase layer is considered to be rather stiff, even during the summer period. High values are rarely backcalculated from field tests. Thus, with one layer systematically overrated other layers or the criterion itself are adjusted to fit the model. Other issues of concern are the global warming and change of vehicles that take place over time. In the assessment of properties one must carefully consider that older laboratory and field testing equipment may not be adequate. As a rule, the test load and derived strains should be near those exerted by traffic. 2

DESIGN CRITERIA

The “bottom of the bound layer horizontal strain” and the “top of subgrade vertical strain” are the two criteria that are commonly used for pavement ME design today. They emanate from the AASHO Road Test and describe road deterioration as a function of load and number of repetitions, (Highway Research Board 1961). As far as regarding the former criterion, which relates to fatigue cracking, specimens can be tested in the laboratory. However, the geometry of the specimen, various apparatus, and the accelerated nature of the test makes it necessary to apply so called shift factors when determining the pavement life in the field from such tests. Still, tests are valuable in that reasonable large changes of the mix design can be evaluated. It is relatively easy to determine equations for new materials in the laboratory. The “top of subgrade vertical strain” criterion is much more difficult to reproduce in practical tests. It was originally determined as a regressed parameter from a full scale accelerated test related to rutting. Over the years many studies have been made to confirm or adjust the relationship. Results vary due to materials used in the construction and subgrade soil as well. Despite all these limitations it is difficult to come up with any better single-parameter based criterion. The strain on the top of the subgrade is also easy to assess in a model with Odemark’s equations, which were commonly used when the relationship was originally suggested! Sometimes, pavement engineers confuse the criterion with subgrade strength or other subgrade properties. It is important to stress that it is not directly correlated to the subgrade per se. After an overlay for example, there is no used or residual life left to consider, and the rutting as it progresses is reset to near zero. Hence, if a new road design is based on the subgrade strain criterion there is an uncertainty of the soil and its variations and in addition to that, the variability of the unbound and bound layers in the structure as well. Further, initial rutting and sequential rutting are not discernable from one another. Surface wear is not included but shows up as rutting when measured with surface monitoring devices. An assumption is made that elastic and plastic strains are related in a predictable way, but they are not if the load range vary much. Clearly, this criterion must be handled with lots of precaution. 3

DESIGN CODE BACKGROUND

Swedish design code of highways emanates from the experience of building roads dating back to the Viking era. In a more modern conception a layer thickness design based on traffic and climate was developed. As more experience with new materials is gathered there are also restrictions established on the materials that may be used concerning the gradation of aggregate, crushed area, angularity of the particles et cetera. 800

For a true functional design some of these restrictions may be obsolete. An example regarding restrictions deals with gradation curves. (Kahndahl & Cooley) reported that hot mixed asphalt concretes may perform well in spite of having gradation curves through a restricted zone. Likely, some failures in the past led to a specification change with the forbidden zone. Maybe, the wrong conclusions were made about the curve, but the forbidden zone remained for many years. The amount of material that had to be wasted over this time remains unknown. For subgrade strength a rather coarse classification based on the materials is used. After preparation of the surface a static plate bearing test is used for construction control. It decides if the surface is well compacted enough to build further on. If the surface is too soft, it may be difficult to compact subbase and base layers appropriately, so a poor foundation may easily deteriorate the whole structure. It has been suggested that the contractor should get a benefit for better than needed values from the test. The present authors agree that strong and well-compacted subgrades may not need as thick subbase and base courses as the average structure, and that over design is just as bad as under design as it does capitalize on limited resources. However, we doubt that a simple static plate bearing test is the right method to rely on predicting future pavement performance. First, the load is only repeated once, but the testing of materials that relates to deformation, i.e. type II rutting requires conditioning involving several hundreds of repetitions in a tri-axial apparatus. (Type I rutting occurs as post-construction compaction by traffic). Secondly, the test acts shallow meaning that it may not be representative for the subgrade behaviour, once the construction is done. Instead, we recommend a model that is able to mimic stress and strain relationships caused by traffic with the finished construction, i.e. the design strain. Further, it must be possible to distinguish between types I and II rutting. There are also examples of weak subgrades where an expensive stabilization may be called for. Again, it is a decision that will influence the use of limited resources. Ideally, a test should simulate the built in-traffic conditions, but that is very difficult or expensive to simulate with overburden pressures et cetera. A falling weight deflectometer (FWD) pulse is however close to loads caused by traffic and serves a better indicator of as-built subgrade strength than many other tests. By varying the load, stress sensitivity can be determined, and risks can be assessed for overloads et cetera.

4

E4 MOTORWAY AT SKÅNES FAGERHULT

In recent years the present authors have come across at least two construction projects where the as-built design was questioned by authorities and admittedly some pavement layer materials were found to be substandard. However, in one case the subgrade and embankment turned out to be rather stiff, or at least much stiffer than the design code table shows. In another case a forced construction on wet cohesive soils, showed that in spite of high strains it should be possible to stay within design limits and perhaps employ some interactive design over the first years of traffic. The former example is discussed in the present paper. The examples lend themselves to suggest a comprehensive test program using the FWD during construction. Thus, building materials could be used to an optimum, preventing over design and help saving resources and the environment. The alternate design example is from a motorway construction in southern Sweden. It is located in a moderately undulating forested area. The subgrade is mostly consisting of a moraine formed during the latest glacial period of the area. The road building code for these circumstances stipulated a traditional gravel-bitumen base layer type. It consisted of 420 mm of subbase material and 80 mm of unbound base material. Two alternative designs were tried in an accelerated load test facility. A heavy vehicle simulator (HVS), was placed in the roadway prior to placing the asphalt layers. A 45 mm asphalt bound capping layer was placed for the purpose of creating a smooth surface for the test. It was removed after the test was completed. Sections were instrumented with pressure cells and strain gauges. FWD testing was done prior to and after the test as well. More FWD 801

testing has been done on an annual basis since the road opened for traffic in October 2004. The final design is shown in Table 1 below. The alternative subbase material consisted of a coarse grade shown in Figure 1. Note that the maximum size aggregate is 100 mm. The standard subbase limits also shown in the graph were modified after the present road was constructed. There was also another alternative in the test, but the coarser grade performed better and it was chosen for the design, It is outside the objective of the present paper to report about this particular test in detail but the coarser material used in the subbase exhibited significantly lower stresses and strains. Thus, the design ought to be less prone to rutting as the top of the subgrade strain was also reduced. In addition, the strain at the bottom of the asphalt layer was also reduced meaning an improved fatigue life. These findings and an extensive laboratory testing of the bituminous layers are published in a note from the Swedish Transportation Research Institute, (Hakim & Said 2000). The report also presents a pavement design for the remaining part of the project based on 30 million equivalent 10 ton standard axle loads. The design is based on the National Swedish Road Administration (NSRA) design tool program PMS Object literally translated as Pavement Management Systems Project Level. It is available as software from the NSRA website, (NSRA). As indicated above, the material elastic properties are based on generic, tabulated values resulting in a bound layer total thickness of 210 mm of which 20 mm is included accounting for studded tire wear. The contractor being confident of the results from the HVS accelerated test decided to use a somewhat thinner design, of 175 mm of bound layers. At the time of the design a change in the code was introduced. The stud wear could be based on the actual property values of aggregates. Thus 7 mm instead of the generic 20 was accounted for stud wear. Further the number of standard axle loads could be interpolated between classes, permitting an additional reduction of 17 mm. As can be seen Table 1.

Figure 1.

Motorway design thickness in mm. Code

Alternative

Passing lane

Setting

mm

mm

mm

Asphalt concrete bound layers Unbound base and subbase Embankment

210 500 n.a.

180 500 120/220

95 585 120/220

Subbase gradation curve.

802

in Table 1, the passing lane was reduced another 85 mm according to actual traffic prediction on this type of rural freeway. The question at the time of opening in October 2004 was of course if the proposed design would suffice? 4.1 Early results Since common use of FWD testing emerged in the 1980:ies it has been suggested that the method should be used for construction control. Even though the method should be suited for this purpose the acceptance from industry has been low. The problem being that the virgin road does not exhibit particularly stiff moduli and that the bearing capacity increases with time. It is a common belief that unbound materials are drying over time, even though no such evidence was found at Minnesota Road Research Site Mn/Road., (Ovik et al. 2000). More likely, the post construction compaction by traffic is a major factor why unbound base layer moduli are backcalculated low on new roads. In more recent studies it has been suggested that type I and type II rutting may be discernable in a single, but more elaborated FWD test. Thus, better predictions can be made about future rutting and specific criteria can be postulated for the two different rutting mechanisms, (Lenngren & Hansson 2004). Four test sections with different height bank fills were examined at the construction site. Test cells M21 and M23 consist of coarser, stiffer subbase material. The other M31 and M33 are references. The first FWD test in the fall of 2004 was done prior to the road opened to traffic and before placing the 40 mm wearing course. The analysis showed a deficit of about 80 mm based on various criteria including one suggested from the research of Mn/Road. i.e. 220 mm of bound layers was stipulated compared to the 175 mm in the final design. Incidentally, this was close to what the code called for, or 210 mm. A second FWD test was carried out in the spring of 2005 with the additional 40 mm wearing course being placed. In the back analysis the asphalt layer, unbound base and subgrade turned out stiffer and the embankment softer than the previous test. See figures 2–3 showing the unbound layer elastic stiffness. Further testing in the years 2006 and 2007 did not show much further growth of strength in the upper layers, meaning that type I rutting had ceased to occur, which would be expected. In May of 2007 the unbound base and subbase actually lost stiffness, of which some may be

500

400

300 MPa

2004 2005 200

100

0 M21

Figure 2.

M23

M31

Unbound layers change of stiffness.

803

M33

attributed to the seasonal variation. On the other hand the embankment continued to grow in strength. The stiffening of the unbound layers seems to propagate downward with the number of loads, which was also seen in a previous study, (Hansson & Lenngren 2006). The asphalt strain increased from the target 150 microstrain to 160 microstrain, which still is near the adjusted target for the remaining design traffic. The top of subgrade vertical strain was reduced from 148 microstrain to 122 microstrain in the two years between 2005 and 2007. The target value is 240 microstrain so the rutting criterion is met by a large margin. For the upper layers the change is attributed to the post-compaction of traffic. The apparent softening of the subbase is more likely an effect of different stress condition with less

800

700

600

MPa

500

Embankment '04 Embankment '05 Subgrade '04 Subgrade '05

400

300

200

100

0 M21

Figure 3.

M23

M31

M33

Embankment layer and subgrade first year change of stiffness.

300

250

Microstrain

200 Asphalt '04 Asphalt '05 Subgrade '04 Subgrade '05

150

100

50

0 M21

Figure 4.

M23

M31

First year change of strain.

804

M33

bulk stress when the upper layers spread the load better. This layer could also be wetter after the spring thaw. The subgrade consisting of cohesive soils also appear stiffer if the deviator stress goes down. The FWD testing at different load levels indicated that this may be the case. However, no further study was done in this particular case, but the assumption that the upper layers did gain strength was indeed verified. An overlay design based on a test in the spring (and adjusted for seasonal change) now suggested an overlay of 0–30 mm for the various test sections and actually very close to the target design if traffic lateral wander is considered. Figure 4 shows the change of strain for the four test sections. The asphalt fatigue strain is critical with the target strain being 150 microstrain. 4.2 Results after four years in traffic In spite of the relatively low critical strain values, the rutting performance of the road showed nothing but mediocre results after four years of traffic as the average rut depth as measured on the surface in the northbound direction was approximately 8 mm. Allowing for an initial rut depth of 3 mm, something like 5 mm is more likely to be expected by the model. A rut measured on the surface is the result of many processes though. Studded tires are allowed during the winter season contributing to the effect. The shape, distribution and distance between ruts all point to different layers and mechanisms behind the ruts, (Lenngren 1988). Some interesting observations were made: • The deepest ruts were found on bridge decks • The least rutting was found under overpasses This led an investigation team to believe that the rutting took place in the asphalt layer as plastic deformation. The northbound direction is indeed facing southwest being exposed to sunlight in the afternoon. In addition, heavy trucks arriving to seaport Helsingborg seem to agglomerate in the afternoon on their way north. The pavement temperature is considerably lower in the shade of the overpasses and hence the asphalt concrete is stiffer and less prone to deform. The deeper ruts found on the stiff foundation are attributed to the fact that the material is pushed to the side, where some heaving occurs, resulting in deeper ruts as

Figure 5. A beam was sawed from the slow lane showing significant deformation of the wearing and binders courses.

805

measured. A cross-section beam was sawed through the asphalt layers as to verify which layer was deformed the most, see Figure 5 below. 5

NON DESTRUCTIVE TESTING FOLLOW-UP

A FWD was brought to the site in May 2008. Pavement temperature was recorded at depths of 40 and 80 mm respectively. During the unusually cold but sunny day the pavement temperature rose from 15 to 25°C during the test. In the shade under the overpass the temperature was more or less constant at 15°C. A second test was slated to July when it was much warmer. Then, the pavement temperature was 40°C at a depth of 40 mm and 38°C at 80 mm. 80 70 60

Load [kN]

50

D0 D20 D30 D45 D60 D90 D120

40 30 20 10 0 –50

0

50

100

150

200

250

300

350

–10 Deformation [mu]

Figure 6.

FWD load-deformation plot at 40°C. 80 70 60

Load [kN]

50

D0 D20 D30 D45 D60 D90 D120

40 30 20 10 0 –50

0

50

100

150

200

–10 Deformation [mu]

Figure 7.

FWD load-deformation plot at 21°C.

806

250

300

350

In the shade it was only 21°C though. The linear layer elastic backcalculation showed very stiff unbound materials but the asphalt layers were backcalculated low as was expected at high temperatures. Time histories showed a large difference between shaded and sunny areas for the center deflection. Note that the sensor at 1200 mm showed an almost elastic response. This sensor is mostly responding to subgrade deformation, but nevertheless it is unusual to see this response as there is normally some damping in all materials. Anyway, the test confirmed that rutting most likely occurred during hot weather in the asphalt-bound upper layers, see figures 6 and 7. In an attempt to backcalculate the wearing, binding and base courses separately, the latter became notably stiffer than the upper two layers. The temperature gradient was about .005 K/m at the time, so it is not entirely due to the colder state. It is more likely that the deformation and inherent attenuation within the materials is redistributing the load in the time domain in a positive sense. The set up and spacing of the FWD sensors were too crude to confirm this, but the phenomenon is certainly worth studying in further evaluations. 6

DISCUSSION

In Sweden, like in many other countries, ME based pavement design methods are replacing the former empirical methods. However, these methods turn out to be very difficult to implement in reality. Authorities and industry have to work together on this task and come up with good proposals on a number of issues; what software to use, proper testing equipment etc. New methods and materials must be dealt with and it seems that the process of legitimizing new approaches has become more complex and harder to get through. In spite of the two rather simple strain criteria that govern the design, there are more and more restrictions on materials and more production control is usually required. The present authors recognize that all these measures are important for quality. At the same time they sometimes contribute to the waste of materials and that limited resources thus are being unnecessarily strained. In the present example about 35 mm less asphalt concrete was used compared to the specifications in the right lane and 115 mm in the passing lane. This is an average saving of over 500 metric ton per lane km. Thus, user-defined functional criteria seem to be a plausible solution to forgo some restrictions. In reality it means that the contractor is allowed to experiment, some would say gamble, more with the design. The driving force is of course cheaper solutions and perhaps a more efficient way of building. Among concerns about foregoing construction control is the time aspect as the service life of a road sometimes outlives the life of a construction company. Sheer functional criteria would likely keep rutting and roughness down, but what about fatigue cracking which does not affect traffic directly? In reality an entrepreneur could use a stiffer binder and limit rutting at the expense of a reduced fatigue life. Warranties over a long time seem to be necessary perhaps combined with a responsibility of maintenance. It will be necessary at all times to be able to at least roughly calculate a salvage value. The key to the relationship between structural status and the remaining functional prediction of service is still “the strain at critical strain points” in the structure. For a start, the two classical critical points can be used. However, deformation in each layer can now be calculated and should be used instead as field validation of new FWD backcalculation techniques continue to improve. To successfully employ mechanistic design concepts the following should be considered: • Functional criteria are well suited to be accepted by industry and authorities alike • Strains are ideal to assess salvage values and remaining life of bound layers • Deformation of layers should be calculated with concern of initial, type I and long/time type II rutting • Strains must at all times in the construction process be calculated for stress conditions near those exerted by traffic • Criteria may have to adjusted as improved unbound materials may contribute to increased rutting in bound materials 807

7

CONCLUSIONS

Employing mechanistic road design is becoming more common throughout the world today. However, to rely on the strain at a couple of critical points often calculated indirectly seem to be a little too much for most highway authorities. Therefore, most of the construction control tests remain; needed or not. However, sometimes these prevent better and cheaper methods from being developed. By interpolating actual traffic to a certain strain and by choosing a stud wear resistant material the bound layers could be reduced by 30 mm or about 14%. By treating traffic in the fast lane separately a 125 mm reduction of bound layers was achieved. That is a 60% reduction. The seasonal change of layer moduli is tabulated for new roads in Sweden. No particular consideration is taken to unusually stiff subgrade or embankment layers mitigating an opportunity to save materials. The motorway at Skånes Fagerhult shows a 40 mm reduction of the asphalt layer if considerations to the present conditions are taken. This effect was not used, but shows up in the bearing capacity measurements. Nevertheless, rutting has occurred in the binder and wearing courses. This type of rutting becomes more severe if the unbound layers are stiff. This is a reminder that ME criteria may have to be recalibrated if substantially better or different materials are being used. The authors see a great potential for saving resources by the mechanistic approach and functional criteria working together. As mentioned in the paper it is not a trivial task to implement mechanistic design to replace older code built entirely on empirical knowledge. However, with sound field testing and tools to backcalculate mechanical properties, we think there is reason to adopt these ideas. Hopefully, our experience will help people interested in getting started. More advanced models employing time history evaluation is recommended. A thorough testing with FWD using repeated multi-drop sequences with increasing and decreasing loads is helpful in assessing soil and materials properties other than pure elastic. REFERENCES Hakim, H. and Said, S. 2004. “Utvärdering av bitumenbundet bärlager, E4 Skånes Fagerhult”. VTI Notat 37 (Swedish). Hansson, J. and Lenngren, C.A. 2006. “Using Deflection Energy Dissipation for Predicting Rutting” Proceedings, 10th international Conference on Asphalt Pavements, Quebec, Canada. On CD-ROM available from ISAP. Highway Research Board. 1961. “The AASHO Road Test History and Description of Project”. Special Report 61 A. Publication 816. Kandahl, P.S. and Cooley, Jr., A. 2002. “Investigation of the Restricted Zone in the Superpave Aggregate Gradation Specification”, in Journal of the Association of Asphalt Paving Technologists. Volume 71. pp. 479–534. Lenngren, C.A. and Hansson, J. 2004. “Comparing FWD Initial Tests with HVS Induced Initial and Long-Term Rutting”. Proceedings 2nd international Conference on Accelerated Pavement Testing, Minneapolis, MN USA. On CD-ROM. Lenngren, C.A. 1988. Some Approaches in Treating Automatically Collected Data on Rutting. In Transportation Research Record 1196, Pavement Evaluation and Rehabilitation 20–26. Washington, D.C. NSRA. 2008. National Swedish Road Administration web-site. www.vv.se Ovik, J.M., Birgisson, B. and Newcomb, D.E. 2000. “Seasonal Variations in Backcalculated Pavement Layer Moduli in Minnesota” in ASTM STP 1375-EB Nondestructive Testing of Pavements and Backcalculation of Moduli: Third Volume.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Lightweight deflectometers for quality assurance in road construction P.R. Fleming & M.W. Frost Loughborough University, England, UK

J.P. Lambert Scott Wilson, England, UK

ABSTRACT: The use of Lightweight Deflectometers (termed LWDs in Europe, and occasionally PFWDs in the USA) for construction quality control or material investigation for road construction has increased worldwide. In the UK the change in pavement foundation design to a ‘performance based approach’ has brought about the use of Lightweight Deflectometers for field assessment of stiffness modulus. This paper reviews the LWD as a field evaluation tool. It discusses in some detail the test variables that can influence and affect the field data quality, and presents brief summaries of recent fieldwork where an LWD has been used as a quality control tool. The paper concludes both on the LWD usefulness and also its limitations for a variety of earthwork and road assessment scenarios, and describes a field test protocol for its use on a variety of materials. The findings demonstrate the flexibility of the LWD but also show that its determination of ‘stiffness modulus’ may differ from that of the conventional Falling Weight Deflectometer (FWD) to a varying extent. The paper provides a useful reference document for LWD users, consultants, material specifiers, contractors and clients. 1

INTRODUCTION

1.1 Paper aim This paper reviews the use of Lightweight Deflectometers (LWD). In general it appears that the term PFWD can mean any portable device for measuring a stiffness of materials in situ, and the term LWD refers to the specific type of PFWD commonly used in Europe, manufactured by Grontmij-Carl Bro in Denmark or Dynatest of Sweden. To further confuse matters the term ‘Dynamic Plate Test’ has also been used in Europe to distinguish it from the traditional Static Plate bearing test. The LWD is increasingly used for investigations of road construction materials and quality control. A background to the LWD development, a review of recent case studies, correlation with the Falling Weight Deflectometer (FWD), and some specific laboratory investigations are presented and discussed. A ‘best practice’ guide is also briefly presented and discussed. This paper is intended for reference by LWD users, consultants, material specifiers, contractors and clients. 1.2 Review of portable field stiffness measuring devices Many questions have arisen about the use and suitability of PFWDs, specifically when they are used as part of construction control within an end product or performance specification. The focus of much of the work in the UK has been on demonstrating the usefulness and reliability of the LWD through field trials. Little work has been carried out on detailed assessment of the influence of the test device variables on the potential outcomes of the measurements. Such variability assessments have mainly been performed on natural materials and these are intrinsically difficult to use to study repeatability and accuracy. 809

The LWD has been available in its current form for several years, and earlier somewhat similar devices existed for measuring stiffness in situ included the prototype TRL Foundation Tester (TFT) (Rogers et al, 1995), the Natural Vibrations Method (NVM) (Fleming and Rogers, 1995), Leichtes Fallgerät from Zorn (known as the ‘German Dynamic Plate’ or GDP) (Fleming et al, 2002), the Soil Stiffness Gauge (also known as the SSG) (Fleming et al, 2002), the Loadman from Finland, the ODIN apparatus (Fleming and Rogers, 1995) the Clegg Hammer (Fleming and Rogers, 1995). All these devices have been described in more detail elsewhere, and can be categorized by the load pulse rate and intensity of maximum load (or contact pressure) (Fleming and Rogers, 1995). To summarize, the ODIN (a research prototype) and Clegg (often used for compaction control) comprise rapid undamped impact tests, the SSG (not specified in the UK) and NVM (a research prototype) comprise small devices that measure the response to low energy impulses applied over a range of frequenciesbut only impart very small strains to the soil under test. The Loadman and GDP comprise damped impacts of a falling mass onto a bearing plate, (the novelty of the Loadman stemming from its enclosed tube apparatus), and are in many ways mechanically similar to the LWD except that both interpret the impact using an accelerometer rather than directly from a load cell, and in general the interpreted deflection has been observed to be less reliable (Fleming et al, 2002). The TFT was a research prototype developed in 1992, and similar to the current LWD in all ways except it had a relatively high mass bearing plate. The TFT was used in research on live sites in the UK until around the year 2000, whereupon the LWD became commercially available and was the adopted portable dynamic plate test in the UK although it was not formally specified in detail in UK guidance until recently (Highways Agency, 2006). Whilst all the portable devices have their advantages and disadvantages the current LWD (manufactured by Grontmij/Carlbro and Dynatest) has emerged as the most acceptable tool for routine use in the UK whilst retaining some flexibility in test protocol, such as variable plate size, load magnitude, and data collection, with the added and important factor that it most closely resembles the loading rate and area of a (single) moving wheel (Fleming and Rogers, 1995), and functions very similarly to the FWD and uses the same transducer technology. One particularly important aspect when considering the in situ measurements made is the interpretation of the deflection under load. In general the device software integrates the geophone (velocity transducer) signal to determine the maximum (or peak) deflection value. This has two important ramifications, the first being that under test the peak deflection may not occur at the same instant as the peak load due to dynamic effects, often observed more prominently on lower stiffness materials. The second facet is that the maximum deflection may include an element of permanent/plastic deflection in addition to recoverable/elastic deflection dependent upon the ‘strength’ of the materials under test, and the efficacy of the contact between the geophone foot and the material under test. Thus, it can be argued that that the term ‘elastic’ stiffness (E) is not necessarily what the device measures, and in the UK the term stiffness modulus is increasingly used to describe the LWD measured value. The direct use of the measured value of ‘stiffnes modulus’ as ‘elastic’ input values into design packages that utilize linear elastic algorithms therefore needs careful consideration. The LWD is shown in Figure 1. The test variables include drop weight, drop height, load contact area, rate of loading and the number of geophones (up to two extra geophones can be connected to allow a limited deflection bowl to be measured). The stiffness modulus (E) from the LWD is calculated using equation 1 given below. E =

A ⋅ P ⋅ r ⋅ (1 − ν 2 ) (MPa ) d0

(1)

where: E = stiffness modulus (MPa). A = plate rigidity factor, default = 2 for a flexible plate, π/2 for a rigid plate. P = maximum contact pressure (kPa)—controlled by the operator and recorded/displayed. r = plate radius—can be controlled, 50, 75 and 150 mm options, UK has adopted 150 mm. 810

Figure 1. Lightweight deflectometer—in use on compacted recycled crushed demolition rubble. Note the 300 mm diameter plate, the falling mass ready for release from a high drop height, and the four rubber buffers which damp the impact and control the load pulse duration. This model is shown with a hardwire transmitting the load cell and geophone measurements.

ν = Poisson’s ratio (usually set in the range 0.3–0.45 depending on test material type). d0 = central geophone peak deflection (mm)—recorded and presented on the readout unit. The standard equation course assumes a homogeneous linear elastic half space. The depth of significant stressing during a dynamic plate test has been the subject of much speculation during several works (Chaddock and Brown, 1995, Fleming et al, 2000 & 2007, Frost, 2000 and Hoffman et al, 2004, and Mooney and Miller, 2008) and it would appear that in many cases the depth, expressed as a function of the plate diameter, has been quoted as 1–1.5 diameters. Static elastic theory suggests 1.5 diameters. However, it is interesting to note that there is a clear argument to suggest that for layered road foundations the depth of significant stressing is likely to be affected by the stiffness modulus ration of adjacent layers, especially if the upper layer is less than one plate diameter in thickness. In part this is also a function of the rate of loading which is device specific related to the performance of the buffers used to damp the load pulse. In the UK sub-base is usually between 150 m and 225 mm thick. The effect of layers has been explained as a factor in assessing the correlation between the fullscale FWD and the smaller portable devices, especially where the load rate of the FWD is slightly longer. One of the difficulties in comparing between devices is the stress dependency (i.e. nonlinear stiffness) of many road foundation materials. The recent work of Mooney and Miller (2008) is an interesting and useful addition to the ongoing scientific debate in that the experimental field work on instrumented sections of granular foundation clearly showed the nonlinear stiffness modulus with depth was required to match predicted to measured absolute values and that equation 1 is a gross simplification of reality. 1.3 Factors influencing LWD test results Controlled laboratory research has considered the potential influence of the many test variables described above to assess the repeatability and reliability of the devices. Over a 811

series of smaller projects, the following variables have been investigated, including buffer temperature, plate diameter, drop height, drop weight, geophone/loading plate attachment (fixed/loose), use of extra geophones (back analysis), plate-surface contact and depth of significant stressing. The buffer temperature effects and plate-surface contact effects are described in detail below. The influence of temperature on the LWD buffers and hence loading characteristics was evaluated and it was found that regardless of buffer temperature the measured stiffness remained effectively constant, the only readily observable change was a slight reported lengthening of the load pulse, which was seen to increase with buffer temperature from 18 to 20 milliseconds. This would be expected as the buffers soften slightly when heated. An investigation was made (Fleming et al, 2007) into the influence of the efficiency of the plate-surface contact, aimed to evaluate if a ‘bad’ drop could be recognized in the device force and deflection versus time signal (shown on the readout unit). It was clearly demonstrated that an improvement in the regularity of the shape of the deflection trace was observed with improved bearing plate contact. In addition, during the test there was observed to be some bounce and/or horizontal movement of the apparatus, and some vibration back through the device again suggesting poor uniformity of contact. However, the judgment of poor contact is generally subjective, and the on-site assessment of impact quality is potentially difficult. In the laboratory results for one typical test the reported stiffness was 75 MPa for the ‘poor’ contact and 145 MPa for the ‘good’ contact. On site such variability in stiffness is common. It was shown that there is merit in examining in more detail the data signal generated at the time of test, and possibly the development of a routine within the software to identify poor quality impact data. Previous work (Nunn et al, 1997) identified site measurements were of poorer repeatability where the aggregate had become segregated at the surface, in particular where there was a lack of fines. It is also of interest that the geophone and protruding foot are ‘spring loaded’ to ensure constant contact with the surface. On weaker materials this has been observed to cause local punching failure and affect the magnitude of peak deflection interpreted. It is clear that good site testing protocols using trained and experienced operators is vital, as discussed further in Section 3. 2

CASE STUDIES AND CORRELATIONS

2.1 Case study 1—in service foundations assessments The LWD has been used successfully to assess existing foundations beneath worn sections of highway proposed for reconstruction. One recent scheme comprised a minor road reconstruction where upon the confined foundation stiffness was measured by the LWD in the range 150–245 MPa with the 300 mm plate. The variation was attributed to variations in foundation thickness between 300–400 mm, evidenced in the trial pit excavations also carried out but at limited locations. However, the confined stiffness values were considered sufficient to increase confidence in an overlay design. On a second recent scheme the LWD foundation stiffness through core holes was determined as relatively low with an average of 72 MPa. This was used as a primary factor in deciding to excavate the road surfacing and compact the foundation prior to reconstruction of the bound road surface. Soft spots were identified, removed and replaced, based on frequent LWD testing during the reconstruction phase. Conventionally Dynamic Cone Penetrometer (DCP) tests are performed through the base of core holes to evaluate foundations by measuring the change in resistance to penetration with depth, (equated to CBR with depth for convenience). This enables the engineer to better understand the current condition of the existing foundation. However, the possibility of direct stiffness measurement on the foundation, through core holes, with the LWD further supports back analyzed foundation stiffness values derived from a structural Falling Weight Deflectometer survey. DCP testing also has a significant risk in locations densely populated with services, making an alternative means of testing more attractive. Ideally the 300 mm diameter LWD bearing plate is utilized, through a 450 mm diameter 812

core hole. The LWD can be used within a 200 mm diameter core hole if the 100 mm LWD bearing plate is used, though it has been observed that this smaller diameter provides poor stability during testing and is more affected by large particles. The experience so far is that good quality data can be obtained with the 300 mm diameter plate through (air cooled) core holes. 2.2 Evaluation of existing fill The LWD was used successfully on a railway viaduct, to evaluate the variability of the existing fill once the ballast had been removed, prior to reopening as a light rail corridor. The LWD showed a good correlation with locations where the fill was thinner over concrete foundations, (proved by subsequent trial pitting). The mean stiffness value along the route of 190 MPa suggested in general a relatively compact engineered fill—though no previous construction records existed. The fill was left in place and formed a suitable substrate to the new trackbed construction. On a similar scheme the LWD was successfully used to measure the stiffness modulus of existing fill materials at an old factory area that varied in composition from predominantly gravelly clay through to areas of recycled crushed concrete. Part of the site was to be used to form a new site access road to a series of new warehouses. The stiffness identified many soft spots, predominantly in the clay fills, where the water content was above the plastic limit. In the areas of crushed concrete high stiffness values were observed, exceeding 250 MPa in general. Much of the better performing material was left in situ and soft spots excavated and replaced with compacted good quality stone. 2.3 Site quality control The LWD is growing in acceptance as a material and workmanship quality control test on a number of minor road schemes—using the UK target values for lower class foundations. In one recent example the LWD was used to provide assurance of the foundation sub-base construction for a school access and service road that was designed to accommodate some heavy vehicles. The target stiffness of 80 MPa was used (Highways Agency, 2006) for 24 hrs after construction, prior to laying the bituminous surfacing. Tests were carried out at 10 m centers in both wheel paths, and of the approximately 100 tests carried out a limited number fell below the target and such areas were remedied by further compaction, and re-tested. 2.4 Slow curing materials The issue of compliance testing on slow curing bound materials in relation to the timing of testing and permission for construction traffic to be allowed access is currently an issue in the new UK guidance. However the LWD has proved useful in monitoring the development of stiffness with time on such materials. As part of a research project for WRAP (Waste and Resources Action Programme—a UK organization aimed at improving sustainability in construction) the LWD was used to monitor the stiffness modulus and stiffness gain with time of a range of hydraulically bound service trench backfill materials. In one case the aim was to reuse the trench arisings, (an as dug gravelly clay), by reworking it with a proprietary binder to improve the properties, and then replacing and compacting it. The data showed the initial stiffness of the reworked material was slightly above the target for granular materials (80 MPa) and after 7 days had reached in excess of 200 MPa which was considered wholly acceptable, showing the mix to be fit for purpose (and providing a basis for mix efficiency and binder content). 2.5 Motorway widening schemes The UK is currently constructing many sections of motorway widening to increase capacity on the national network. The LWD was used recently on one such scheme, (a major junction 813

widening scheme using the latest performance related design and specification (Highways Agency, 2006). In this case the contractor had proposed an interesting variation in foundation in comparison to traditional designs, showing the flexibility of the new UK guidance. A traditional Type 1 material (a well graded crushed rock) was to be overlaid with an asphalt layer to form a high stiffness (Class 3) foundation. The LWD was used in parallel with the full size FWD. In general both suggested the sub-base was well constructed and satisfied the design target value of 80 MPa, except in two locations that were remediated. The average correlation between the LWD and FWD was close to one, although the point to point correlation showed relatively low repeatability in this case. 2.6 Correlations & site variability In many instances it is considered that the use of the LWD as a ‘relative’ measure of stiffness modulus in situ is appropriate—e.g. in the case of looking for variations in stiffness and soft spots for subsequent investigation or remediation. However, in the UK the philosophy adopted for motorway and trunk road schemes is one of ‘absolute’ stiffness values compared to site target values during (re)construction schemes. In this latter case there is a need to provide assurance that an LWD measured stiffness is credible, and this has been assessed on the basis of correlations to the full size FWD derived stiffness (at the same contact stress). The determination of such correlations on live construction sites has been the focus of much of the applied research work in the UK during the development of the relatively new UK road foundation design and specification (Highways Agency, 2006). The experience in the UK is generally that the LWD does, in general, record similar stiffness modulus values to the FWD where the FWD applies the same contact pressure and a similar loading time. The FWD does apply an increased static preload however, due to its greater static mass. Fleming et al, (2007) recently summarized the range of correlation coefficients as 0.8 to 1.4 for LWD:FWD. Other work such as by Nazzal et al, (2006) and Hejlesen and Bultzer (2008) concluded that the ratio of LWD to FWD stiffness was close to unity. The latter work included changing the buffers on the FWD to achieve a similar load pulse duration, which improved the correlation. In addition to the correlation between devices, it is of interest to observe the typical variability of stiffness with position along a section of notionally the same construction (i.e. same materials, layer thickness and water content). In the UK data has been analyzed in detail and a general pattern has emerged, which is considered useful for selecting the appropriate frequency of testing and also the setting of target values for quality assurance and quality control on site. In general, the variability in any one trial section can be usefully reported as the Coefficient of Variance (CoV), which is the ratio between the standard deviation and the mean for a test section. The reported range of CoV observed was 25–60% for FWD and LWD on predominantly fine grained subgrades, perhaps due to variation in water content. For granular capping (subgrade improvement) layers the CoV range observed was 10–40% (and higher values when wet). For sub-base materials (highly specified well graded crushed rock) the CoV observed was typically less than 15% (again observed to be higher on very wet sites). In a presentation at an LWD/Intelligent Compaction user meeting in the fall of 2007 in Minnesota, it was very encouraging to note that the values of CoV reported from a wholly independent study were almost identical for similar material types (White, 2007). 2.7 Industry opinions (UK) Loughborough University has held two one-day seminars on the use of LWDs in practice, in 2007 and 2008. These were well attended and it was clear from the numbers attending that the interest in LWDs is increasing in the UK. Several useful datasets of information and opinions were put forward in the formal presentations, together with useful overview of industry trends and opinion from the discussion sessions. Where practicable the salient points have helped inform the best practice guide described in Section 3. A brief summary of the main points from each seminar are presented in the following paragraphs. 814

From seminar 1 (in 2007) it was clear that LWD manufacture and specification were still developing, in response to industry feedback. This was primarily to provide robust wireless data transmission and user friendly visual display and data analysis tool for site use. The Dynatest LWD was presented as an alternative to the more widely known Carlbro (now Grontmij) model though there is little to differentiate them. The presentations and discussion identified some concerns over the widespread use of LWDs in quality control for major schemes, in particular: on stiffer stabilized foundations where there was concern over inadequate dynamic energy of the LWD to produce a meaningful deflection magnitude. No industry standard or a site test protocol had, at this time, been agreed or published, and there was a long discussion over the number of drops and measurements per test location that was most appropriate, the frequency of tests, data quality issues, and timing of the testing, especially in relation to poor weather and its effects. Experience suggested large variations in stiffness through wetting and drying of many foundation materials though it was agreed that just prior to laying the next layer was an appropriate time to test for compliance. Concerns were also expressed over how to objectively assess the quality of a single test and this was discussed at length with regard to experienced operators getting a ‘feel’ for the test efficacy—though it was pointed out that no formal training schemes or certifications were yet available; concerns were also expressed over repeatability and reproducibility between devices—and no data was yet available to confirm the ‘uncertainty’ of the measurements made by different devices. Seminar 2 (in 2008) was a stimulating and useful update of how the LWD had been quite widely used in recent practice and demonstrated the increasing confidence in its use in a commercial environment and that it was generally accepted by Clients for materials assessment and design/construction assurance. A series of presentations descried how the LWD was used as a versatile and simpler/cheaper alternative to the full size FWD. Many of the issues raised during the first seminar a year earlier had, it seemed, been addressed through experience and a natural evolution of practice. A draft best practice guide was presented by a manufacturer, discussed further in Section 3, including a proprietary data quality algorithm that could interrogate the test output signal for indicators of ‘problems’ in the deflections recorded. A ‘hands on’ session was also included for those new to LWDs to experience undertaking tests and analysis on a variety of materials compacted into boxes. The closing discussion set the agenda for the UK to produce an important ‘best practice’ document and training procedure for all operators to gain a recognized consistent standard, for achieving the protocol in practice. Currently the best practice guide and training seminar are being sponsored in the UK’s by Britpave (the UKs concrete paving association), which includes members from all aspects of commercial highways work. It is looking to gain acceptance from the UK Highways Agency who are the client for all major road network in England. 3

BEST PRACTICE GUIDE

3.1 Aim The aim of the proposed ‘best practice’ guide in the UK is to ensure that there are: competent operators; well maintained and calibrated equipment; regular consistency checks; industry standard training; clear effective site procedures; and compatibility of data output and reporting. 3.2 Draft testing protocol Before the LWD is used its calibration status and its consistency should be checked to ensure reliable accurate data will be measured on site. Appropriate site records should be taken to detail factors such as weather, construction detail, notable visible defects and test location reference. The device’s mechanical set-up including plate diameter and number of geophones should be checked and corroborated on the read-out unit to ensure the settings are correct. To ensure the test location selected is representative of the local area (i.e. for evenness, gradation etc) seating drops at the target applied stress are performed (it is proposed to reduce 815

this to one seating drop on bound material). The target maximum contact stress is in the range of 100 to 200 kPa, and should result in maximum deflection of between 40–1800 μm. The drop height can be adjusted during seating drops to achieve the target contact stress. In the new UK performance specification the target stress is currently set at 100 kPa for granular materials and 200 kPa for bound materials. (Note: to achieve 200 kPa contact stress with a 300 mm diameter plate requires extra falling weight masses to be added from the standard 10 kg to either 15 or 20 kg. An alternative is to reduce the plate diameter to 200 mm, then the 10 kg falling mass is sufficient.) To measure the stiffness modulus, after seating further drops are carried out at the required target stress comprising three drops on unbound materials and one drop on bound materials. The consistency of the results from the three drops should be high and within 10%, or for the bound materials the recorded drop should be close to the seating drop. The quality of impact signal data should be checked to ensure smooth load and deflection pulses. This can be done sufficiently on the screen of the readout unit. Repeat tests should be performed were inconsistent or poor quality data are given, or the absolute values fail the site compliance targets set in the design, but all the data must be reported. If the aim is also to assess the stress sensitivity of the materials (useful in design and back analysis procedures), then it is recommended that for unbound materials and cohesive materials the three recorded drops are carried out at increasing contact stress (e.g. 40, 70, 100 kPa) and several are done per characteristic construction/material and/or per day. The determination of approximate heights to provide these contact stresses is usually assessed on site at the start of the day. 3.3 Test quality assessment In the absence of any widely available algorithm software to interrogate the test output signals, it has been deemed sufficient to utilize simple diagrammatic examples of good and poor impacts, as shown below in Figures 2 to 4. The use of a material to improve the contact between the bearing plate and the soil surface has also been the subject of some research and discussion. However, to date it has not been formalized into a clear and objective procedure. Fleming et al, (2007) reported varying success from smoothing a single sized sand over a coarse or rough surface to improve the contact efficacy. This changed the measured stiffness modulus by up to 100% from the original poor data, and in general a small amount of sand improved contact, though excess sand could reduced the stiffness modulus measured. The detail of the best practice guide is yet to be finalized in the UK, but may include requirements for calibration certificates and also internal equipment checks to be carried out on known surfaces (e.g. a concrete floor) to check the device is working prior to transporting it to site.

Deflection (μm)

Time (ms)

Figure 2.

High quality test with deflection—time pulse returning to zero.

816

Deflection (μm)

Time (ms)

Increasing number of blows at same point

Deflection (μm)

Figure 3. Effect of compaction under testing showing reduced deflection with number of blows and a ‘permanent’ element of the deflection—time pulse.

Time (ms)

Figure 4. This response may be due to hard material causing the plate to lift off the ground or the presence of excess water, characterized by the high ‘rebound’ of the deflection to a positive (upward) value in contrast with figure 2.

4

CONCLUSIONS

The LWD is proving to be a versatile and portable stiffness modulus measurement tool. It appears to be increasingly used on a variety of materials/constructions, both on major schemes and minor road constructions in the UK, primarily during construction but also in investigations prior to reconstruction. It is now specified in recently published UK road foundation design and specification guidance. The LWD is increasingly being used as a FWD substitute, and has the advantage of portability and ease of use, in addition to lower cost. The correlation of the LWD to FWD stiffness is often reported as approximately 1, but appears to be variable, and perhaps site dependent. Recent work has added to the research findings that the depth of significant stressing is around 1 plate diameter. 817

Several factors affecting LWD data quality and the development of ‘best practice’ guidance have been presented and discussed. There is some concern over the influence of plate contact efficacy, though some qualitative methods of evaluating the test integrity by the signal shape are emerging. Future workshops and reviews of practice are expected to evolve this guidance further. The UK is slowly implementing the best practice, concurrent with a new training programme to ensure all site operators are practicing consistent methods for measurement and reporting. ACKNOWLEDGEMENTS The authors would like to acknowledge the UK Highways Agency, and the Centre for Innovative Construction Engineering at Loughborough University for past collaborations and funding various work packages summarized herein. The opinions expressed are solely those of the authors. REFERENCES Chaddock, B. and Brown, A.J. 1995. Road Foundation Assessment. Proc. of the 4th Int. Symp. Unbound Aggregates in Roads (UNBAR4), Nottingham University, 1995, pp. 200–208 (check). Fleming, P.R, Frost M.W. and Rogers, C.D.F. A Comparison of Devices for Measuring Stiffness In situ. In Unbound Aggregates in Road Construction, editors Andrew R. Dawson, Balkema, 2000, pp. 193–200. Fleming, P.R., Dixon, N., Lambert, J, and Young, C. Monitoring the Performance of Hockey Pitches During Construction, The Engineering of Sport 4, Kyoto, Japan, 2002, pp. 545–552, ed. S. Ujihashi, and S. Haake, Blackwell. Fleming, P.R., Lambert, J.P., Frost, M.W., and Rogers, C.D.F. In-situ Assessment of Stiffness Modulus for Highway Foundations During Construction. Presented at the 9th International Conference on Asphalt Pavements, Copenhagen, Denmark, August, 2002, p. 12, CD-ROM. Fleming, P.R., and Rogers, C.D.F. Assessment of Pavement Foundations During Construction. In Transport, Proceedings of the Institution of Civil Engineers, Vol. 111 (2), 1995, pp. 105–115. Fleming, P.R., Frost, M.W., and Lambert, J.P. “A Review of the Lightweight Deflectometer (LWD) for Routine In situ Assessment of Pavement Material Stiffness”, Transportation Research Record 2004, Soil Mechanics, 2007, pp. 80–87. ISSN 0361-1981. Frost, M.W. (2000): The Performance of Pavement Foundations during Construction. Ph.D. Thesis. Loughborough University. Hejlesen, C., and Baltzer, S. 2008. New Danish Test Method for the Lightweight Deflectometer (LWD). In Advances in Transportation Getoechnics, eds. Ellis, Yu, McDowell & Thom, Taylor and Francis, pp. 157–160. Highways Agency, Design Guidance for Road Pavement Foundations (Draft HD 25), Interim Advice Note 73, Highways Agency, London, February 2006. Hoffman, O. Guzina, B.B., and Drescher, A. 2004. Stiffness Estimates Using Portable Deflectometers. Transportation Research Record 186, 59–66. Mooney, M.A. and Miller, P.K. 2008. Analysis of Light Falling Weight Deflectometer Test based on InSitu Stress and Strain Response. J. Geotech. & Geoenv. Engineering, ASCE, to appear 134(10). Nazzal, M., Abu-Farsakh, M., Alshibli, K. and Mohammed, L., Evaluating the Potential use of a Portable LFWD for Characterising Pavement Layers and Subgrades. Geotechncial Engineering for Transportation Projects: Proceedings of Geo-Trans 2004, Los Angeles, US, 2004. Nunn, M.E., Brown, A., Weston, D., and Nicholls, J.C. Design of Long Life Flexible Pavements for Heavy Traffic, TRL report 250, 1997, TRL Limited, London, ISSN 0968-4107. Rogers, C.D.F., Brown, A.J., and Fleming, P.R.; Elastic Stiffness Measurement of Pavement Foundation Layers, Proc. of the 4th Int. Symp. Unbound Aggregates in Roads (UNBAR4), Nottingham University, 1995, pp. 271–280. White, D. 2007. Intelligent Copmaction and Field Assessment of Stiffness, presentation to the MnDOT LWD/Intelligent Compaction workshop, 17th November 2007, Detroit Lakes Minnesota USA.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The use of surfacing service life as a parameter in pavement strengthening design G. Refsdal & R. Johansen The Norwegian Public Roads Administration, Eastern Region, Norway

G. Berntsen NCC Roads, Contractors, Oslo, Norway

ABSTRACT: With a good knowledge of the existing surfacing service life, it is possible to evaluate the effect of pavement strengthening. By comparing the surfacing service life before and after the pavement strengthening, the effect of the strengthening can be evaluated in a very precise manner against both technical and economical criteria. The paper describes the background for the change in procedure for assessing pavement strengthening requirements and the method for designing the strengthening. On the basis of this experience a new method for pavement strengthening was introduced in the 2005 revision of the Norwegian Materials and Pavement Design Manual. The need for strengthening is no longer established on the basis of measurements with FWD or other indirect methods, but only to the recorded service life of the surfacing. 1

INTRODUCTION

1.1 Historical views The Norwegian procedure for pavement strengthening design was until 2005 based on traditional approaches. These included material investigations for calculation of structural number as well as the determination of layer moduli based on deflection measurements. During the 70’ies and 80’ies the Dynaflect equipment was used on a large scale in Norway—with 18 units in use. Following the phasing out of the Dynaflect, the falling weight deflectometer was introduced in Norway during the late 80’ies and 90’ies, however in a limited number used mainly for research purposes and input to e.g. strengthening design. Norway never fully adopted the analytical approach for evaluation of strengthening requirements, however deflection data was considered a useful supplement for the designer. There has been scepticism in letting material parameters be the key indicator of the service life of a surfacing/pavement and funding to develop a large system. In 1994 the BUAB report (“Better Utilization of the Bearing Capacity of Roads”), which presented four years of research in the field of road bearing capacity, recommended the following major changes: – Lifting of all seasonal axle load restrictions to take place immediately based on analyses of the economic cost-benefit. – A change in the pavement strengthening procedure, with focus on the obtained surfacing service life as an alternative to an analytical approach. The proposed change in the system for pavement strengthening and rehabilitation required a longer period of performance data than what was available through the PMS in 1994. However, when the Norwegian pavement design standards were revised in 2005, a new system for pavement strengthening and rehabilitation was introduced. This system was based on information from 14 years of extensive monitoring of pavement performance on road network level. 819

1.2 Traditional pavement strengthening indicators The need for pavement strengthening or rehabilitation is commonly related to inadequate service levels for the road users in combination with excessive costs in maintaining the existing pavement structure. The need for pavement strengthening was for many years based on “engineering judgment”, later followed by the introduction of deflection measurements (with or without backcalculated moduli), and today there is a move towards an analytical approach, taking into use the best possible knowledge of: – Material characterization of the pavement layers. – Existing traffic loads and predicted traffic growth. – The climatic conditions. The analytical approaches have been greatly improved over the last 10–20 years, and many pavement strengthening design methods are today based on field measurements with FWD’s combined with the back calculation of layer moduli. 1.3 Analytical design methods and their shortcomings Among the existing design methods for evaluation of existing road pavement conditions are: – – – –

the structural number (index method) deflection measurements investigations using Dynamic Cone Penetrometer (DCP) analytical methods with back calculation of deflection measurements.

The different methods often give diverging outcomes and a calibration against in situ performance is necessary. Analytical methods may contribute in explaining short surfacing service lives; however the analytical methods require information about the pavement structure, such as: – – – –

Layer thicknesses. Strength properties (back calculated E-moduli or even tri-axial testing). Particle size distribution and moisture condition. Frost susceptibility, etc.

In Norway the subgrade conditions and roadside topography are very variable, thereby reducing the usefulness of information obtained through sampling and testing at economical frequencies along the road line. These are challenges that in practice render analytical methods less reliable than desired. 1.4 Surfacing service life versus pavement design life The surfacing service life is defined as the period of time from placing a wearing course until the surface condition is such that a new wearing course is required in order to meet established maintenance standards. The surfacing service life may in many cases be used as an indicator of success in the structural pavement design process, but does not normally feature as a parameter in the design procedures. In pavement design systems, emphasis has traditionally been placed on pavement design life. The pavement design life might typically be 20 or even 30 years for a flexible pavement, but the required resurfacing frequency during this period is usually poorly defined. At the end of the design life cycle there will in practice be no special procedure to indicate that this period has expired and there will be no assessment to say whether the pavement design was successful or not. An unsuccessful pavement design would simply have given a higher resurfacing frequency than the more successful pavement design, and systematical records to prove the success are normally lost or not gathered. The surfacing service life is a parameter closely linked to operational cost as it is a deciding factor in finding annual costs for the maintenance of the road. Extensive collection of 820

pavement performance data over many years has given new opportunities to obtain the surfacing service life. It is therefore tempting to utilize this information more extensively, also as a parameter that indicates bearing capacity among other defects that cause resurfacing to be required. However, such use of data will require a link between the expected and the observed surfacing service life. The observed surfacing service life is derived from the PMS. The expected surfacing service lives is found in accumulated data gathered in the National Road Data Bank over years of registering performance parameters at a large scale on the road network, see Table 1. All analytical/mechanistic design systems have to be calibrated against in-situ performance. Such systems therefore represent an indirect way of providing an answer to the question of the designer; what design is the most economical. On the contrary, the PMS gives us an answer directly from the performance record in the form of a real surfacing service life. The advantage of using the surfacing service life as a parameter for pavement strength is that: – It reflects performance, which is the main concern for the road user. – It provides a direct link to the economy of the road operation. 2

THE NORWEGIAN PAVEMENT MANAGEMENT SYSTEM

2.1 The Norwegian road network The Norwegian main national road network comprises approximately 26000 kilometers, of which 7000 kilometers are trunk roads and 250 kilometers are multilane motorways. In addition there are about 27000 kilometers of county roads and 37000 kilometers of municipal roads. All national roads are now paved, while 20% of the county roads still have gravel surfacing. The current average pavement surfacing age is 8,2 years for national roads and 9,9 years for county roads. 2.2 The project level Pavement Management System The Norwegian Pavement Management System is a Windows-based system that utilizes all available data from the National Road Data Bank and presents the data for the users in a format that makes it easy to make appropriate decisions in the maintenance of road surfacings. The PMS is used primarily by the regional pavement engineers to prepare plans and tender documents for resurfacing works at project level, but is also used at management level for planning works for periods of several years. The main focus is on making and adjusting plans for the next 3 years so that budgetary constraints are met. This tool helps the engineers monitor performance and to make the right decisions concerning location, timing and extent of future resurfacing works within their region. 2.3 Data collection Performance data for the road network will from 2009 be collected using a newly developed measuring system produced by ViaTech in Kongsberg, Norway (www.viatech.no), see Figure 1. There will be 13 measurement vehicles in operation. Each vehicle is equipped with a rotating class 3 laser scanner, mounted at the rear end of the vehicle at a height of 2,2 metres from the road surface. A combination of lasers provides the IRI-data. The equipment operates in such a manner that the surface is mapped electronically at full accuracy over a lane width of up to 4 metres and slightly beyond these boundaries at reduced accuracy. The data are continuously linked to the national road identification system. The measuring system produces: – Detailed rut depth data. – Detailed International Roughness Index (IRI) data. – Geometry, such as cross fall, cross section data, horizontal radius and longitudinal profile. 821

Figure 1.

From an annual meeting for measuring units (2007, comparison of results).

– Larger surfacing cracks. – Quality and position of road markings. In addition, a digital camera system (VidKon) captures photos of the road every 20 m and stores the images in a database for quick retrieval so that a record of the appearance of the road surface is kept for future use by whoever needs such information. Any site can be seen from both directions if desired. The photos are extensively used by maintenance engineers to check damages like potholes, cracking etc. The collected performance data are transferred from the computer to the National Road Data Bank. These data are imported into the PMS database. A simple screen gives the user an overview of the PMS sections, which varies in length from a few hundred meters to several kilometers. Specific road sections may be studied in detail, as the historical development of either rutting or roughness. A picture of the screen that presents data is shown in Figure 2 as an illustration (details in Norwegian). The data may also be presented as the detailed condition data like rutting, roughness and crossfall along the road at 20 m intervals (not shown here). Performance data for each section as shown in Figure 2 are presented as the 90%-ile values, i.e. 10% of the section is allowed to be in “substandard” condition. These graphically presented data are used together with photos and other information of the specific road section to produce plans for resurfacing within a region. This Pavement Management System has been implemented in all the five regions of the Norwegian Public Roads Administration. The utilization of road performance data is considered to be a great improvement for the regional pavement engineers, assisting them in the planning of resurfacing works, as well as for planning at management level. 2.3.1 Surfacing service life The presentation of performance development for rutting and roughness in Figure 2 allows the determination of the surfacing service life of the existing surfacing, i.e. the period from the laying of the surfacing until the threshold values for rutting or roughness have been reached. On the national road network rutting is in most cases the determining parameter for resurfacing. On the county road network roughness is more likely to be critical, however a combination of types of surface damage are likely to trigger resurfacing on these roads. 822

Figure 2. The historical and predicted development of rutting (top) and roughness (bottom) for a specific road section over the period 1993–2008. The horizontal straight lines are threshold values, dotted lines are extrapolations for establishing the expected surfacing service life.

3

PAVEMENT STRENGTHENING BASED ON SURFACING SERVICE LIFE

3.1 The need for pavement strengthening or rehabilitation Pavement strengthening or rehabilitation is considered when: – The surfacing service life is unreasonably low, or – The allowable axle load shall be increased or a very large increase of the traffic volume is expected. The aim of pavement strengthening is normally to achieve a surfacing service life as expected from a new road. Another case is upgrading of an existing road in order to increase the allowable axle loads or increased traffic volumes. The system gives an answer to whether there is a need for strengthening or not, as well as the required additional pavement strength. The strengthening method has to be addressed separately, and evaluated using traditional field measurements and sound engineering judgment. 3.2 Assessing the need for strengthening On road sections where the surfacing service life is unacceptable short, the strengthening need is established on the basis of the relationship between the actual (functional) surfacing service life and what is expected for the type of road and surfacing (Surfacing Life Factor SLF). This procedure requires that the expected surfacing service life can be derived. Table 1 shows the present expected surfacing service lives for new roads in Norway according to accumulated data over many years in the National Road Data bank. Local experience can call for the use of alternative estimates of “acceptable” surfacing lives, but this will be a modification according to sound engineering judgment. 823

The expected service lives, as presented in Table 1, may need revision due to gradual improvements in material technology and construction techniques, change in policy, for instance regarding the use of studded tires, change in threshold values for performance parameters (rutting and roughness), etc. The present Norwegian design catalogue for new roads does not take into consideration climatic variations, but a differentiation of expected surfacing service lives due to climatic conditions may be taken into account in later revisions. Definitions: SLF = the ratio between the functional (observed) surfacing service life and the expected surfacing service life. Functional surfacing service life = the actual surfacing service life that can be observed/ estimated, ending at the time one of the threshold performance parameters is reached Expected surfacing service life = the surfacing service life that should be expected on an adequately designed pavement SLF =

Functional surfacing service life Expected surfacing service life

Surfacings with Surfacing Life Factors above 0,7 The required strengthening is based on Table 2. When SLF > 0,7 the required strength improvement is expected to be taken care of by the ordinary resurfacing. Surfacings with Surfacing Life Factors 0,7–0,5 The required strengthening is based on Table 2. However, the required strengthening should be verified by material sampling and an evaluation of pavement deficiencies. Surfacings with Surfacing Life Factors below 0,5 A Surfacing Life Factor below 0,5 indicates a pavement structure with serious deficiencies in the pavement structure. Such a pavement is generally substandard in many aspects such as design strength, or the materials in one or more of the pavement layers may be of substandard quality. The cause of the problem will normally be identified through sampling and testing of pavement materials and an evaluation of pavement structure. In addition both deflection measurements and DCP/CBR testing may contribute to the evaluation of the pavement structure and in finding the appropriate method for strengthening. 3.3 Other defects than bearing capacity A short surfacing service life may have other causes than poor bearing capacity, and such conditions will have to be excluded in the evaluation process. These factors may include: − Problems related to the surfacing itself. − Frost heave problems. Deficiencies related to the bituminous surfacing itself should be detected during the construction quality control or the warranty period (normally 5 years in Norway). Also

Table 1. Expected surfacing service lives (years) for typical flexible surfacings in Norway, for various AADT values.

Surfacing type

<300

300– 1500

1500– 3000

3000– 5000

5000– 10000

10000– 15000

>15000

Stone mastic asphalt Asphalt concrete (type I) Asphalt concrete (type II) Asphalt concrete with soft binder

– – – 14

– – 13 12

– 13 12 10

– 11 – –

9 8 – –

7 6 – –

6 5 – –

824

Table 2. Strengthening needs related to Surfacing Life Factor (SLF). Required additional pavement structural index value (Fdiff)* for various traffic groups.*** Surfacing Life Factor (SLF)**

<0,5

0,5–1,0

1,0–2,0

2,0–3,5

f f f f

6 9 12 15

6 9 13 17

7 10 14 18

8 11 15 19

= 0,8 = 0,7 = 0,6 = 0,5

*A structural index of 3 is equivalent to 10 mm thick layer of asphalt concrete. A structural index of 1 is equivalent to 10 mm thick layer of sub-base. **The SLF is the ratio between the functional surfacing service life and the expected surfacing service life. ***Traffic groups of million 10 tonnes Equivalent Standard Axles.

earlier history of surfacing performance, which can be obtained from performance history (Figure 2), can clarify the causes of a short surfacing life. Premature resurfacing can also be a result of damage caused by frost heave, which will normally be identified and handled separately. These include surface cracks and an uneven road surface. Frost problems related to weakening of the base layer during thawing, and the presence of water susceptible materials, should however be handled as a pavement strength issue. 3.4 Pavement strengthening measures The system described here, based on the evaluation of the surfacing service life, is used for evaluation of the need for strengthening, i.e. − Whether there is a need for strengthening or not. − The degree of the required strengthening. While the need for—and the degree of—the required strengthening can be established through the Surfacing Life Factor (SLF), there are many options in the selection of strengthening method. If the pavement structure is too thin, adding strength at the top of the pavement may be a reasonable solution within certain limits. When there is a problem of material quality in the base layer, or even deeper in the structure, the most cost-effective solution may be to improve these substandard parts of the pavement, for instance by milling and stabilization. The appropriate type of strengthening is obtained by an investigation into the reason for the short surfacing service life. This may include the following methods: − − − −

Sampling and testing of materials in the pavement layers. DCP measurements. Deflection measurements. Georadar or other specialized methods for investigation.

3.5 Assessing the effect of pavement strengthening through the surfacing service life With a good knowledge of existing surfacing service life, it is possible to evaluate the effect of pavement strengthening that links the effect directly the maintenance economy. By comparing the surfacing service life before and after the pavement strengthening, the effect of the strengthening can be evaluated in a very precise manner against both technical and economical criteria. An example is shown in Figure 3. 825

Figure 3.

4

Increased surfacing service life reveals the effect of pavement strengthening.

USE OF THE PARAMETER SURFACING SERVICE LIFE FOR OTHER PURPOSES

4.1 Available information for many purposes Pavement engineers have commonly not had specific focus on systematical assessments of the achieved surfacing service lives. Only in recent years have systems been established to make it possible to collect, store and retrieve this information in a convenient manner. Neither has the potential for the possible use of this information always been very obvious. In chapter 3 the use of surfacing service life for evaluation of pavement strengthening needs is described. Two other areas of application are shortly described below, i.e. − Establishing a resurfacing strategy based on annual cost. − For assessments of the budget. 4.2 Annual costs—combining surface service life and the construction cost The knowledge of surfacing costs has considerable added value for the road maintenance management when it is combined with the knowledge of expected surfacing service lives of the different types of surfacing under a variety of conditions. This information puts us in position to identify the best choice of surfacing for a certain road section in a rational manner with a fairly good accuracy regarding total economy. Figure 4 gives an example of how this information is presented in the document Sufacing Strategy for NPRA, Eastern Region as “best surfacing choices” for the AADT group 1500–3000 vehicles per day. Each individual surfacing requires different types of preparatory work incorporated in the table. A ranking of best choice is presented according to annual surfacing costs. In many cases local conditions will influence the final selection of surfacing type, thereby leading to a choice that is not ranked as the most economical in the table. However, if the choice is very different from the most economical surfacing according to the table, the planner should be able to give rational reasons for the choice. 4.3 The use of surfacing service lives in budget assessment The resurfacing budget required to maintain the performance at a certain described level will depend on several factors: − Asphalt prices. − Variation in climate. 826

Rank no.

Asphalt surfacing type. (Norwegian standard code system)

Expected surfacing For the service Alt. levelling surfacing life course itself (years) A B

Annual cost (NOK/m2) Preparatory work Alt. spotwise Deep Alt. shallow level.-course milling milling C D E F G

Sum

1

Agb11 75 kg/m2

13,8

3,06

1,82

3,06

1,15

2,11

1,34

1,63

2,58

2

Agb16 100 kg/m2

17,0

3,39

1,57

2,64

0,99

1,81

1,15

1,40

2,22

4,95

3

Ma16 100 kg/m2

15,5

3,31

1,67

2,82

1,06

1,94

1,23

1,50

2,38

4,98

4

Ab11 75 kg/m2

15,0

3,32

1,71

2,88

1,08

1,98

1,26

1,53

2,43

5,03

5

Agb11 90 kg/m2

15,4

3,36

1,68

2,82

1,06

1,94

1,24

1,50

2,38

5,03

4,88

6

Ma11 75 kg/m2

12,3

3,06

1,99

3,34

1,25

2,30

1,46

1,78

2,82

5,05

7

Ma11 90 kg/m2

13,9

3,32

1,81

3,05

1,14

2,09

1,33

1,62

2,57

5,13

8

Ab11 90 kg/m2

16,6

3,68

1,59

2,67

1,00

1,84

1,17

1,42

2,26

5,26

9

Ab16 110 kg/m2

18,2

4,10

1,49

2,51

0,94

1,73

1,10

1,34

2,12

5,59

10

Ab11 45 kg/m2

13,3

3,33

1,87

3,15

1,18

2,17

1,38

1,67

2,66

5,99

11

Ab11 60 kg/m2

13,3

2,93

1,87

3,15

1,18

2,17

1,38

1,67

2,66

6,08

12

Agb11 60 kg/m2

12,1

2,74

2,01

3,39

1,27

2,33

1,48

1,80

2,86

6,13

13

Ma11 60 kg/m2

10,6

2,79

2,23

3,76

1,41

2,59

1,65

2,00

3,18

6,56

Figure 4.

Example of “best surfacing choice” for the AADT group 1500–3000 vpd.

Figure 5.

The development of asphalt surfacing service lives in Norway 1990–2005.

Planners sum

− Choice of technology and technology development. − Surfacing service life—and above all; change in surfacing service life. Prior to the introduction of the Pavement Management System in 1990, the knowledge of obtained surfacing lives was limited. The performance monitoring has exposed a steady increase in the surfacing service life from just above eight years in 1990 to approximately 14 years in 2005 as shown in Figure 5. This increase was both unexpected and remarkable, and explains why it has been possible to absorb the 40% reduced asphalt budgets during the same period, without a dramatic decline in performance. The present surfacing service life reflects the pavement technology as constructed in the early 90’ies and it is possible that future surfacing service life could still increase, unless offset by the effect of e.g. climate change. New technology is today applied in production of pavement materials and the positive effect of these methods and materials is not yet shown in the surfacing service life. The systematic pavement strengthening of road sections through the 90’ies, benefiting roads having a low surfacing service life, will undoubtedly also contribute to an overall increased surfacing service life. 827

5

CONCLUSIONS

A new approach for pavement strengthening has been introduced in the revised Norwegian Pavement Design Guidelines from 2005. This approach involves the functional (observed) surfacing service life as an input parameter for the need for—and design of— pavement strengthening and rehabilitation. The parameter functional surfacing service life has been used in various analyses by practitioners for years, but is now adopted in a rational manner in the pavement design system for pavement strengthening as expressed by the key parameter Service Life Factor, SLF. SLF is the ratio between functional surfacing service life and the expected surfacing service life for the current type of surfacing and traffic volumes. It is likely that Norway in the future will pursue further development of an analytical design method for the purpose of explaining pavement behavior or unexpectedly short surfacing service lives for specific road sections. However, such a system will be supplementary to the purely performance based system that relates to surfacing service life and thereby directly reflects operational pavement costs. Historical records of the surfacing service life can be utilized for the purpose of finding annual costs for resurfacing measurers. Thereby a reliable catalogue of the most rational choice of surfacing for various conditions can be established, as it has been done at the Norwegian Public Roads Administration, Eastern Region. Surfacing service life has important application in analyses of budget needs. REFERENCES Senstad, P. 1994. Better Utilization of the Bearing Capacity of the Road Network. Final Report. pp. 24–29. NRRL Publication No. 75, Norwegian Public Roads Administration (in Norwegian). Senstad, P. 1995. Better Utilization of the Bearing Capacity of Roads. pp. 11–13. Nordic Road & Transport Research, No 1. Refsdal, G., Senstad, P. and Sørlie, A. 2004. The lifting of all Seasonal Load Restrictions in Norway in 1995. Background, and Effects. TRB Meeting 2004. Gryteselv, D., Haugødegård, T. and Sund, E. 2001. The New Norwegian Pavement Management System. Fifth International Conference of Managing Pavements, Seattle, Washington.

828

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Going beyond elastic response while evaluating falling weight deflectometer data C.A. Lenngren Vectura Consulting, Borlänge, Sweden

ABSTRACT: Back calculated elastic moduli from falling weight deflectometer tests are used for determining stresses and strains in pavement structures. Linear elastic models are preferred by pavement engineers for their inherent simplicity. Non-elastic response is then considered as noise by the evaluator. The present paper presents examples from research projects and includes instrumented pavement sections, and a variety of pavement types. Part of the non-elastic deformation can be regarded as a “conditioning of test” phenomenon and some as plastic response, volumetric change and water being present in the material. By carefully analyzing repeated load drops and full time histories, it seems that non-elastic deformation can be utilized to detect proneness to early rut depth growth and other parameters related to pavement deterioration. When using full time histories and repeated drop cycles it is evident there is more signal and less noise in the data than previously thought. 1

INTRODUCTION

The Falling Weight Deflectometer (FWD) test is a proven method of assessing important pavement material properties. The backcalculation of elastic moduli from non-destructive tests is an important practice in determining stresses and strains in road structures. Rather straight-forward linear elastic models are often used on a regular basis by pavement engineers for their inherent simplicity and promptness. The strains also comply with the empiricalmechanistic methods used today. Response due to non-elastic properties is then usually considered as noise by the evaluator. As it seems, some of the non-elastic deformation occurring can be regarded as “conditioning of test” phenomena and other parts as plastic response, volumetric change and/or effects of water being present in the material. By carefully analyzing repeated load drops and full time history evaluation it seems that non-elastic deformation can indeed be assessed for an estimation of early rut depth growth and other interesting parameters related to pavement deterioration. Many engineers have developed a confidence in using FWD data and the results are used for future reconstruction and rehabilitation of the road. However, when using a common linear elastic model typically about 10–20% of the deflection basins are discarded for various reasons; often some of the results are just not very reasonable. Apart from measurement errors, the most common causes include a misjudged layer thickness error and/or limitations of the model to linear properties and the bonding between layers. In reality coping with less than perfect data is truly an engineering judgment task requiring lots of experience. Uncertainties are dealt with in either gathering more data, which can be expensive and not non-destructive, or by adding a safety factor which contradicts using limited resources in a sensible way. The present paper is a summary of several studies of problems encountered with backcalculation of deflection data and how it may be interpreted to good use. Often if encountered with a problem the evaluator would ask; “what is wrong with the data?” or “how to weed out abnormalities to get the true elastic response?” Well, with the improved computing power and better calibration of the machines, it seems that some of the idiosyncratic data is fully 829

explainable and could be used in an effective manner. It is the present author’s conclusion that much more information than deflections and elastic moduli are assessable in the test protocol. The present paper is intended for the pavement design engineer and students in highway engineering, but computer programmers may find it useful too for the further improvements of software. 2

A SHORT FWD HISTORY

Falling weights have been used to test soils in the field for a long time. One reason is the portability; a relatively small weight can produce a large load when hoisted and dropped from any given height. Originally FWDs were first used in Russia for pavement testing. There was a prototype made in France in the 1960’s. The first machines were thought of as being more economical than the large trucks that were used at the time to gather pavement deflection data. Entrepreneurial inventors developed the machines further in Denmark and Sweden in the late 1970’s and 1980’s. While most countries use FWDs on paved roads today, their first main task in Sweden was on gravel roads that were to be upgraded with a thin surface dressing. These early machines were equipped with two deflection sensors. Thus, some idea was grasped about the bearing capacity of the subgrade and the pavement separately. A segmented loading plate capable of adjusting to uneven gravel surfaces was then used for the first time. Another early use was assessing bearing capacity for overlay design purposes. With the introduction of the personal computer and backcalculation software it was possible to assess the strains needed for the mechanistic-empirical models that emerged at the time. Some countries use the FWD for network monitoring, but then usually some direct regression is used for the evaluation of pavement, subgrade or both. The more advanced possibilities to explore data are for research projects. For most road research projects in the world today, there are FWDs involved somehow. 3

HARDWARE CONSIDERATIONS

One great advantage using the FWD is that the test defines a standard by itself. It does a good job of mimicking the load of a unique truck axle traveling over the pavement at a constant speed, which is the custom speed on which further pavement overlay design is based. Provided the same type of machine is used the loading time and the shape of the loading curve is constant over time. Stresses and strains are close to those caused by actual traffic, which is not the case for most other non-destructive testing devices. Note that different brands of machines may differ quite remarkably though and it is difficult to compare results from different equipment directly. Just like a slow moving truck produces a different response than the one going at highway speeds down the freeway. The present author has previously studied the effect of different load pulses by deliberately altering the load mode by changing the buffer configuration on the same individual machine. Thick asphalt pavements are affected by this due to their visco-elastic properties. Cohesive soils may also show different stiffness by altering the rise time of the load pulse (Lenngren 1994). The pulse duration is quite important for various reasons. Shorter pulses are indeed reflecting faster moving traffic, but there are also some considerations about using a too short pulse: • Inertia comes into play that may be difficult to cope with due to unknown composition of the structure. • A fast load will shift the behavior of asphalt to a colder more elastic response, which may mask proneness to rutting. • Excess water present will hide soft layers. FWDs usually have a rise time of 10–25 milliseconds (ms). For pavement research it may be worthwhile to look at rise times up to 50 ms though. One concern is the work input from 830

100 90

Load Pulse Shapes

Short-Low

kN

80

Short-Medium

70

Short-High

60

Long-Low Long-Medium

50

Long-High

40 30 20 10 60

57

54

51

48

45

42

39

36

33

30

27

21

24

18

15

12

9

6

3

0

0 ms

Figure 1.

Different load pulses and load heights.

the drop. Most pavement engineers are familiar with potential energy, meaning that mass times g, times height gives a fixed input. Ep = m ∙ g ∙ h

(1)

Now an implication is that a short pulse would contain less energy if the maximum load is the same as a longer duration pulse. In Figure 1 six different time history drops are shown. The interesting fact about the plot is that two different load modes were used on the same spot. Each load mode was dropped from three different heights. The respective heights are being fixed on the machine with electro-mechanical switches, so they stay exactly the same. The shorter pulse has a rise time of about 17 ms and the longer one 25 ms. In the figure we see a top load of about 90 kN for the shorter and only 70 kN for the longer pulse. Incidentally, the medium short drop is about the same as the high long drop. The reason for this is that more energy or work is being squeezed into a shorter time span. So when comparing results from different pulses, this must be taken into consideration. With the same maximum load used for backcalculation, the longer pulse will affect a larger volume soil that may behave differently. At airports in particular, the short pulse is common as it reflects high speeds at take-off operations. It also yields a higher maximum load for the drop height. Mind though, that at large depths the load even from fast moving planes actually is not the fast. If the subgrade is of concern, maybe it is better to use the longer load pulse after all. As far as the configuration of the machine goes, the two mass machines do produce a pulse more closely to a haver-sine wave and thus a wheel load. For advanced evaluation the onemass machines may not be inferior in the analysis as long as one knows what the exact input is. For repeated work it is important to see to that rubber parts are not worn and that they are replaced by similar spare parts. 4

FWD EVALUATION TECHNIQUES

4.1 Linear elastic layer backcalculation software As mentioned above, the interpretation of data got a head start with the introduction of backcalculation software in the late 1980’s. It is outside the scope of the present paper to go through the development of these, but a few words are appropriate in this context. Generally, using the maximum load and maximum deflections actually results in a match between theoretical and measured basin differing less than one percent root mean square error per sensor. As long as the layer thickness is correct and that there are no large temperature gradients in the pavements one is doing just fine with this technique. One key issue is the fact that the 831

load is near those exerted by traffic. The use of assessing pavement thickness with Ground Penetrating Radar (GPR) has helped and simplified the evaluation tremendously. Other small improvements of the software include handling layer interfaces, which sometimes pose problems when assumed to have full friction. See also (Lenngren 2002). 4.2 Ways to handle non-linearity As mentioned above, one of the fortes with the FWD is the standardized load pulse, which is close to the traffic load. This is a way to ensure that whatever you measure is indeed close to working mode of the specimen; and that cannot be wrong. However, the field environment is not always cooperating on producing average conditions. 4.2.1 Asphalt concrete temperature The first culprit is the asphalt concrete temperature having a great influence on the elastic response. The load frequency is too, but as long we are using the same load pulse we are fine. The pavement temperature has to be assessed somehow and the results are adjusted after the backcalculation is done. Now, if the test was done during a day with varying temperatures on the same type of pavement, it is possible to derive some kind of graph for the specific pavement. (The general formulae used are actually quite generic and besides the property changes with age). Figure 2 shows a plot of modulus with temperature. There is a group of data readings in the range of 14 to 16°C that does not seem to fit as the modulus is lower then the trend line. Well, actually they do belong to stretch with polymer modified bitumen, so they should not be used for a conclusion of the other reading. In addition to illustrating how the temperature adjustment can be done, a graph like this could also reveal different mixes. 4.2.2 Stress sensitivity Rather early, different load levels were used to detect stress sensitivity in unbound layers. From tri-axial testing it is a well-known fact that the resilient modulus (Mr) is a function of the bulk stress (σ1 + σ2 + σ3). There are a number of more or less sophisticated ways of expressing this but one of the most commonly used is: Mr = k1 * (σ 1 + σ 2 + σ 3 )k2

(2)

Modulus MPa

100000

10000

1000 0

5

10

15

20

25

30

Temperature °C

Figure 2.

Pavement temperature graphed with asphalt modulus, note different mixes at 14–16°C.

832

The constants k1 and k2 can indeed be determined by the backcalculation program if two or more load levels are used. Further for cohesive soils the bulk stress is replaced by the deviator stress (σ1–σ3) instead. Actually, the program would know which relation to use as in the latter case the modulus is going down the higher the load is. This is very good information for the pavement design engineer. If the subgrade soil is cohesive the risk associated with overloaded trucks is certainly much higher than for the corresponding friction soil. The experience from using the stress sensitivity regression has not been as successful as for the backcalculation of layer moduli. In many situations no stress sensitivity is detected and the results are inconclusive, i.e. some basins exhibit it but nearby ones do not. The backcalculation software will display a coefficient of determination (r2) so that the integrity of the regression could be valued provided that three or more load levels are used. One observation is that starting with the highest load going down yield better r2 than increasing the load levels, which is common practice for the tri-axial testing. A viable reason for this is a better conditioning of the material with the higher loads first. The higher load does a better job than the lower one in honing the material to be more elastic if you like. (After all we are using an elastic model). If the load series repeats the regression usually gets better with the number of repetitions. It is common practice to use the last series for the elastic evaluation. In conjunction with a Heavy Vehicle Simulator (HVS) experiment it was found that well compacted areas exhibited relationships close to what you get from a tri-axial test, whereas poorly compacted areas did not. This may be useful for compaction control for instance. Figure 3 shows how the constant k2 changed after the area between sections 4 to 10 trafficked by the HVS thoroughly compacted it. The r2 and k2 can be used to evaluate proneness to type I rutting a.k.a. post compaction by traffic. It seems if r2 and k2 are above certain values the initial rutting is decreased quite substantially. The findings looked very interesting but the test area was unfortunately limited in the study. Further research could validate the finding (Lenngren & Hansson 2004). 4.3 Using repeated drop sequences As seen in the example above the noise you get in the evaluation can perhaps make sense if used diligently. Usually, when testing anything seat drops are used. Supposedly for FWDs, the seat drop will set the sensors to the pavement. However, there is also a conditioning of test going on, meaning that the material will deform to adjust to the specific load it was subjected to. In all materials there is always some kind of residual tension left from whatever previous load is was subjected to. It is like walking over a squeaky floor at night. No matter how careful you are, you will set off these residual tensions! One interesting thing about these residuals

0.5

k2 after HVS k2 before HVS

k2 value

0.4 0.3 0.2 0.1 0 0

2

4

6

8

10

12

Section

Figure 3.

Exponent k2 changed after being compacted by a wheel load over sections 4–10.

833

14

Figure 4. Software evaluation package helps to determine important parameters revealing non-elastic behavior.

is that they do steal energy from the FWD load. This means that the deformation goes down in the layers beneath. On the other hand, a loosely compacted layer will have room to deform so the total deformation will be greater. Two different processes that counteract each other and both of them are disturbing the elastic response. In order to check these effects the present author added an evaluation package to the backcalculation software. The idea is to plot the repeated loads and also to see if the regression of stress sensitivity changes. Figure 4 shows a panel from it. Back calculated data are shown and selected in the spreadsheet to the left. Moduli for a chosen layer are shown at the bottom in the bar graphs. In this case nine drops were used and five stations are shown, the first one corresponding to the selected area. The nine drop series contains a seating drop of approximately 21 kN, then follows 21, 39, 50, and 70 kN drops, which are repeated. The selected area in the spreadsheet is plotted to the right. The seat drop is shown as a red open circle. It is shown having a modulus of 97 MPa (scale is inverted). The second drop shows 105 MPa a significant rise. Obviously some compaction and conditioning occurred as the first load was dropped. The sixth drop, which is the third drop at this level, is producing a lower modulus of 103 MPa. The previous compaction was maybe disturbed by the higher load levels. Incidentally, the lowest load yields the highest modulus here; a higher proportion of the load may go somewhere else on this new road. Old roads are actually much more consistent than this, due to the compaction of traffic. Another interesting observation is that for most projects, the least variability is found for the 50 kN load. This is also true for very large data sets as was seen in an investigation of 834

Strategic Highway Research Program, Long Time Pavement Performance study (Schmalzer 2007). A plausible explanation may be that this load is closest to the stress situation caused by traffic. Note also the slight load shift for the 70 kN drops, i.e. a horizontal offset. This is a telltale sign of compaction exerted by the FWD as the shift is caused by a better support for the later drop. As is evident there are many factors to deal with in analyses like these. Research has been initiated to identify those parameters that will discern type I rutting and poor compaction in an efficient and appropriate way as it will be very good and useful information for the pavement evaluation. 5

TIME HISTORY EVALUATION

Time histories have been used to some extent in conjunction with research, but it is not a standard procedure when doing pavement analysis. Some researchers have gained experience in looking for useful information, (Hansson & Lenngren 2006). Load as in Figure 1 can be plotted with the displacement traces in the time domain of course. But it is also interesting to plot the load versus the displacements, the so called hysteresis curve. It will definitely reveal non-linear behavior. Figure 5 shows a screen dump from the evaluation software CLEVERCALC 4.0. Traces are plotted in the lower part over time and above the loaddisplacement curves are seen. The example is from an asphalt concrete pavement with good bearing capacity. Note that all curves are quite open, even the outer sensor to the left. This is due to damping in the soil. For a perfect linear elastic response only a straight line will be projected in the loaddisplacement diagram. Most pavements exhibit some damping and for asphalt there is also the visco-elastic response. A typical reaction from a 50 kN load on an intermediate road on cohesive soils is shown in Figure 6. Seven sensors at different offsets 0–120 cm are plotted. (The one at zero offset is denoted D0 and produces the largest curve to the right). Most of the hysteresis can be attributed to the damping of the soils here also. Figure 7 on the other hand shows an example where the subgrade is granular and the unbound layers are extremely well compacted. That could be seen for the leftmost sensor D120 that exhibits an almost elastic response.

Figure 5.

Software screen from time history evaluation tool.

835

Another more severe example is a saturated subgrade. Moving water is pushing outer sensors upwards, see Figure 8. If a linear-elastic backcalculation is done using maximum deflection values the subgrade would be considered rather stiff. For design purposes this would be disastrous. For all these examples the area within the closed loop represents the work lost in the drop. About the same losses can be expected for a rolling wheel. They will contribute to the rolling

60

50

Load [kN]

40 D0 D20 D30 D45 D60 D90 D120

30

20

10

0

–100

0

100

200

300

400

500

600

–10 Displacement [mu]

Figure 6.

Load-deflection diagram from an intermediate road.

60

50

40 D0 D20 D30 D45 D60 D90 D120

Load [kN]

30

20

10

0

–100

0

100

200

300

400

500

600

–10 Displacement [mu]

Figure 7. Load-deflection diagram from road with an almost perfect elastic subgrade. The open do curve is almost entirely due to visco-elastic behavior in the asphalt concrete layers.

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70 60 50 D0 D20 D30 D45 D60 D90 D120

Load [kN]

40 30 20 10 0

–500

500

1500

2500

3500

4500

5500

–10 Displacement [mu]

Figure 8.

Load-deflection diagram where water is pushing outer sensors back up.

resistance of vehicles and as you can see the variation is huge for different pavement types and situations. Generally, about a third of the rolling resistance is considered to be attributed to the pavement, but part of that in turn is coupled to friction, (Taylor et al. 2001). It is interesting to estimate what the work is in numbers. It is not trivial as the sampling is deteriorating with time so the tail end of the curve is somewhat uncertain. So with the reservation of not being very accurate the curves shown have been calculated to vary from about 2 Nm in Figure 5 up to 100 Nm for Figure 8. Figure 6 showing time histories from an intermediate two-lane road asphalt concrete pavement road yielded a hysteresis loss of approximately 8.35 Nm for the standard axle wheel load. This will be approximately 17 J per 10 ton axle, for the 60 ms duration. Figure 7 is the example from a road, where the damping is small and negligible in the unbound layers. At the time of the test the asphalt pavement temperature was around 40°C. The hysteresis loop work is here about 2.9 Nm, so it may be surmised that warm weather may add up to 3 Nm or so for asphalt pavement roads. Concrete roads often show very low work or about .5 Nm for the 50 kN load. If these numbers are assessed correctly they could be very useful input in Pavement Management Systems (PMS). Not only could CO2 emissions be assessed better, it is also an incentive to do better compaction work and use stiffer materials. 6

CONCLUSIONS

For many years much of the refinement made to pavement software evaluation tools was to achieve an improved signal to noise ratio for the elastic evaluation. Since the performance model and the inherent criteria are calibrated for a linear layer elastic response, this is not very surprising. However, when looking into details of stress sensitivity, time histories et cetera; a lot more information can be derived from FWD testing of pavements. For research a few software tools have emerged that may be useful for more common inspection and evaluation. However, some of the evaluation parameters have to be validated, before they are integrated in the software. An interesting side effect is that more sophisticated analysis demands a better calibration of sensors. Conversely, advanced evaluation will indeed reveal a poor calibration. 837

The new evaluation methods involving time histories and multi drop analysis bode well for: • • • • • •

Construction control Interactive design Assessment of post compaction of traffic Work hysteresis monitoring of pavements for PMS Better performance models for plastic deformation Other engineering tools useful for construction like presence of water

The past twenty years of development have been quite interesting to follow. The computer hardware has improved quite dramatically. It will be very interesting to see how the nondestructive evaluation techniques will evolve for the next two decades. REFERENCES Hansson, J. and Lenngren, C.A. 2006 “Using Deflection Energy Dissipation for Predicting Rutting” Proceedings, 10th international Conference on Asphalt Pavements, Quebec, Canada. On CD-ROM available from ISAP. Lenngren, C.A. 1994 Non-Destructive Testing Utilizing Controlled Variable Rise Time, Proceedings Fourth International Conference on Bearing Capacity of Roads and Airfields, Vol. 1, pp. 467–490, 1994. Lenngren, C.A. 2002 Backcalculation of Thin Air—A Way to Cope with Slipping and Sliding Layer Interfaces, Proceedings Six International Conference on Bearing Capacity of Roads, Railways and Airfields, Lisbon, Portugal A.A. Balkema Publishers. Vol. 1, pp. 203–212, 2002. Lenngren, C.A. and Hansson, J. 2004 “Comparing FWD Initial Tests with HVS Induced Initial and Long-Term Rutting”. Proceedings 2nd international Conference on Accelerated Pavement Testing, Minneapolis, MN USA. On CD-ROM. Schmalzer, P.N. 2007 “Deflection Data Averaging: Is it a good thing? FWD User Group Conference and Workshops. Des Moines IA, 29 September–2 October, 2007. Taylor, G., Marsh, P. and Oxelgren, E. 2001 Effect of Pavement Type on Fuel Consumption NRC Centre for Surface Transportation Technology. IRF World Congress, June 2001.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Pavement contribution to truck rolling resistance C.A. Lenngren Vectura Consulting, Borlänge, Sweden

ABSTRACT: The influence of pavement type and condition on truck rolling resistance has been examined in a number of studies. These studies show that the rolling resistance does vary, but it is difficult to assess exactly how much can be attributed to the pavement type. By plotting load and deformation from a falling weight deflectometer test a hysteresis curve is obtained. Moreover, the energy losses can be estimated from such a plot. In the present study it was found that the visco-elastic properties of the asphalt had a great influence on the curve. Water present and the subgrade material type also affected the shape of the curve; so, the various properties could be determined. At one site, asphalt concrete and Portland cement concrete pavements were compared. The difference in energy losses between the two pavement types is significant, something which may affect life cycle cost analysis. 1

INTRODUCTION

Vehicle costs are important for the optimization of transportation. The well-known Highway Design Manual (HDM) series of programs issued by the World Bank illustrates the fact by having a very detailed input concerning the vehicle fleet. Road roughness affects among other things, the vehicle speed, rider comfort, vehicle wear and accidents. All these can be attributed to costs. Over the years the magnitude of the vehicle operating costs has fluctuated with the fuel prices. When the price is going up efforts are made to mitigate fuel consumption, and when the price is stabilized for some time more powerful engines are marketed. A more recent view of the costs comprises carbon dioxide emissions, which were previously ignored. If these are accounted for and with increasing fuel costs it seems like vehicle operating costs are more important than ever. Portland cement concrete (PCC) pavements incur higher investments costs then asphalt concrete (AC) ones. The higher cost is balanced by lower maintenance costs and a longer technical life. Sometimes it is also claimed that the truck rolling resistance is lower on concrete pavements and thus carbon dioxide emissions would be reduced too. An important incentive as the world continues to grow and emissions must be kept at bay. Fuel consumption is depending on acceleration, wind resistance, and rolling resistance. The wind resistance is a function of the vehicle and wind speed. The rolling resistance is depending on the tire friction, internal friction for engine and drive train, plus a component of deforming the surface. The energy is lost as heat as can be seen shortly after a rain shower when pavements are first dry in the wheel tracks. Anyway, of the losses attributed to rolling resistance the most part is from the tire interacting with the pavement. Significant research work has been sponsored by the tire industry. Obviously, at times friction is needed to control the vehicle, but coarse macro-texture or tire treads usually demands more fuel. In Canada, a large study was done on fuel consumption on different pavement surfaces (Taylor et al. 2001). One conclusion was that pavement temperature influenced the outcome significantly. Note that ambient temperature also affects fuel consumption but in an opposite manner. Also, during the cold season the fuel mix is adjusted in most markets to a higher percentage of alcohol, which results in a higher consumption.

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The pavement surface condition does affect the fuel consumption also. At a full-scale pavement test facility in Nevada automated trucks on WesTrack demanded 4% less fuel after the track was resurfaced (Mitchell 2000). The influence of the pavement profile including joints on rolling resistance is rather easy to determine with a truck suspension model, but the losses within the pavement layers and soil are much more difficult to assess. 1.1 The falling weight deflectometer The falling weight deflectometer (FWD) is a device used by pavement engineers to access bearing capacity on roads. It is used for estimating salvage values, a decision tool for future maintenance, or overlay work. Originally FWDs were first used on roads in Russia, but entrepreneurial inventors developed them further in Denmark and Sweden in the 1980’s. While most countries use them on paved roads, their first main usage in Sweden was on gravel roads that were to be upgraded with a thin surface dressing. A loading plate capable of adjusting to uneven gravel surfaces was then used for the first time. Over the years the techniques of evaluation of deflection data have evolved considerably due to the rise in computing power. For overlay design purposes the method of backcalculating elastic moduli has proven to minimize mistakes with under-designed structures, but more importantly it has helped saving large amounts of money by suppressing over-design. As function driven construction parameters are becoming more common, the FWD also is an excellent tool for assessing road capital value after any given time, making long term contracts and warranties easier to accomplish. When conducting a test a weight is dropped on a rubber coated loading plate so that the magnitude and duration of the loading is similar to that of a passing truck tire. Sensors resting on the ground register the bending of the surface as deflections, which lasts about 25 to 50 milliseconds depending on the machine. Simultaneously, a load cell registers the rise and fall of the load pulse. A hole in the loading plate allows for the center deflection, which is the largest, to be recorded. Other sensors are spaced at some distance away from the loading plate. The farthest is usually 120 to 240 cm away from the center.

Deflection Sensors Loading plate Figure 1.

The FWD is usually towed with data gathering equipment in the vehicle.

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1.2 Different approaches The load and deflection data can be used for different purposes. Deflection itself is a way of judging bearing capacity and historically there have been many devices measuring the road network for that purpose. The next level of complexity is using data for an elastic model so that strains related to a performance model can be assessed. In this case only the maximum deflections for a given load need to be used. The method works surprisingly well if the performance model is properly calibrated. The load is standardized to mimic a truck load, which is a good reason for getting consistent results. This is the most common use for FWD data today. To get further with the data more elaborate testing can be done. It is common to use many load levels for instance, so that stress sensitivity can be tested, (Lenngren & Hansson 2004). Tests can also be repeated a number of times to discern elastic from non-elastic behavior. The pulse length and shape can be altered to check dynamic response, (Lenngren 1994). Finally, be tracing the load and deflections over time it is also possible to do visco-elastic analysis of asphalt concrete and damping of unbound materials and soils, (Magnuson et al. 1991). 2

DYNAMIC TESTING OF PAVEMENTS

In the mid 1990’s a large correlation study was carried out in Sweden regarding a highspeed Road Deflection Tester, RDT (Andrén 1999). Well over 100 pavement sections were tested and compared with FWD data. Time histories were sampled so that the effects of truck speed could be assessed. At a dual carriageway test site one direction was constructed as an asphalt concrete pavement and the other direction was a PCC pavement. At the time it was considered interesting to compare the two pavement types as the subgrade, traffic and environment were practically the same. Both sections turned out to have excellent bearing capacity, but the PCC was as expected, much stiffer and did not exhibit temperature related behavior. The RDT response did not vary significantly with speed either on the PCC sections. In the following analysis the load-deflection graphs showed less area inside the curve for the PCC plots. The size of the area reflects the energy losses, which however at the time of the study, was of no or little concern. At a later stage, when the alleged more energy efficient behavior of concrete was claimed by the cement industry the present author came to think of this test. Free from difficult fuel measurements or hard to do repeated runs with a truck, it seemed ideal to investigate the pavement contribution to the rolling resistance. A quick check of the historic data showed that there really were too few tests and that the sampling rate was barely adequate for this purpose. It was then decided to do a larger study with more modern equipment. 2.1 Field test in August 2008 A suitable field site was found on European highway 4 about 40 km north of Uppsala, Sweden. The road, a four lane freeway had been in use for about two years on the PCC and one year on the AC pavement part. In town Björklinge, the road pavement type changes from PCC to AC, with only a slight drop in average daily traffic at the interchange. Winters are cold and summers are moderate here; most precipitation occurs in July. Incidentally, latitude 60°N went right through the test area. The subgrade consisted mostly of glacial till at the test sections, even though the landscape is shifting from old seabed, flat farmland to undulating forest in the area, see Figures 2 and 3. The testing occurred at the evening on 2 September, 2008. This was planned so there would be little bending in the concrete slabs due to temperature gradients. The weather cooperated as most of the day had been overcast with some light rain occurring now and then. The air temperature kept constant at 16°C and the AC pavement temperature was recorded 18°C at two different depths. Thus, no gradients were expected in the pavement. From an evaluation standpoint this was most fortunate as the layers could be treated as homogenous. Another bonus was the fact that the temperature was close to the annual average for the AC pavement. 841

Figure 2.

The FWD at the PCC test site on highway 4.

Figure 3.

The AC test site on highway 4 and surroundings.

Due to traffic management control, all testing was done in the right wheel track in the northbound right lane. A seating load of 50 kN was used, then three load levels of 36, 51 and 65 kN that were repeated twice for a total of 10 drops per station. Twenty-eight stations were sampled each on the PCC and AC sections, respectively. 2.2 Results of stiffness The various layers were backcalculated for stiffness. The PCC stiffness was assumed to be 50 GPa as it otherwise would be difficult to assess the rather thin asphalt bound base. A fourlayer system was used for the PCC model, and for the AC only three layers were used. The objective with the backcalculation was not to pin down the numbers exactly, but more to see if the test was sound, and if the environmental conditions were similar. As could be seen in the tables the subgrade stiffness was almost the same for the two sites. The unbound 842

Table 2. Backcalculated average E-moduli for the AC pavement.

Table 1. Backcalculated average E-moduli for the PCC pavement. Thickness

Modulus

Layer

cm

MPa

PCC

20

Asphalt base Unbound layers Subgrade

50000 (Fixed) 10 10000 78 180 Semi-infinite 370

Thickness

Modulus

Layer

cm

MPa

Asphalt layers Unbound layers Subgrade

17 108 Semi-infinite

12200 240 375

100 90

Load Pulse Shapes

Short-Low

kN

80

Short-Medium

70

Short-High

60

Long-Low Long-Medium

50

Long-High

40 30 20 10 60

57

54

51

48

45

42

39

36

33

30

27

24

21

18

15

9

12

6

3

0

0 ms

Figure 4.

Typical time history plots showing three load levels and two different load modes.

layer modulus was backcalculated higher for the AC sections; but the stress level is also a little higher so that is to be expected if the same material is used. Over all the bearing capacity is very good for both pavement types. 2.3 Time histories Time histories have been used to some extent in conjunction with research, but it is not a standard procedure when doing pavement analysis. Some researchers have gained experience in looking for useful information, (Hansson & Lenngren 2006). The standard plot is showing the traces in the time domain, which is shown in Figure 4 for some different loads. As a standard procedure the load pulse is not altered for a single test, only the magnitude of the load is. Thus, the bulk or deviator stress influence on the modulus can be established. By plotting the load and the deformation a hysteresis curve is formed. For a perfect linear elastic response only a straight line will be projected. For most pavements there will be some damping by the materials and for asphalt there is also a visco-elastic response. A typical reaction from a 50 kN load on an intermediate road on cohesive soils is shown in Figure 5. Seven sensors at different offsets 0–120 cm are plotted. Most of the hysteresis seen can be attributed to the damping of the soils. Figure 6 on the other hand shows an example where the subgrade is granular and the unbound layers are extremely well compacted. Note the curve to the left (sensor D120) which exhibits an almost elastic response. 2.4 Energy loss estimation, a first attempt The exact loss of energy to the pavement system is difficult to access by these measurements. First, there is a rubber plate between the load cell and the pavement that may affect the results. 843

60

50

Load [kN]

40 D0 D20 D30 D45 D60 D90 D120

30

20

10

0 -100

0

100

200

300

400

500

600

-10

Displacement [mu]

Figure 5.

Load-deflection diagram from an intermediate road. 60

50

Load [kN]

40 D0 D20 D30 D45 D60 D90 D120

30

20

10

0 -50

0

50

100

150

200

250

-10

Displacement [mu]

Figure 6.

Load-deflection diagram showing visco-elastic influence and little damping.

The machine is calibrated with this in mind, but nevertheless it is an uncertainty. Further, the sampling deteriorates with time, so the tail end of the curve has to be managed somehow. During the test procedure, there is slight shift of the load to the support legs that may also influence the results. In the present paper some decisions had to be made about treating the data. They may not be the best way to reflect absolute numbers and they are not validated through experimental setups. However, they represent a first trial. Further discussion of how to best analyze the data from research and instrument manufacturers is appreciated. A time history evaluation program was written to manage the data, try various different ways of handling the tail data, present the material, and export to spreadsheet programs. As the data were sampled at 100 ns rate the difference in deformation for each step was small, the area under the curve was estimated by adding the product of load and delta-deformation over a given time span. As the rise time of the machine used is approximately 25 ms, about 50 ms is a good value to start with for a time window. On a road surface there is always some noise going on mostly due to passing traffic. Therefore it is difficult to define the start of a load by just reading the load cell value as it is fluctuating. Instead the curve is defined in time by the instant where the load reaches 844

5% of the peak load. Then it is up to the analyst to sample from that point or some other preset value. The peak load is depending somewhat to the stiffness of the specimen, so it will in turn affect the start point. However, at this end of the curve it is not that important as any accumulated area is small. It was noticed at the present site that the sampling offset varied a few milliseconds for the reason just mentioned. Handling the tail end is more difficult. First of all, there is a drift in the sensor output. The time it takes for the displacement sensor to reach zero varies depending on the specimen. There is a small shift of the dead weight from the support legs to the loading plate et cetera. For the present case it seemed like the time for the load or any displacement sensor to reach zero varied too much. The sampling window was then kept constant to 60 ms from the start time, approximately 10 ms before the 5% maximum load was reached. A Simpson’s rule integration was also tried on these curves in addition to the step approximation. Generally, it yielded a 2% smaller surface as the slope on average for the deflections are in that range, so this was to be expected. However, for some of the lower loads, it seemed as the simple step accumulation was less affected by the tail end effects. In the following the step approximation is used. 3

RESULTS

Figure 5 shows time histories from an intermediate two-lane road AC pavement road. It yielded a hysteresis loss of approximately 8.35 nm for the standard axle wheel load. This will be approximately 17 J per 10 ton axle, for the 60 ms duration. This corresponds to 280 Watt at continuous operations. If 100 kW is needed for coasting a 40 ton vehicle, a little bit more than one percent or 1 kW can be attributed to the rolling resistance on this type of road, (Taylor et al. 2001). Four times 280 Watt is just about 1 kW. Bear in mind though, there are some uncertainties about these values, but it seems that they are fairly close to the experimental data. Figure 6 is an example from a road, where the damping is small in the unbound layers, but the asphalt pavement temperature is around 40°C. The work is here about 2.9 nm, so it may be surmised that warm weather may add up to 3 nm or so for asphalt pavement roads. So how does this compare to field test in the present study? Figure 7 shows the PCC response for one of the 50 kN drops being near the average work area of 0.05 nm. It is drawn to the same scale as Figure 8 and obviously the stiffness is indeed high as the maximum displacement is a mere fifth of a millimeter. The response is not entirely elastic; the slab is after all resting on a 10 cm thick asphalt layer. Nevertheless, little hysteresis work is excited and thus the pavement response contribution to rolling resistance ought to be just about as low as it can be. Figure 8 shows a near average 50 kN drop for the asphalt pavement. It too displays a relatively small work area, even though it is four times greater than for the PCC example.

60

50

Load [kN]

40 D0 D20 D30 D45 D60 D90 D120

30

20

10

0 -50

50

150

250

350

-10

Displacement [mu]

Figure 7.

PCC load displacement diagram; D0 area is 0.423 nm.

845

450

The difference is significant. The relative difference on the total rolling resistance is of course smaller as this represents only the pavement contribution. It is obvious that the asphalt road is much better than the intermediate example seen in Figure 5 with a value of about 1 nm. The concrete road hysteresis is still even better at 0.5 nm. It shows that there is indeed a lot of potential to save fuel by choosing a higher quality pavement. Figure 9 shows the hysteresis work for two 10-drop sequences for one station at each site. Drops 1, 3, 6 and 9 are corresponding to the standard 100 kN axle load, hence with a FWD load of 50 kN. Noteworthy observations in Figure 9 are that the hysteresis is consistently descending with the drop number. It has to do with the conditioning of the test and some small compaction effort being achieved. The load to work data relationship is not linear as much more volume material is affected by the larger loads; inherently much more unbound material is affected also.

60

50

Load [kN]

40 D0 D20 D30 D45 D60 D90 D120

30

20

10

0 -50

50

150

250

350

450

-10

Displacement [mu]

Figure 8.

AC pavement load-displacement diagram; D0 area is 2.2 nm.

4500 4000 3500 3000 2500

mJ

AC PCC

2000 1500 1000 500 0 1

2

3

4

5

6

7

Drop #

Figure 9.

Approximate hysteresis work for the drop sequences.

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8

9

10

4

CONCLUSIONS

Truck rolling resistance is affected by pavement hysteresis work. An estimate from drive tests indicates that about a third of the rolling resistance can be attributed to the pavement, maybe much more on smaller roads. For AC pavements higher values can be expected at hot weather and lower ones at cold temperatures. Truck fuel consumption is also depending on the temperature, but usually more fuel is needed at lower temperatures for other purposes. So this is why it is difficult to discern differences through drive tests. Further, surface friction, joints and roughness all affect the drive test results as well. A thorough analysis of FWD time history data can contribute to the understanding of pavement hysteresis and how much it contributes to rolling resistance. In the present test the PCC pavement exhibited about four times lower work loss as AC pavements at the mean annual average temperature. Other tests show that thick asphalt pavements have high hysteresis at hot temperatures. By theory they should also be less sensitive at lower temperatures. More testing could confirm this hypothesis. For thin pavements quite large losses occur in the soil and unbound materials. Poorly compacted materials mean large losses. Other, highly compacted friction material exhibited an almost linear elastic response and thus very losses were kept low. Thus, extra efforts like extended compaction during the construction of roads could be worthwhile if these measures are included in life cycle cost analyses. The pavement does contribute significantly to truck rolling resistance and this should be factored in when choosing pavement type. The FWD can be used for environmentally proofing selected highways. The FWD seems to be viable for this purpose. However, there are a few uncertainties of how to treat the tail end of the time history curve. Some studies need to be done on calibration and the test method. ACKNOWLEDGEMENT The author wants to express his appreciation to Christer Hagert at the National Swedish Road Administration. In very short notice the FWD test was sponsored in time for the paper deadline. REFERENCES Andrén, P. 1999 High-speed rolling deflectometer data evaluation, Nondestructive Evaluation of Ageing Aircraft, Airports, and Aerospace Hardware III. Proceedings of SPIE. Ajit K. Mal Editor Volume 3586, pp. 137–147. Hansson J. and Lenngren, C.A. 2006 “Using Deflection Energy Dissipation for Predicting Rutting” Proceedings, 10th international Conference on Asphalt Pavements, Quebec, Canada. On CD-ROM available from ISAP. HDM-4 http://www.worldbank.org/html/fpd/transport/roads/rd_tools/hdm4.htm Lenngren C.A. 1994 Non-Destructive Testing Utilizing Controlled Variable Rise Time, Proceedings Fourth International Conference on Bearing Capacity of Roads and Airfields, Vol. 1, pp. 467–490. Lenngren, C.A. and Hansson J. 2004 Comparing FWD Initial Tests with HVS Induced Initial and Long-Term Rutting. Proceedings 2nd international Conference on Accelerated Pavement Testing, Minneapolis, MN USA. On CD-ROM. Magnuson, A.H., Lytton, R.L. and Briggs, R.C. 1991 Comparison of computer predictions and field data for dynamic analysis of falling weight deflectometer data Transportation Research Record 1293, Backcalculation of Pavement. Washington D.C. Mitchell Terry. 2000 WesTrack Track Roughness, Fuel Consumption, and Maintenance Costs TechBrief, USDOT, Federal Highway Administration, January 2000. Taylor, G. Marsh, P. and Oxelgren, E. 2001 Effect of Pavement Type on Fuel Consumption NRC Centre for Surface Transportation Technology. IRF World Congress, June 2001.

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Structural assessment of the English strategic road network— latest developments B. Ferne Transport Research Laboratory, Crowthorne, UK

R. Sinhal & R. Fairclough Highways Agency, UK

ABSTRACT: Over a number of years the UK Highways Agency has developed ever more sophisticated methods for assessing the condition of its strategic road network and selecting the most economic maintenance treatments based on a continuous value management process with an adaptable multi criteria decision tool to provide the essential guidance. The paper describes this approach, in particular the comprehensive range of regular surveys at traffic speed of functional and structural condition at network level and the slower speed tools for the more detailed project level investigations. The consequent rigorous assessment of all proposed maintenance schemes, using the condition information as input to the multi criteria decision tool, has demonstrably achieved a consistently high technical quality. Established standards are applied more consistently and the latest research findings are considered positively to achieve quick wins. 1

INTRODUCTION

The UK Highways Agency is responsible for the operation and stewardship of the English strategic road network on behalf of the Secretary of State for Transport. Primary functions are to manage traffic, tackle congestion, provide information to road users and improve safety and journey time reliability, whilst respecting and minimising the adverse impact on the environment. The strategic road network comprises over 7,200 km (4,500 miles) of road with around 40,000 km of lanes ranging from motorways to single carriageway trunk roads. This infrastructure asset is currently valued at over £81 billion ($120 billion) and carries a third of all road traffic in England and two thirds of heavy freight traffic. The prime objective of the Agency is to deliver a high quality service to all their customers by: • • • •

reducing congestion and improving reliability, improving road safety, respecting the environment, seeking and responding to feedback from their customers.

However to achieve these aims involves maintaining the condition of the network to keep it safe and available for use and this constitutes a very significant proportion of the Agency’s budget of over £800 m ($1200 M) per year. The overall aim is to maintain the network at minimum whole life cost, ensuring the right works are undertaken at the right time in the right place. 2

CONDITION ASSESSMENT

In order to evaluate when, where and what maintenance is needed on a road network it is essential to have regular and reliable measures of the condition of the pavement in terms of its functional surface condition as well as its structural condition. Additionally, what could 849

be considered part of its functionality is the safety condition of the surface. The current techniques required for pavement assessment on the UK strategic road network are comprehensively described in HD 29 of the UK Design Manual for Road and Bridges (Highways Agency et al., 2008). These methods cover measurement of the construction and condition of different types of pavements, except skidding resistance which is covered in HD 28 (Highways Agency, 2004). 1.1 Functional condition—current techniques Following HA-funded research and development by TRL of a test vehicle, HARRIS (Highways Agency Road Research Information System), as shown in Figure 1 and as described by Ferne et al., (2003), the Highways Agency has, since 2000, let a commercial contract, TRACS (TRAffic-speed Condition Surveys). This contract provides surveys of the surface condition of the core road network including the measurement of transverse and longitudinal profile, texture profile, road geometry and cracking, as described by Christie et al., (2000). In addition the vital location referencing information is collected by inertial-supplemented high quality GPS. This contract now covers around 40,000 lane km every year with some parts covered every six months. With such large quantities of condition information being collected every year it is vital that these data are robust and reliable. Therefore, the UK HA have commissioned the TRL to provide a quality assurance system for such surveys which includes comprehensive accreditation of the survey vehicles and random checks on the data quality. A similar approach has been applied to the similar SCANNER contract which covers the English local roads, as illustrated in Figure 2 and as described by Thomas et al., (2007).

Figure 1. The UK Highways Agency Road Research Information System (HARRIS).

Figure 3.

Figure 2. SCANNER survey vehicles taking part in accreditation trials at TRL.

Latest TRL survey vehicle, HARRIS2.

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1.2 Functional condition—latest developments TRL have continued to develop and assess the latest technology for such surveys together with major improvements in the interpretation of such data. The latest version of HARRIS, see Figure 3, provides extremely detailed three dimensional plots together with high resolution colour images of the road surface, which can for example be used in the identification of defects in concrete pavement surfaces, as shown in Figure 4, or edge deterioration. 1.3 Structural condition—current techniques To minimize the cost of maintaining a pavement we not only need to know about the safety and functional condition of the pavement but, of equal importance, the structural condition. The assessment of structural condition generally involves the assessment of condition in-depth, either indirectly by measuring its response under load, i.e. deflection measurement, or more directly by measuring material type, composition, thickness and condition (such as cracking, stripping or delamination). For many years in the UK we have been using the slow speed UK Deflectograph, shown in Figure 5, to measure pavement deflection response supplemented by the Falling Weight Deflectometer when more detailed investigations are required. Descriptions of the equipment and their application are given in HD 29 (Highways Agency et al., 2008). The Deflectograph is used to assess the structural condition of flexible pavements. It works on the principle that as a loaded wheel passes over the pavement, the pavement deflects and the magnitude of the deflection is related to the strength of the pavement layers and subgrade. The survey speed is slow (2.5 km/h) and consequently Deflectograph surveys cause considerable disruption, particularly on heavily trafficked roads. On the English strategic network this type of survey is no longer carried out at network level and is only used in support of individual maintenance schemes. As with TRACS, the UK HA is keen that these deflection surveys provide reliable data so provides well defined quality operating procedures and the equipment is annually accredited by testing at TRL, see Figures 5 and 6. The 2007 annual report for the FWD trials has been published by TRL as PPR261 (Nell and Langdale, 2008).

Figure 4.

Example of combining 3D view of road surface with road surface image.

Figure 5. UK deflectographs attending annual accreditation trials at TRL.

Figure 6. Falling Weight Deflectometers attending annual accreditation trial at TRL.

851

The assessment procedure used depends on the type of pavement and its mode of deterioration. Some thick, well constructed flexible pavements with asphalt base have been found not to deteriorate in the conventional way and with timely attention to surface defects can have a long but indeterminate life. These potentially long-life pavements are identified with deflection and thickness criteria. The structural condition of other flexible pavements is assessed in terms of residual life using a long-established Deflection Design Method based on deflection and traffic loading, as summarized in HD 30 (Highways Agency et al., 2008). Any interpretation of deflection response normally also requires information on the construction materials and thicknesses of the layers of a pavement. Although this can be provided from cores taken from the pavement, this is slow, disruptive and only provides limited samples. TRL has carried out extensive assessments of the capability of Ground Penetrating Radar to provide such information at traffic speed for the UK HA, as described in HD 29 (Highways Agency et al., 2008) and is currently working to provide the quality assurance for such surveys that will ensure that the UK Highways Agency can confidently commission such surveys and obtain robust reliable data to store in their Pavement Management System, as described by Lagarde-Forest et al., (2008). 1.4 Structural condition—latest developments With the current high levels of traffic congestion, the UK HA have been considering the options for measuring deflection response at traffic-speed. Consequently TRL are currently evaluating and developing for routine use, on behalf of the UK Highways Agency, a Danishbuilt Traffic Speed Deflectometer, see Figure 7. The device can measure the deflection response of a pavement at up to 80 km/h, as reported by Ferne et al., (2009) in a companion paper to this conference. As a first stage, the results are being related to the current UK Deflectograph interpretation method which provides an indication of whether the pavement is likely or not to be a long-life pavement and to provide an estimate of the residual structural life and strengthening requirements for the latter pavement type. In due course we expect to develop a more fundamental interpretation of the response of this type of device. The deflection response of a flexible pavement is always dependent on the temperature of the bituminous materials. A comprehensive methodology for correcting deflection measurements back to standard conditions has been developed for the slow-speed Deflectograph results which take into account the state of the bituminous materials in terms of age and condition as well as the pavement temperature, measured by inserting a probe into the pavement material, as more fully described in HD 29 (Highways Agency, 2008). This need for temperature measurement and correction is equally applicable to the measurements from the new Traffic Speed Deflectometer. However the physical contact method of temperature measurements is clearly impractical for a traffic-speed device and TRL has therefore developed a method of predicting in-depth temperatures from surface temperature measurements. The latter can easily be obtained during traffic-speed surveys using infra-red sensors. The method is based on the BELLS equation (Lukanen et al., 2000) and adapted to UK conditions.

Figure 7. UK highways agency Traffic Speed Deflectometer.

852

100 mm Measured Temp. [deg C]

40 35 X=Y 30 25 20 15 10 5 0 0

Figure 8.

5

10

15 20 25 30 100 mm Predicted Temp. [deg C]

35

40

Actual temperatures at 100 mm against predicted temperatures.

The method normally requires an estimate of the air temperature for the previous day but recent work has shown that for UK sites the accuracy of the method is only slightly reduced by considering the air temperature at the time of the survey, which is generally a much easier parameter to collect. This technique of predicting in-depth temperatures is also being considered for use with the current slow-speed deflection survey techniques such as the Deflectograph and FWD in that it should enable faster and safer surveys with less exposure of the operators to traffic hazards when leaving the survey vehicle to take in-depth temperature measurements. An example of measured vs. predicted temperatures at 100 mm depth on a range of UK sites is shown in Figure 8. 2

MAINTENANCE MANAGEMENT

A number of UK studies, developing the concepts of long life pavements (Nunn and Ferne, 2001), have shown that in the vast majority of cases on the English strategic road network the deterioration mechanisms encountered concern defects originating and propagating from the surface of the pavement downwards. This has lead to the HA developing a more appropriate and reliable pavement assessment regime by always first considering surface condition before structural condition. This new approach integrates existing procedures for assessing surface and structural maintenance and assumes that no maintenance of any kind is required unless there is evidence of wear on the road surface. Much more reliance is placed on the results of surface condition surveys that are now mostly carried out at traffic speed with little traffic disruption, as discussed earlier in Section 2. A simple overview of the overall selection and design procedures is shown in Figure 9. Further details are given in HD 30 (Highways Agency, 2008). This approach also broadly coincided with the introduction of a Road Users’ Charter and the coincident move by the Highways Agency to be a service based organisation, there has therefore been a change of emphasis on the determinants for maintenance intervention. This recognizes that the road user is concerned mainly with the surface condition of the road. Currently there are two levels of pavement condition survey: • Network level, • Scheme or Project level. 2.1 Network level surveys The network level machine surveys are all carried out at or near traffic speed. Two types of equipment are used, TRACS and SCRIM. A commercial TRACS survey is undertaken at 853

Figure 9.

Simple overview of maintenance assessment, selection and design.

least annually on the majority of the strategic network. It provides the following measures of the condition of the pavement surface, mainly measures of functional condition: • • • • • • • • •

Rut depth, Ride quality, Texture depth, Cracking, Fretting, Surface type, Noise, Geometry, Retro-reflectivity of road markings.

All network level pavement issues (for example, network level reporting, budget planning, targeting of priority lengths for treatment) are based on the data collected from the network level surveys. Any additional data required to define/design individual maintenance schemes is collected by project or scheme level surveys. 2.2 Scheme level assessment The main scheme level surveys include those by slow-speed Deflectograph for all schemes other than those of rigid construction. These are needed to assess the structural condition of the pavement and determine whether the pavement is, or remains, a potentially long-life pavement. For flexible pavements requiring surface treatment visual condition surveys will also be required, which will provide data to establish the preferred option for surface treatment. This survey will vary in content depending on the existing pavement construction. In addition, special surveys that are relevant to a particular scheme, or options for a scheme, may be undertaken including: • • • • • •

Falling weight deflectometer, Ground penetrating radar, Dynamic cone penetrometer, Coring or trial pits, CCTV surveys of drainage pipe runs, Topographical surveys. 854

The initial aim of scheme or project level assessment is to determine how far the surface deterioration extends into the pavement and, in particular, whether it is only in the surfacing. Details of the exact location and extent of rutting and pattern of cracking are available from routine survey data. Cores taken on the cracks or at crack ends determine the depth, direction and propagation of cracks. These cores should penetrate at least half-way into the base on fully flexible pavements to ensure that the full depth of cracking can be recorded. They also provide evidence of which layers are affected by rutting and any loss of integrity of the materials, such as stripping of the binder. In future, on the basis of earlier TRL research, Ground Penetrating Radar is likely to be used to assess crack depth penetration over a much larger sample of the scheme than is possible with cores, as presented by Forest and Utsi (2004). If the cracking is found to penetrate into the structural layers of the pavement then a conventional thorough structural investigation will be necessary. 2.3 Treatment selection Acknowledgement of the existence of long-life pavements will of course affect the selection of suitable maintenance treatments. As was stated earlier, long life pavements will not be of infinite life. However, so long as the pavement has been well constructed and the foundations remain sound, no structural treatment such as overlays or reconstruction should be necessary. The surface of a long-life pavement will deteriorate as for determinate life pavements. Accumulated deformation will cause rutting which will need to be treated by replacement or by thin overlay before it becomes a safety hazard. Cracking may initiate at the surface which will need treating by replacement before it penetrates into the structural components of the pavement. Skid resistance will deteriorate and initiate the necessary remedial surface treatment. If structural deterioration has occurred, on a determinate life pavement, strengthening may need to be provided by overlays or reconstruction. However it should be noted that it may be that only thin overlays are necessary to convert a determinate life pavement into a long life equivalent. 2.4 Prioritization of maintenance schemes—current approach The UK Highways Agency is responsible for building and maintaining the motorway and allpurpose trunk road network in England. Individual areas within the network are managed on behalf of HA by specialist consultants known as Managing Agents (MA) or Managing Agent/Contractors (MAC). However the final allocation of maintenance funds is determined by the Highways Agency which needs to ensure that maintenance is targeted at schemes that are likely to yield maximum benefits to the road user, minimise disruption and offer the best value for money. To facilitate the prioritisation process, a Value Management (VM) process was developed and implemented by the Highways Agency, with support from TRL engineers. The VM process was first developed in 1998 to permit relative assessment of capital road maintenance bids. Since 2000/2001, the process has been adopted to develop and prioritise the roads renewal maintenance programme for all schemes over £100,000 (circa $150,000 US). The process comprises a standard submission to be made by the MA/MAC for each proposed scheme. The proposals are scrutinised by HA staff and then jointly scored with the MA/MAC at approximately quarterly continuous Value Management Workshops. The role of each VM workshop is to score each scheme against four criteria, namely: • • • •

Safety, Value for money, Reduction of disruption, Environment.

The scores are used by the Highways Agency to help prioritise the roads renewal programme within each Area and across the five HA Regions and the network as a whole. 855

2.5 Prioritization of maintenance schemes—latest developments The Value Management system has continually evolved encompassing whole-life cost, longlife pavements and many other concepts. Recently the approach has also been adopted to cover other types of maintenance schemes including structures, drainage, geotechnical and lighting schemes. Currently new research is investigating a methodology to harmonise the scores of the VM processes for the different types of highway infrastructure that are at present based on different sets of multi decision criteria. The research will also aim to identify additional ‘value factors’ such as sustainability, carbon footprints etc. and incorporate them in the harmonised VM approach. It will also explore the potential for incorporating a risk based approach in the harmonised methodology. The current Value Management approach has evolved into a very effective and practical tool for prioritising maintenance but further improvements are anticipated from the research briefly described above. 2.6 Pavement management system In order to reliably store all construction and condition information described in the earlier Sections the UK Highways Agency has developed the Highways Agency Pavement management System (HAPMS). In addition to a road network definition and condition data, HAPMS contains data that describe the physical characteristics of the network and its makeup. The main elements of HAPMS are shown diagrammatically in Figure 10. HAPMS consists of a set of computer applications that provide the following business capabilities: • Data management by holding network, construction, definitive inventory, traffic, accident and condition data in a single database; • Data analysis and reporting facilities both in map-base and textual formats; • Integrated tools for the optimisation, in terms of minimising whole life costs within the available budget, of pavement maintenance at both the scheme and network level; • Recording and management of lane closure information.

Figure 10.

Diagram of main components of UK Highways Agency Pavement Management System.

856

3

SUMMARY AND CONCLUSIONS

Over a number of years the UK Highways Agency has developed ever more sophisticated methods for assessing the condition of its strategic road network and selecting the most economic maintenance treatments based on a continuous value management process with an adaptable multi criteria decision tool to provide the essential guidance. Using an approach encompassing rigorous assessment of all proposed maintenance schemes this has demonstrably achieved a consistently high technical quality. Economic decisions are based on robust whole life cost evaluations of the pavement schemes, forcing highway engineers to derive cost effective solutions. Established standards are applied more consistently and the latest research findings are considered positively to achieve quick wins. For example enormous savings totaling many millions of pounds have been achieved by the early implementation of the long-life pavement concept in maintenance decisions including the virtual elimination of deep reconstructions and the encouragement of recycling solutions such as the reuse of bituminous materials and the crack and seat treatment of rigid pavements. ACKNOWLEDGEMENTS © Copyright Transport Research Laboratory 2008. This paper has been produced by TRL Limited as part of a contract placed by the Highways Agency. Any views expressed in it are not necessarily those of the Agency. REFERENCES Christie, C. Ferne, B.W. Kennedy, C.K. & McQueen, S. 2000. Comprehensive pavement condition monitoring—from research to practice. Surface Transport 2000 Conference, Crowthorne, June 2000. Ferne, B.W. Wright, M.A. & Pynn, J. 2003. The development of HARRIS—a system for road surface condition monitoring at traffic speed. TRL Annual Research Review 2002, Crowthorne, TRL 2003. Ferne, B. Langdale, P. Round, N. & Fairclough, R. 2009. Development of the UK Highways Agency Traffic Speed Deflectometer. International Conference on the Bearing Capacity of Roads, Railways and Airfields, Illinois, 2009. Forest, R. & Utsi, V. 2004. Non destructive crack depth measurements with Ground Penetrating Radar. Tenth International Conference on Ground Penetrating Radar, 21–24 June, Delft, The Netherlands. Highways Agency et al., 2004. Design manual for roads and bridges—volume 7: Pavement design and maintenance, Section 3: Pavement maintenance assessment, part 1: Skidding resistance, HA 28/04. London: TSO (The Stationery Office). Highways Agency et al., 2008. Design manual for roads and bridges—volume 7: Pavement design and maintenance, Section 3: Pavement maintenance assessment, part 2: Data for pavement assessment, HA 29/08. London: TSO (The Stationery Office). Highways Agency et al., 2008. Design manual for roads and bridges—volume 7: Pavement design and maintenance, Section 3: Pavement maintenance assessment, part 3: Maintenance assessment procedure, HA 30/08. London: TSO (The Stationery Office). Lukanen, E.O. Stubstad, R. & Briggs, R. 2000. Temperature predictions and adjustment factors for asphalt pavements. FHWA-RD-98–085, McLean, VA: Federal Highway Administration. Lagarde-Forest, R. Cook, A. & Fairclough, R. 2008. Quality assurance of GPR pavement investigation surveys. 12th International Conference on Ground Penetrating Radar, June 16–19, 2008, Birmingham, UK. Nell, S. & Langdale, P. 2008. Highways Agency 2007 National Falling Weight Deflectometer correlation trials. Published Project Report PPR261. Transport Research Laboratory, Wokingham. Nunn, M. & Ferne, B.W. 2001. Design and assessment of long-life pavements: United Kingdom experience. 80th Annual Meeting Transportation Research Board, Washington, D.C., January 2001. Thomas, C. Werro, P. & Wright, M.A. 2007. SCANNER accredited surveys on local roads in England— Accreditation, QA and Audit testing—Annual Report 2005–06. Published Project Report PPR229. Transport Research Laboratory, Wokingham.

857

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Practical use of light weight deflectometer for pavement design S. Baltzer & C. Hejlesen Danish Road Directorate, Danish Road Institute, Denmark

H.C. Korsgaard & P.E. Jakobsen Grontmij, Carl Bro, Pavement Consultants

ABSTRACT: A light weight deflectometer is a recent version of bearing capacity measuring equipment which has been on the Danish market since the end of the nineties. A light weight deflectometer is handy in the field and can be used at an early stage in the construction process—on subgrade and sand difficult to access for traditional measuring equipment. This is why the equipment has great potential in supplementing or maybe even replacing some of the measurements that are conducted during the design and construction phases today. Before replacing other equipment, it is essential to have a good understanding of the capabilities and how results correlate with traditional devices. This paper reports on a test comparing measurements from several bearing capacity devices; Light Weight deflectometer, Falling Weight Deflectometer, Static Plate Load, Vane test equipment and Dynamic Cone Penetrometer. 1

BACKGROUND

With regard to road construction it is important for initial design purposes to know the bearing capacity (E value) of the subgrade at an early stage in the process. The practice of the Danish Road Directorate is to assess the subgrade E value on the basis of CBR tests supplemented by vane tests, if required. In addition to this there are of course empirical values for the various soils which can be helpful when determining the subgrade E value. The Road Directorate adjusts the design when the road has been constructed to the top of the base gravel layer. This is done by measuring the actual bearing capacity of the constructed layers by means of static plate load testing. Design with the measured E values forms the basis of any adjustment of the asphalt layer thickness. As the light weight deflectometer is a fairly new equipment, further experience with the measuring method is required. Both the Road Directorate and Grontmij | Carl Bro have an interest in gathering experience with the measuring method—the Road Directorate as a client and knowledge centre (Danish Road Institute) and Grontmij | Carl Bro as a manufacturer of light weight deflectometers and a consulting engineering company—and the parties have therefore joined forces to perform a major test to compare light weight deflectometer measurements with measurements from traditional and well-known equipment. 2

MADS TEST

The test with the comparative measurements was called MADS, an acronym for “sammenligning af Minifaldlod og Andre Dynamiske og Statiske målemetoder” [Comparison of light weight deflectometers and other dynamic and static measuring methods]. The purpose of MADS was to assess how the E value, determined on the basis of light weight deflectometer measurements conducted on clay till, compares to values based on equipment and methods which already are known and trusted. A second purpose was to test the lightweight 859

1

Removal

2

LWD, 3 devices FWD Static plate load test LWD, 3 devices Nuclear density gauge Dynamic cone penetrometer Vane test Figure 1.

Compaction Repetition of measuring series

Sample-taking

Order of equipment in the test program.

deflectometer with various buffer types and numbers. The tests were conducted at the end of May 2006 on two test sections in connection with a motorway construction project on the island of Lolland, southern Denmark. The test sections were areas of natural soil, where the organic layer had been removed to prepare it for road construction. The test sections were located at the chainages km 128.1 and km 129.5, which are the identity codes used in this paper. In each section, three measuring points were established. The measuring programme lasted three days, as many devices were used to conduct measurements. The test sections were prepared through a slight removal of the surface and a levelling of the individual measuring points with a steel ruler. When measurements had been conducted by all equipment types, the subsoil was compacted and the measuring series was repeated. The order of equipment was set so that that the lightest and least destructive equipment types measured first as shown in figure 1. 3

EQUIPMENT

As shown in figure 1, measurements were performed with six equipment types described in detail below. 3.1 Light weight deflectometer The light weight deflectometer is a portable falling weight equipment performing dynamic loads. The equipment stresses the soil with a load by means of a weight that falls from a given height and transfers a force to a circular load plate. In this case, the force of the individual measurements varied with the drop height of the weight. Figure 2 shows a measurement performed with a light weight deflectometer. Three light weight deflectometers participated in the tests: The Danish Road Institute’s equipment of the make Keros and two from Grontmij | Carl Bro of the make Prima 100. 3.2 Falling weight deflectometer The falling weight deflectometer measures the deflection basin under a dynamic loading corresponding to the loading of a 5 tonne twin-wheel running at a speed of 40–60 km/h. The measurement is performed with a weight which falls freely and transfers the impact force to the subsoil via a buffer system and a cylindrical plate (diameter 300 mm). The mass of the weight, falling height and diameter of the plate are adjusted to the requested impact force. The pulse time is approximately 25 ms. 3.3 Static plate load test Static plate testing was performed by a hydraulic jack acting against heavy construction machinery and thereby transferring load to a cylindrical plate. In order to ensure a uniform 860

Figure 2. Left: the light weight deflectometer of the Road Institute is seen in the foreground and one of the Grontmij | Carl Bro devices and the car with the falling weight deflectometer is seen in the background. Right: a setup for the static plate load test is seen.

Figure 3.

Nuclear density gauge.

load, a pressure distributing rubber plate was applied on the underside of the load plate. For static plate load testing on subsoil (the subgrade) a plate pressure of 50–100 kPa is normally applied. During testing, the pressure must be kept constant while measuring the deflection (see Figure 2). For the MADS test, plates of a diameter of 300 and 760 mm were applied. 3.4 Nuclear density gauge The nuclear density gauge uses a radioactive source to determine the wet density and the water content of unbound materials. The density measurements were performed at depths of 150 mm to 300 mm below surface which are standard measuring depths in Denmark. The water content was determined in the upper 50 to 70 mm. Figure 3 shows a photo of the equipment used for the MADS test. At this test, the density measurements were performed by two measurements with a mutual angle of 45°C, at each test point. 3.5 Dynamic cone penetrometer The Dynamic Cone Penetrometer (DCP) is used for determination of the strength of the individual layers, and at the same time the layer boundary can be determined. The test 861

Figure 4.

Left: the performance of a dynamic cone penetrometer test is seen. Right: a vane test.

was performed by measuring the deflection of the cone tip after five blows with an 8 kg hammer. A photo of the DCP measurement can be seen in figure 4. The result from a DCP measurement is a CBR value that was converted into E modulus by the empirical expression: E = 10 · CBR. 3.6 Vane shear testing The purpose of vane shear testing is to measure the in-situ shear strength properties of soil. By means of this measurement the undrained shear strength is determined along the cylinder face which is cut loose in the soil when the handle and thus the rod is turned (see Figure 4). In cohesive soils, both the undisturbed shear strength, cv, and the remoulded shear strength, cvr, can be determined. At the MADS test, a measurement was taken every 200 mm in depth. On the basis of the undisturbed shear strength, the subsoil E modulus was determined by: E = 100 · cv 4

SOIL CHARACTERISTICS OF THE TEST FIELDS

Soil samples were taken at each test point so that the soil characteristics could be determined on the basis of laboratory tests carried out at the laboratory of the Danish Road Institute. The tests show that the subsoil is weathered clay till. The clay has natural water content between 16% and 19% and a loss on ignition of 4%. In Table 1, liquid limit, plastic limit and plasticity index values are indicated for the sections at kilometer posts 128.1 and 129.5. The variation in the plasticity indexes for the two sections is due to the fact that the test section at km 128.1 has a larger content of fines (< 63 μm) than the test section at km 129.5. CBR tests were performed by means of standard Proctor test of the subsoil samples from each measuring point, as shown in Figure 5. In addition to this, two CBR test variants were performed. The purpose of the first test (circular mark in Figure 5) was to perform Proctor compaction testing with optimum water content in order to obtain dry densities of 100%. The samples were then water-saturated. During compaction testing, only densities of 96–97% were obtained. The purpose of the second test (solid triangle in Figure 5) was also to perform Proctor compaction tests with optimum water content, but with dry densities of 95% followed by water-saturation. In this test the required dry densities were obtained. The purpose of the variations of the CBR tests is to demonstrate which CBR values would be realistic for the in-situ situation. 862

Table 1. Liquid limit, plastic limit and plasticity index for the two test sections. Test field

Liquid limit [%]

Plastic limit [%]

Plasticity index [%]

km 128.1 km 129.5

41 33

13.5 11.5

27 21

2,2

40%

2,1

35%

2,0

30%

1,9

25%

1,8

20%

1,7

15%

1,6

10%

1,5

5%

1,4 0%

5%

10%

15%

IN-SITU Water content

CBR

3 ρd [t/m ]

Proctor og CBR km 129,5 point 3

0% 20%

Water content Dry density

Figure 5.

CBR

96% CBR water-saturated

95% CBR water-saturated

Test results from Proctor and CBR tests and two variants of CBR tests.

From Figure 5 it appears that with an in-situ water content of 16–19%, the soil is watersaturated and a CBR value of approximately 2% can be anticipated. According to experience 2% CBR can be converted into an E value of approx. 20 MPa. From the nuclear density gauge measurements in the field, the dry density is determined to be between 84% and 92%. This means slightly lower than the dry density with which the CBR test variants were performed. Thus, it must be expected that the surface modulus is just below 20 MPa, which corresponds to what can be expected for weathered clay till. The Proctor curve in Figure 5 also illustrates that the in-situ water content of 16–19% is far above the maximum value on the Proctor curve, so the compaction carried out in-situ between the two measuring sequences is not expected to be particularly effective. 5

DETERMINATION OF E VALUE

All bearing capacity measurements were performed under the same uniform conditions as much possible to allow comparison of the E values. In Table 2, the mean E values of the three measuring points in each test field are shown for comparable measuring series. Identical plate sizes were used for light weight deflectometer, falling weight deflectometer and static plate load tests; a radius of 150 mm. The falling weight deflectometers (FWD) and static plate load testing (SPL) were measured with a load close to 100 kPa, so the resulting E value is listed directly in the table. Plate loads applied for the light weight deflectometer (LWD) measurements were both higher and lower than 100 kPa. The value listed in the table is interpolated to 100 kPa. For vane testing the values of the upper 40 cm have been converted into E values, whereas the upper 30 cm of the Dynamic Cone Penetrator (DCP) measurements of have been converted into E values. These depths have been chosen to make sure that results from the different loading equipment are all related to the same “lump” of soil. 863

Table 2. Average surface moduli (in MPa) for the two test sections at a plate pressure of approx. 100 kPa. Test field

km 128.1

km 129.5

Before compaction

LWD, DRI, 3 hard buffers LWD, Grontmij1, 3 hard buffers LWD, Grontmij1, 4 soft buffers FWD Static plate load test Vane test DCP

8.7 7.2 10.6 10.8 10.0 12.3 10.0

13.6 – – 9.8 16.7 13.7 19.3

After compaction

LWD, DRI, 3 hard buffers LWD, Grontmij1, 3 hard buffers LWD, Grontmij1, 4 soft buffers FWD Static plate load test Vane test DCP

12.5 – 16.5 11.8 – – 15.0

17.2 18.2 17.7 12.6 13.0 11.0 19.5

Empirical values

CBR ⋅ 10 Danish Road Standards

max. 20 10–20

max. 20 10–20

The numbers listed in the row “Danish Road Standards” in Table 2, show the span of E values recommended for subgrade of weathered clay till (if no measurement is available) by the Danish Road Standard on design of pavements (Danish Road Directorate, March 2005). As appears from Table 2, all measured E values are within the same order which indicates that on clay till the light weight deflectometers used can be applied on equal terms with other bearing capacity measuring equipment. 6

EFFECT OF COMPACTION WITH ROLLER AND HEAVY EQUIPMENT

The compaction was performed by means of an 8 tonne smooth-wheeled roller which is not ideal compaction equipment for clay, but this was what the contractor could provide at that time. The effect of the compaction was, as expected, very little. However, this seems to be most visible and consistent on the basis of the light weight deflectometer measurements, where the E value has increased by 3–6 MPa after compaction. The density determined on the basis of the nuclear density gauge measurements also reveals a poor effect of the compaction with an increase in dry density of approx. 0.5–1% for measurements undertaken before and after the compaction. The compaction performed with roller improves the bearing capacity. However, it could be interesting to see whether measuring with the heavier equipment, such as the falling weight deflectometer and static plate load, would also compact the measuring points. This was investigated by means of a light weight deflectometer in some of the measuring points. Light weight deflectometer measurements are performed at various drop heights (contact pressure) and therefore the result of the measurements can be illustrated in a curve indicating the E modulus dependency of the plate contact pressure. An example of light weight deflectometer measurements appears in Figure 6, which shows four series of light weight deflectometer measurements conducted; (1) as first measuring equipment and (2) after static plate load to determine whether compaction can be measured after conducting measurements with this equipment. Immediately after (2), measurements were taken with nuclear density gauge, in which case a pole was pounded into the soil where the probe could be placed and a hole was left in the measuring point. Measurement (3) was performed in order to determine whether an effect of the nuclear density gauge hole could be measured. Finally, measurement (4) was made after compaction as the first measuring equipment in the repeated series of measurements. The measurements shown in Figure 6 indicate that the soil is the weakest before compaction. The static plate load test shown in Figure 6 indicates an increase in the E modulus, while 864

Effect of compaction km 128,1, Point 3 45.0 40.0 35.0

E0 (MPa)

30.0 25.0 20.0 15.0 10.0 5.0 0.0 0.0

20.0

40.0

60.0

80.0

100.0

120.0

Contact pressure (kPa) Before compaction - after SPL - after density

Before comp - before SPL

After compaction - after SPL

Before comp - after SPL - before density

Figure 6. Results of measurements performed with the falling weight deflectometer of the Danish road directorate in section km 128.1 and point 3.

Effect of compaction - 2 km 129,5, point 2 45.0 40.0 35.0

E0 (MPa)

30.0 25.0 20.0 15.0 10.0 5.0 0.0 0.0

20.0

40.0

60.0

80.0

100.0

120.0

Contact pressure (kPa) Before compaction - before SPL

Before compaction - after SPL

After compaction - after SPL

Figure 7. Results of measurements performed with the light weight deflectometer of the Danish road directorate in section km 129.5 and point 2.

compaction increases the soil strength even more. The nuclear density gauge measurements do not seem to have any influence on the E value. The figure also illustrates that some compaction allows measuring from higher drop heights, which was initially difficult on the very soft soil. The measurements shown in Figure 6 are the “most proper” and “easiest comprehensible” of the measurements in the six measuring points. The general impression is that compaction increases the E modulus. The highest E modulus increases are seen at low loads, and the lowest increases are seen at high loads. A light weight deflectometer measurement after a static plate load test can result in both a higher and a lower E modulus (see Figure 7) where the E modulus after static plate load test is lower than before such testing. This is assessed to be more than just measuring uncertainties and may be due to the development of pore water overpressure. This must be investigated further through a more thorough treatment of the data. 865

7

VARIATION OF LIGHT WEIGHT DEFLECTOMETER BUFFERS

As mentioned earlier, various types and numbers of buffers were used on the light weight deflectometers for the comparison. The two buffer types were soft, pointed buffers and hard, rounded buffers. The differences in buffer shapes appear from the setups in Figure 8. The soft buffers generate a pulse time of approximately 25 ms, which can be compared to the pulse time of a traditional falling weight deflectometer. Figure 9 illustrates results from measurements with the light weight deflectometer of the Danish Road Institute from a test with both buffer types. The test was performed in points 1 to 3 in the section at km 128.1. As it appears from Figure 9, the pulse times obtained by the two buffer types clearly vary. The soft buffers generate a higher pulse time and a pulse time that depends on the drop height (contact pressure). The hard buffers only generate a very little pulse time reduction at higher contact pressures. On the basis of the measurements with the hard buffers, it appears that pulse time changes do not depend on whether the section was measured before or after compaction. From Figure 9, it appears that the pulse time increases

Figure 8.

The two buffer types used for the test.

Comparison of buffer types km 128,1, Point 1 35.0

Pulse time (msek)

30.0 25.0 20.0 15.0 10.0 5.0 0.0 0.0

20.0

40.0

60.0

80.0

100.0

120.0

Contact pressure (kPa) Before compaction - before SPL - 3 hard buffers

Before compaction - before SPL - 4 soft buffers

Before compaction - after SPL - 3 hard buffers

Before compaction - before SPL - 3 soft buffers

After compaction - after SPL - 3 hard buffers

Figure 9. Comparison of two buffer types; the soft buffers generate a higher pulse time and at the same time a pulse time that varies slightly with the drop height (contact pressure).

866

Comparison of LWD from DRI and Grontmij - after compaction km 128,1 50

E0 (MPa)

40

Grontmij point 1, 4 soft buffers Grontmij point 2, 4 soft buffers

30

Grontmij point 3, 4 soft buffers DRI point 1, 3 hard buffers

20

DRI point 2, 3 hard buffers DRI point 3, 3 hard buffers

10

0 10

20

40

60

80

100

120

Contact pressure [kPa]

Figure 10. Two different light weight deflectometers perform relatively uniform measurements in the points 1 to 3 in section km 128.1.

by a few milliseconds when using three soft buffers instead of four. The same effect is seen when reducing the number of hard buffers. The E modulus dependency on buffer type is, however, not as simple as the pulse time dependency. Figure 10 shows the results from two of the light weight deflectometers in all three measuring points in the field at km 128.1. The curves with circular marks are measuring point 1, the square marks are for measuring point 2, while the triangles are from measuring point 3. Both light weight deflectometers have the same curve shape and the figures show that that point 1 is softer than point 2, which again is softer than point 3. It is good to see such uniform measurements from two different makes of measuring equipment. The curve generated from the measurements with Grontmij | Carl Bro’s light weight deflectometer lies consequently higher than the one generated from the results from the Danish Road Directorate’s light deflectometer. This indicates that soft buffers and thus higher pulse times generate a higher E value. This is, however, not confirmed by all measurements, and therefore further data processing and measurements will look into this before any conclusions are made. 8

COMPARISON WITH OTHER TESTS

The stress dependency that appears from the light weight deflectometer curves confirms that measurements are performed on clay soil. On clay soil the E modulus typically falls with increasing load, which is also characterized as stress softening behavior, whereas the opposite is normally the case on friction soil, however to a minor extent. In the 1970’s a comprehensive Nordic Cooperative Research Project was conducted under the name of STINA [STINA, 1977]. In this project the bearing capacity of various subgrade types was tested both in-situ and by means of laboratory testing. Figure 11 illustrates the result of a dynamic triaxial test on weathered clay till from Akselved, on Sealand, Denmark. Here a corresponding curve shape is seen. However, the STINA test shows that a minimum point on the curve is reached already at a load of approx. 50–60 kPa (0.5–0.7 kp/cm2). This tendency does not appear in the MADS test. The E values obtained in the STINA test, approx. 15 MPa in the minimum point (100 kp/cm2 corresponds to 9.81 MPa), correspond very well with the E values measured in-situ in the MADS test. 867

Figure 11. Dynamic triaxial test on weathered clay till during the STINA test. (1 kp/cm2 corresponds to 0.0981 MPa).

9

CONCLUSIONS

The tests show that light weight deflectometers seem to be able to replace or supplement testing such as falling weight deflectometer, static plate load test, dynamic cone penetrometer, and vane testing when measuring on clay till. It is not recommended to replace nuclear density gauge measurements with light weight deflectometer testing. The purpose of nuclear density gauge testing is to ensure that the material is compacted to an optimum so that no settlements will occur later in the service life of the road—that are at least not caused by insufficient compaction. It is, however, likely that the combination of nuclear density gauge measurements and light weight deflectometer measurements can be a very strong optimisation tool as well as a control tool. During the MADS tests, many measurements were made with a light weight deflectometer in order to obtain more experience on e.g. the influence of buffer type and number on pulse time and E value. So far it can be concluded that: • As expected, the form and material properties of buffers affect the pulse time. However, the pulse time do not seem to have a systematic influence on the resulting E-value. • The pulse time decreases with an increasing number of buffers. Changing from two to five hard buffers generated a reduction in pulse time of approximately 5 ms. REFERENCES Danish Road Directorate, ”Konstruktion og vedligehold af veje og stier, Hæfte 3.3, Dimensionering af befæstelser og forstærkningsbelægninger (Vejdirektoratet, marts 2005)” [Construction and maintenance of roads and paths, Booklet 3.3, Design of pavements and reinforcement pavements, March 2005]. ”STINA, Samarbetsprojekt för tillämpning i Norden av AASHO-undersökningen, Slutrapport, teknisk del, bilagor, A 1977:4”, Nordiske Ministerrådets sekretariat,, Oslo 1976, [The Nordic Cooperative Research Project for the Application of the AASHO Road Test Results (STINA), Final report, technical part, enclosure A 1977:4, the secretariat of The Nordic Council of Ministers, Oslo 1976].

868

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Structural evaluation of rubblized concrete pavements in Iowa H. Ceylan, K. Gopalakrishnan & S. Kim Iowa State University, Ames, Iowa, USA

ABSTRACT: Rubblization is one of the surface preparation techniques before placing a Hot Mix Asphalt (HMA) overlay that involves breaking the Portland Cement Concrete (PCC) pavement into pieces. This paper describes the structural assessment related to the long term performance of rubblized concrete pavements in Iowa. The structural performance of seven representative in–service rubblized concrete pavement sections across Iowa were evaluated through Falling Weight Deflectometer (FWD) and Dynamic Cone Penetrometer (DCP) tests, and visual pavement distress surveys. Through backcalculation of FWD deflection data using the Iowa State University (ISU) layer moduli backcalculation program, the pavement layer moduli values were determined and were correlated with the long-term pavement performance. The backcalculated subgrade modulus values were also compared with the subgrade modulus values obtained from DCP test results. The results indicate that the rubblized pavement sections in Iowa are performing very well. It is recommended that the rubblized pavements be frequently monitored to gain a better understanding of their longterm performance. 1

INTRODUCTION

An asphalt overlay of a fractured concrete pavement has become an alternative rehabilitation strategy that many agencies are now using instead of total reconstruction for heavily distressed Portland Cement Concrete (PCC) pavements. Slab fracturing may be done for two reasons: to attempt to mitigate reflection cracking in the overlay, and/or to dispense with preoverlay repair of a concrete pavement with extensive cracking and/or materials-related deterioration (e.g., “D” cracking, alkali-silica reaction, alkali-carbonate reaction, etc.). Several surface preparation techniques have been used before placing a Hot Mix Asphalt (HMA) overlay in attempts to minimize reflection cracking. Some of the most common techniques are rubblization, crack-and-seat, break-and-seat, and saw-and-seal (Hall et al. 2001). Rubblization is an in-place rehabilitation technique that involves breaking the concrete pavement into pieces. The sizes of the broken pieces usually range from sand size to 75 mm (3 in) at the surface and 305 to 381 mm (12 to 15 in) on the bottom part of the rubblized layer (Von Quintus et al. 2007). The rubblized PCC pavement behaves like a high-quality granular base layer and it responds as an interlocked unbound layer—reducing the existing PCC to a material comparable to a high-quality aggregate base course. This loss of structure must be accounted for in the HMA overlay design thickness (Galal et al. 1999). The results from a comprehensive investigation conducted by PCS/Law (PCS/Law 1991), the National Asphalt Pavement Association (NAPA) study (NAPA 1994), and a nationwide survey conducted by the Florida Department of Transportation (DOT) (Ksaibati et al. 1998) all indicate that rubblization is the most utilized procedure for addressing reflection cracking (Heckel 2002; LaForce 2006). More than 50 million square yards of U.S. highways has been successfully rubblized between 1994 and 2002 since the first project in New York in 1986 (Von Quintus et al. 2007). The performance experience of rubblization have also been studied in a considerable number of states including Illinois (Thompson 1999, Heckel 2002, Wienrank and Lippert 2006), Indiana (Gulen et al. 2004), Wisconsin (Von Quintus et al. 2007), Michigan (Baladi et al 2002; AP Tech 2006), Alabama (Timm & Warren 2004), Ohio (Rajagopal 2006), Arkansas (Rajagopal 2006), Colorado (LaForce 2006), and Texas (Sebesta & Scullion 2006; Scullion 2006). 869

The results of these studies indicated that the performance of rubblization technique varied from place to place and from project to project. The variation is due to factors such as the condition of the existing PCC pavement, type and level of distress, type of construction equipment, environmental conditions, traffic, and type and thickness of HMA overlay. In addition, many agencies are considering the use of mechanistic-based design procedures, such as the Mechanistic Empirical Pavement Design Guide (MEPDG) developed under NCHRP 1–37A (NCHRP 2004) for overlay design procedure. Even though the modulus for the rubblized layer is an important design value in MEPDG to determine the thickness of the HMA overlay, those values reported have not been adequately validated with performance data (Von Quintus et al. 2007). These studies indicate that there is a need to gain more information on the performance of this technique to significantly increase its use as a viable rehabilitation strategy. The primary objective of this study is to evaluate the structural condition of existing rubblized concrete pavements across Iowa and to develop a knowledge database for rubblization, which will be useful in the selection of cost-effective PCC pavement rehabilitation strategies in Iowa. Seven representative rubblized concrete pavement sections across Iowa were selected for evaluation considering state wide location and pavement age. A series of field experiments were carried out at the selected test sections during 2007. The methodology and the results of data analysis are discussed in this paper highlighting the important findings regarding the long-term performance of Iowa rubblized concrete pavements. 2

RUBBLIZATION EXPERIENCE IN IOWA

Iowa has a significant portion of PCC pavements in state highways and county roadways. Many of these pavements have deteriorated to a condition that requires rehabilitation or reconstruction. As early as 1985, the Iowa DOT recognized the potential of rubblization in rehabilitating old concrete pavements and conducted a research project to rehabilitate and evaluate a severely deteriorated concrete roadway (Tymkowicz & DeVrie 1995). A 3.0 km (1.9 mi.) section of L-63 in Mills County was selected and divided into 16 sections. In 1985, HMA overlay construction was done in 13 sections after rubblizing the existing pavement and in three sections without rubblization. The variables of rubblization, drainage, and HMA overlay depths of 75 mm (3 in.), 100 mm (4 in.), and 125 mm (5 in.) were evaluated in 1995. This research led to the following conclusions (Tymkowicz & DeVrie 1995): • The rubblization process prevents reflective cracking. • Edge drains improved the structural rating of the rubblized roadway. • A HMA overlay of 125 mm (5 in.) on a rubblized base provided an excellent roadway regardless of soil and drainage conditions. • A HMA overlay of 75 mm (3 in.) on a rubblized base can provide a good roadway if the soil structure below the rubblized base is stable and well drained. • The Road Rater structural ratings of the rubblized test sections for this project are comparable to the non-rubblized test sections. After this research, the use of rubblization has steadily increased in Iowa state highways and county roadways. Data collected during 2003 and 2004 from projects rubblized between 1997 and 2003 indicate a total of 21 rubblization projects in Iowa. However, there were some changes in the rubblization practices adopted in Iowa which are due to poor subgrade, lack of crushed aggregate base, and the use of thin concrete pavements (Jansen 2006). The main keys to modified rubblization procedure include keeping the concrete pieces in place and tightly interlocked, achieving a maximum sizing in the 305 to 457 mm (12 to 18 in.) range, and keeping traffic off the rubblized pavement until a lift of binder is down (Jansen 2006). 3

EXPERIMENTAL DATA COLLECTIONS

A field experiment was carried out from July 2007 to November 2007 to assess the structural condition of existing rubblized concrete pavements across Iowa. During the field testing, 870

weather was sunny and roads were dried. Seven representative rubblized concrete pavements sections (listed in Table 1) were selected considering state wide location and pavement age. These pavements were at least 5 years old since the day of construction. The experimental test methods include the Falling Weight Deflectometer (FWD), the Dynamic Cone Penetrometer (DCP) and visual distress surveys. Core samples were also extracted to collect in-situ material, identify the layer underneath HMA layer, and provide space for conducting the DCP test. FWD and DCP tests and coring were performed on three locations in each test section—start (A), middle (B), and end (C) point. The visual distress survey was conducted on the entire test section. 3.1 Falling Weight Deflectometer (FWD) FWD has become the standard equipment for evaluating the structural condition of a pavement structure due to the accuracy with which it can measure the deflected shape of a loaded pavement at appropriate rates of loading. The FWD test is conducted by applying dynamic (impulse) loads to the pavement surface, similar in magnitude and duration to that of a single heavy moving wheel load. The response of the pavement system is measured in terms of vertical deformation or deflection over a given area using seismometers (geophones). In this research, the FWD was used as the main nondestructive test (NDT) equipment to evaluate the structural condition of rubblized pavement sections. Deflection data were collected using Iowa DOT’s JILS-20 FWD (see Figure 1) by applying a step loading sequence of 27, 40, 53, and 67 kN (6,000, 9,000, 12,000 and 15,000 lbs) at three different locations (start, middle, and end Table 1.

List of rubblized pavement sites for field evaluation. Location

Layer thickness (mm)

Test section no.

County

Road

HMA

Granular

Rubblized PCC

AADT*

Construction year

1 2 3 4 5 6 7

Black Hawk Black Hawk Delaware Franklin Mils Polk Polk

D16 V43 IA3 C23 L55 IA 141 IA 141

168 163 246 191 180 193 234

0 0 0 76 0 0 0

191 201 221 234 155 229 249

1,280 1,340 740 120 820 18,000 18,000

2001 2001 2003 1998 1999 2001 2001

*AADT = Annual Average Daily Traffic in 2005.

Figure 1.

Picture of Iowa DOT’s JILS-20 FWD equipment.

871

point) in each test project. The locations of geophones in the Iowa DOT’s FWD equipment are at 0 (D0 mm), 203 (D203 mm), 305 (D305 mm), 457 (D457 mm), 610 (D610 mm), 914 (D914 mm), 1219 (D1219 mm), and 1524 mm (D1524 mm) from the center of FWD plate load. 3.2 Dynamic Cone Penetrometer (DCP) DCP tests were conducted at the same locations after coring where FWD tests were conducted. The DCP tests were conducted to collect additional information about the in-situ subgrade soil properties. The DCP is an in situ device where measurements of penetration per blow (mm/blow) are obtained. In 2003, the ASTM published a standard for use of the DCP (ASTM D6951 2003), “Standard Test Method for Use of the Dynamic Cone Penetrometer in Shallow Pavement Applications.” The device works by using a standard 8 kg (17.6 pound) hammer, which is lifted to the handle and dropped to the anvil, forcing the rod to penetrate the compacted soil area. The greater the number of blows needed to penetrate the rod into the soil, the stiffer the material. 3.3 Visual distress survey Visual distress surveys over the entire test section were conducted for the selected project sites identified in the field evaluation program. The distress survey methodology employed was similar to that described in the Strategic Highway Research Program’s (SHRP) “Distress Identification Manual for the Long-Term Pavement Performance (LTPP) Project” (Miller and Bellinger 2003). A distinction was made between reflective cracking and low—temperature (transverse) cracking. Cracking was identified as “reflective cracking” when the transverse cracks were uniformly spaced (corresponding to PCC joint spacing underneath the HMA layer). 4

ANALYSES OF IOWA’S RUBBLIZED PAVEMENTS

4.1 FWD data analyses Two-frequency FWD tests were conducted on a single location to identify the FWD sensor measurement errors. No significant differences were observed, which indicated that the FWD can produce consistent results for same test material. The measured deflections on geophones showed a linear trend with increasing FWD loads (see Figure 2). This indicates that the deflections at different FWD load levels can be normalized to one FWD load level. The measured deflections at 27, 53, and 67 kN of FWD loads were all normalized to 40 kN FWD load. Figure 3 presents the average of normalized maximum FWD deflections (D0 mm) for each test section. The pavement layer modulus is an important property representative of the pavement structural condition as well as a required input in the MEPDG. Recently, researchers at Iowa State University (ISU) developed user friendly and spreadsheet-based software for layer moduli backcalculation of rubblized PCC pavements (see Figure 4). This program employs Artificial Neural Networks (ANN)-based structural models for predicting not only the moduli of pavement layers based on FWD deflection data, but also the critical structural responses. The ANN-based structural models were developed by relating the structural responses (strains and deflections) to layer thicknesses and moduli values using a synthetic database. A synthetic database was generated using an Elastic Layer Program (ELP) by computing the critical strains for a wide range of layer thicknesses and moduli values. Details of the development and validation of ANN based structural models are described by Ceylan and Gopalakrishnan (2007). The FWD surface deflections obtained for rubblized sections were inputted into the ISU rubblized pavement layer moduli backcalculation program to predict the moduli of HMA, rubblized PCC and subgrade. The modulus of HMA is more temperature-sensitive than the modulus of rubblized PCC and subgrade. The computed HMA moduli at different temperature conditions were adjusted to the HMA moduli at a reference temperature (25ºC) using Equation 1 reported by Noureldin (1994). 872

Figure 2.

FWD deflections with loads.

Figure 3.

Normalized FWD maximum deflections (D0 mm).

Figure 4.

ISU rubblized PCC pavement layer moduli backcalculation program.

873

EAC = EAC ,25 ×

2747.5 (T )2.46

(1)

with EAC = Asphalt concrete modulus (MPa), EAC,25 = Asphalt concrete modulus at 25 ºC, and T = Asphalt concrete temperature, ºC. Figure 5 clearly illustrates the effect of temperature on HMA modulus. The backcalculated HMA modulus below 25ºC decrease and the modulus above 25ºC increase after adjustment to the reference temperature of 25ºC. Figure 6 summarizes the layer moduli results for each of the rubblized sections. Table 2 presents the overall statistical summary for layer moduli results. The average rubblized PCC modulus in this study was found to be 539 MPa (78 ksi). This is numerically closer to the modulus value of 448 MPa (65 ksi) recommended by Wisconsin DOT study (Von Quintus et al. 2007). Both of them are lower than the default modulus value of 1034 MPa (150 ksi), which is currently used in MEPDG (NCHRP 2004) and recognized as a quite conservative value (Von Quintus et al. 2007). The backcalculated rubblized PCC modulus values in this study ranged from 259 to 1,120 MPa (38 to 162 ksi). This variation might be due to factors such as the condition of the existing PCC pavement, type and level of distress, type of construction equipment, environmental conditions, traffic, and type and thickness of HMA overlay. A similar range of values, 247 to 827 MPa (35 to 120 ksi), was reported by Wisconsin DOT study (Von Quintus et al. 2007). These values are similar to those determined from deflection basin testing of HMA overlays placed over rubblized PCC pavements—both from the Long-Term Pavement Performance (LTPP) Specific Pavement Studies-6 (SPS-6) experiment and actual construction projects reported by Von Quintus et al. (2000).

Figure 5.

HMA moduli before and after adjustment to a reference temperature of 25ºC.

25,000

1,000 Rubblized PCC 900

Subgrade

800

Modulus (MPa)

HMA Modulus (MPa)

20,000

15,000

10,000

700 600 500 400 300

5,000

200 100

0

(a)

Figure 6.

0

No.1

No.2

No.3

No.4

No.5

No.6

No.7

(b)

Test Section

No.1

No.2

No.3

No.4

No.5

No.6

Test Section

Backcalculated pavement layer moduli: (a) HMA; (b) Rubblized PCC and subgrade.

874

No.7

Table 2.

Overall statistical summary for pavement layer moduli.

Variable

HMA modulus (MPa)

Rubblized PCC modulus (MPa)

Subgrade modulus (MPa)

Average S.D. Max Min

12,092 9,604 60,416 2,268

539 310 1,120 259

100 28 140 66

200

Subgrade Modulus (MPa)

180

DCP Average: 89 STEDV: 48

FWD Average: 100 STEDV: 28

DCP FWD

160 140 120 100 80 60 40 20 0 No.1

No.2

No.3

No.4

No.5

No.6

No.7

Test Section

Figure 7.

Comparison of subgrade modulus values from DCP and FWD.

4.2 DCP test results To represent DCP measures at different depths in each location, the average rate of penetration or penetration index (DCPIwtag) is determined by calculating the weighted average using the following Eq. (2) (Sawangsuriya and Edil 2004): DCPI wtag =

1 N ∑[( DCPI )i × ( z )i ] H i

(2)

with H = total penetration depth, z = layer thickness, DCPI = penetration index for z, (mm/blow). The rate of penetration (DCPI) has been correlated to the California Bearing Ratio (CBR, percent), an in situ strength parameter (ASTM D6951 2003). The DCPI-CBR correlation for soils other than CL soils below CBR 10% and CH soils is as follows: CBR =

292 DCPI 1,12

(3)

The CBR has been correlated to the resilient modulus (Mr), an input parameter representing soil material strength in MEPDG (NCHRP 2004). The Mr-CBR correlation used in the MEPDG is as follows: M r = 2555(CBR )0.64

(4)

The average DCPIwtag and CBR values for test sections are 26.2 mm/blow and 15.9%, respectively. As shown in Figure 7, the average subgrade modulus value of 89 MPa (12 ksi) 875

obtained from DCP test results is slightly lower than the backcalculated subgrade modulus value of 100 MPa (14 ksi) obtained from FWD data using the ISU ANN-based backcalculation program. This result indicates that the ISU ANN-based backcalculation program provides good predictions for subgrade modulus. The average rubblized pavement subgrade modulus value of 89 and 100 MPa (12 and 14 ksi) meets the minimum strength requirement 69 MPa (10 ksi) of the foundation layers for rubblization project specified by Wisconsin DOT (2007). Considering the fact that the DCP and FWD tests were conducted in summer, the results seem to indicate that the foundation layer of Iowa rubblized sections can provide enough strength. 4.3 Visual distress survey The visual distress survey results are summarized in Table 3. In general, no load-associated distresses, such as fatigue cracking, were found in any of the test sections as shown in Figure 8. The predominant distresses observed in the rubblized PCC sections are longitudinal cracking and low-temperature cracking as shown in Figures 9 and 10, respectively. No reflection cracking was observed in these rubblized PCC sections. The test sections were also well drained. These results tend to indicate that the rubblized pavement sections in Iowa are performing very well under the structural conditions identified in this study.

Table 3.

Summary of visual distress survey results. Location

Test section no.

County

Road

Visual distress survey results

1 2 3

Black Hawk Black Hawk Delaware

D16 V43 IA3

4 5 6

Franklin Mils Polk

C23 L55 IA 141

7

Polk

IA 141

11 low temperature cracks 1 block and 8 low temperature cracks 2 longitudinal cracking on wheel paths (about 4.8 km) and 9 low temperature cracks No cracks 14 low temperature cracks 14 longitudinal cracks, 3 low temperature cracks 2 longitudinal cracks

Figure 8. Picture of distress-free HMA surface on rubblized PCC (test section no. 4: C23 in Franklin county).

876

Figure 9. Picture of longitudinal cracking on HMA overlaid rubblized PCC (test section no. 3: IA3 in Delaware county).

Figure 10. Picture of low-temperature cracking on HMA overlaid rubblized PCC (test section no. 1: D16 in Blackhawk county).

5

SUMMARY OF FINDINGS

The structural condition of existing rubblized concrete pavements across Iowa was evaluated through Falling Weight Deflectometer (FWD) tests, Dynamic Cone Penetrometer (DCP) tests, and visual pavement distress surveys, etc. Through backcalculation of FWD deflection data using the ISU layer moduli backcalculation program, the pavement layer moduli values were determined for various projects and were correlated with the long-term pavement performance. The backcalculated subgrade modulus values were also compared to the subgrade modulus values obtained from DCP test results. Based on the results of this study, the following findings and conclusions were drawn: • Rubblization is a valid option to use in the rehabilitation of PCC in Iowa under good support or foundation. • Iowa’s rubblized pavement sections considered in this study are performing very well. The predominant distresses exhibited on HMA overlaid rubblized PCC sections are non-load associated distresses such as low-temperature cracking and/or longitudinal cracking. • The average rubberized PCC modulus of the rubblized layer in this study was found to be 539 MPa which is close to the modulus value of 448 MPa recommended by Wisconsin DOT study. • The ISU ANN-based backcalculation program provides good predictions for subgrade modulus. REFERENCES Applied Pavement Technology (AP Tech), Inc. 2006. Evaluation of Rubblized Pavement Sections in Michigan Constructed between 1988 and 2002, Final Report, Prepared for Antigo Construction, Inc, Antigo, Wisconsin. ASTM D6951. 2003. Standard test method for use of the dynamic cone penetrometer in shallow pavement applications, American Society for Testing and Materials, West Censhohocken, Philadelphia. Baladi, G., Svasdisant, T. & Chatti, K. 2002. Identify Causes for Under Performing Rubblized Concrete Pavement, MDOT-PRCE-MSU-1999-110, East Lansing, Michigan. Ceylan, H. and Gopalakrishnan, K. 2007. Neural networks based models for mechanistic-empirical design of rubblized concrete pavements. Proceedings of Geo-Denver 2007 (CD-Rom), ASCE, Denver, Colorado. Galal, A.K., Coree, B.J., Haddock, E.J. & White, T.D. 1999. Structural adequacy of rubblized portland cement concrete pavement. Transportation Research Record 1684: 172–177, National Research Council, Washington, DC. Gulen, S. Noureldin, A.S. & Weaver, J. 2004. Life and Cost Comparison of Three Rehabilitation Techniques on I-65 between SR-2 and SR-114, FHWA/IN/JTRP—2004/8, Indiana Department of Transportation, West Lafayette, Indiana.

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Hall, K.T., Correa, C.E., Carpenter, S.H. & Elliot, R.P. 2001. Rehabilitation Strategies for Highway Pavements, NCHRP Web Document 35 (Project C1-38): Contractor’s Final Report, National Cooperative Highway Research Program, Transportation Research Board, Washington, DC. Heckel, L.B. 2002. Rubblizing with Bituminous Concrete Overlays—10 Years Experience in Illinois, Final Report IL-PRR-137, Illinois Department of Transportation, Springfield, Illinois, (September 3, 2007). Jansen, J. 2006. Rubblization vs. crack and seat, 2006 Great Iowa Asphalt Conference, Des Moine, Iowa. Ksaibati, K., Miley, W. & Armaghani, J. 1998. Rubblization of Concrete Pavements, FL/DOT/SMO/98426, Florida Department of Transportation, Gainesville, Florida. LaForce, R.F. 2006. Performance of Colorado’s first Rubblization Project on I-76 near Sterling, CDOTDTD-R-2005-20, Yeh and Associates, Prepared for Colorado Department of Transportation, Denver, Colorado. Miller, J.S. & Bellinger, W.Y. 2003. Distress Identification Manual for the Long-Term Pavement Performance (LTPP) Project, FHWA-RD-03-031 (4th edition), Federal Highway Administration. Mclean, Virginia. National Asphalt Pavement Association (NAPA). 1994. Guidelines for Use of HMA Overlays to Rehabilitate PCC Pavements, Information Series 117, Lanham, Maryland. National Cooperative Highway Research Program (NCHRP). 2004. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures, Draft Final Report NCHRP Project 1-37A, Transportation Research Board, National Research Council, Washington, DC. Noureldin, A.S. 1994. Temperature gradient in full depth asphalt and its effect on modulus and shear Gradients. The Proceedings of 6th Conference on Asphalt Pavements for Southern Africa (CAPSA), Cape Town, South Africa. PCS/Law. 1991. Guidelines and Methodologies for the Rehabilitation of Rigid Highway Pavements using Asphalt Concrete Overlays, PCS/Law Consulting Services, prepared for NAPA and SAPAE, Maryland. Rajagopal, A. 2006. Investigation of Pavement Cracking on SR-4 and Demonstration of Multi-Head Breaker in Fracturing Reinforced Concrete Pavements before Asphalt Overlay, FHWA/OH-2006/12, Infrastructure Management & Engineering, Inc., Prepared for Ohio Department of Transportation, Columbus, Ohio. Sawangsuriya, A. & Edil, T.B. 2004. Soil stiffness gauge and dynamic cone electrometer for earthwork property evaluation. Proceedings of the 83rd Annual Meeting Transportation Research Board (CD-Rom). Washington, DC. Scullion. T. 2006. Nondestructive testing results from the rubblized concrete pavement on interstate 10 in Louisiana. Rubblization of Portland Cement Concrete Pavements, Transportation Research Circular E-C087, Transportation Research Board, Washington, DC. Sebesta, S., Scullion, T. & Von Holdt, C. 2006. Rubblization for Rehabilitation of Concrete Pavement in Texas: Preliminary Guideline and Case Studies, FHWA/TX-06/0-4687-1, Texas Transportation Institute, College Station, Texas. Thompson, M.R. 1999. Hot mix asphalt overlay design concepts for rubblized Portland cement concrete pavements. Transportation Research Record 1684: 147–155, National Research Council, Washington, DC. Timm, D.H. & Warren, A.M. 2004. Performance of Rubblized Pavement Sections in Alabama, IR-04-02, Highway Research Center, Auburn University, Auburn, Alabama. Tymkowicz, S. & Derives, S. 1995. Iowa Development of Rubblized Pavement Base—Mills County, HR315, Iowa Department of Transportation, Ames, Iowa. Von Quitus, H.L. & Tam, W. 2000. HMA overlay Design for Rubblization of PCC Slabs, Report No. 3066., Brent Rasht Engineering, Inc., Final Report prepared for Michigan Asphalt Pavement Association, Lansing, Michigan. Von Quitus, H.L., Rao, C., Mallela, J. & Aho, B. 2007. Guidance, Parameters, and Recommendations for Rubblized Pavements, Final Report WHRP 06-13, Wisconsin Department of Transportation, Madison, Wisconsin. Wienrank, C.J. & Lippert, D.L. 2006. Illinois performance study of pavement rubblization. Rubblization of Portland Cement Concrete Pavements, Transportation Research Circular E-C087, Transportation Research Board, Washington, DC. Wisconsin DOT. 2007. Facilities Development Manual, Madison, Wisconsin, (September 3, 2007).

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Structural evaluation of Full-Depth Reclamation in Virginia A.K. Apeagyei & B.K. Diefenderfer Virginia Transportation Research Council, Charlottesville, Virginia, USA

ABSTRACT: In an effort to more effectively fund pavement rehabilitation, the Virginia Department of Transportation (VDOT) is investigating the use of full-depth reclamation (FDR) as a pavement rehabilitation alternative on a trial basis. This paper documents the in-situ structural testing related to foamed asphalt and asphalt emulsion-based FDR process on an existing two-lane rural highway in Virginia. The effectiveness of the FDR process was characterized by performing falling-weight deflectometer (FWD) testing to compare the before-and-after structural condition. The results of the study show an increase in structural capacity of FDR sections over the first seven months of service. The FWD results allowed for the calculation of a structural layer coefficient for the FDR pavement sections containing different binding agents. Data used in this study suggests initial differences in structural capacity of FDR sections based on binding agent used. Additional laboratory testing and field monitoring of the projects is recommended. 1

INTRODUCTION

Pavement recycling has become an increasingly used technology to extend the service-lives of pavement structures and to stretch available funding for pavement rehabilitation. In general, in-place pavement recycling remixes the in-situ pavement material in some form and reuses it in the final pavement. This is may be performed as either Cold In-Place Recycling (CIR) or Full-Depth Reclamation (FDR). CIR consists of pulverizing all or a potion of the existing HMA layers and mixing them with a rejuvenating agent. This material is then repaved in a cold temperature operation. The pavement may then be surfaced by a new hot-mix asphalt (HMA) layer. FDR consists of pulverizing the existing bound layers along with all or a portion of the unbound layers and/or subgrade, adding a binding agent (such as foamed or emulsified asphalt binder, Portland cement, or fly ash), compacting the mixture, and surfacing with a new HMA layer. FDR has been successfully demonstrated by several highway agencies including: Georgia (Lewis et al., 2006), Kansas (Romanoschi et al., 2004), Louisiana (Mohammad et al., 2003), Maine (Mallick et al., 2002a, 2002b), Nevada (Bemanian et al., 2006; Maurer et al., 2007), Texas (Hilbrich and Scullion, 2008), Utah (Guthrie et al., 2007), Wisconsin (Wen et al., 2004), Saskatchewan (Berthelot et al., 2007), and New Zealand (Saleh, 2004). In particular, Nevada DOT has placed an emphasis on the use of both CIR and FDR for their pavement network. Bemanian et al. (2006) states that Nevada has completed nearly 900 centerline miles of FDR since 1985 and that the use of this process has increased the load-carrying capacity and structural uniformity of their pavement system. The authors state the use of FDR has resulted in cost savings in the hundreds of millions of dollars when compared to traditional reconstruction processes. In order to more effectively utilize FDR in empirical-based pavement design methodologies, others have reported their processes for determining layer coefficients and/or layer moduli of FDR materials. The results from other organizations investigating layer coefficients for FDR materials utilizing the falling-weight deflectometer (FWD) are summarized in Table 1. It could be seen from Table 1 that reported layer coefficients vary widely and range from a low of 0.17 to a high of 0.42.

879

Table 1.

Summary of structural layer coefficients for FDR.

Reference

Binding agent

Layer coefficient

Romanoschi et al., 2004 Marquis et al., 2003 Dai et al., 2008

Foamed asphalt Foamed asphalt Foamed asphalt Asphalt emulsion Fly ash Foamed asphalt

0.18 0.22–0.35 0.20–0.42 0.17–0.41 0.23 0.18

Wen et al., 2004 Bemanian et al., 2006

2

BACKGROUND

VDOT recently completed an FDR trial where an approximate 1.6 km (1 mile) section of a rural primary route was rehabilitated using foamed asphalt and asphalt emulsion as the stabilizing agent. Within the project site, both lanes over a half-mile length were reclaimed using foamed asphalt as a binding agent and both lanes over an adjacent half-mile section were reclaimed using emulsified asphalt as a binding agent. The reclamation work was performed during May 2008 and consisted of two passes of a reclaimer to pulverize the existing pavement followed by shaping and compaction. The first pass of the reclaimer pulverized the existing roadway and added approximately 2% Portland cement (by weight) to the pulverized section. The second pass involved the distribution of one of the two asphalt binder treatments: asphalt emulsion consisting of a PG 58-22 binder or foamed asphalt consisting of a PG 64-22 binder. The amount of asphalt binder used was determined based on evaluation of the existing pavement materials and were 3.5% and 3.0% for emulsion and foamed asphalt, respectively. The Wirtgen model WR 2500 S pavement reclaimer used was equipped with onboard metering capability to accurately handle water and asphalt emulsion or foamed asphalt during the reclamation operation. Figure 1 shows the road reclaimer with emulsion tanker during the reclamation process on Route 40. Following the pulverization and addition of the binding agent, the reclaimed material was shaped by using a motor grader and compacted with a pad-foot and pneumatic tire roller. After compaction, density measurements were performed using a nuclear gauge. The results of density tests from the emulsion sections indicated average density values of 20.56 kN/m3 (130.9 Ib/ft3) and 20.64 kN/m3 (131.4 lb/ft3) for the eastbound and westbound directions respectively. Compared to laboratory-based modified Proctor dry density testing, a relative compaction of 102% was achieved on the emulsion sections. Similar results were obtained for the foamed sections. Following this, traffic was allowed on the pavement. An HMA overlay was added after approximately two weeks. FWD deflection testing was conducted prior to the reclamation process and again after the reclamation process and HMA overlay were completed. Deflection testing was performed 7 months prior to the reclamation process and also at 1, 1.5, 2, 2.5, 3, 4, and 7 months after reclamation. This testing was performed to assist VDOT with determining the thickness uniformity and the structural capacity of the reclamation process for future rehabilitation projects. 2.1 Site description State Route 40 is an east-west facility that runs through southern-central Virginia, approximately 56 km (35 miles) south of the city of Roanoke. This section has a combined traffic volume of approximately 1,800 vehicles per day (3% trucks) and is a two lane undivided facility (VDOT, 2006). The existing pavement consisted of approximately 12.7 to 15.2 cm (5 to 6 in.) of HMA and surface treatments over approximately 15.2 to 25.4 cm (6 to 10 in.) of aggregate materials (consisting of crushed aggregate and uncrushed gravel). Prior to reclamation, the original pavement showed numerous structural distresses including longitudinal cracking and alligator cracking within the wheel paths. 880

Figure 1. A Wirtgen model WR 2500 S pavement reclaimer with onboard metering capability for water, asphalt emulsion, and foamed asphalt was used.

2.2 Data collection and analysis Deflection testing was conducted by using VDOT’s Dynatest model 8000 FWD. The FWD load plate was located between the wheel paths during testing. The FWD was equipped with nine sensors at radial distances of 0, 20.3, 30.5, 45.7, 61.0, 91.4, 121.9, 152.4, and 182.9 cm (0, 8, 12, 18, 24, 36, 48, 60, and 72 in.) from the center of the load plate. Testing was conducted at 100 foot intervals and at four load levels 26.7, 40.0, 53.4, and 71.2 kN (6000; 9000; 12,000; and 16,000 lbf). At each load level, two deflection basins were recorded. In addition to the measured deflection (Sensors 1 through 9), the following data were reported or calculated from the FWD testing: plate load, plate pressure, air and surface temperature, test date and time, subgrade resilient modulus (MR), effective pavement modulus (Ep), and effective structural number (SNeff). The previous day’s average air temperature (average of high and low) was obtained from Weather Underground (www.wunderground.com) for the day preceding each test date from a nearby weather station. These data were used to calculate a temperature-corrected (corrected to 68°F) deflection under the load plate (D0). FWD data were analyzed using ModTag, Version 4.1.9 (VDOT, 2007). The trial pavement sections were analyzed by evaluating the temperature corrected deflection under the load plate (D0) and calculating the effective structural number (SNeff) and effective structural number (Ep). The analyses were conducted in accordance with the 1993 American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures (AASHTO, 1993). The pavement was analyzed as two separate pavement structures. Testing using ground penetrating radar was used to detect differences in pavement thickness between the western half of the project (emulsion) and the eastern half (foamed asphalt). Coring performed in October 2008 confirmed the pavement thicknesses. 3

RESULTS

3.1 Deflection testing Deflection testing using the FWD was performed 7 months prior to the reclamation process (before testing) and also at 1, 1.5, 2, 2.5, 3, 4, and 7 months after reclamation (after testing). Figure 2 shows the variation of the deflection at the load plate (D0) at the 40-kN (9000-lbf) load level with time for both emulsified and foamed asphalt sections. It can be seen that the 881

30

30 Emulsion

25

25 FWD deflection (mils)

FWD deflection (mils)

Emulsion 20 Before reclamation

15

Foam 10

5

20

Before reclamation

15 Foam

10

5

0

0 0.0

2.0

4.0

6.0

8.0

0.0

Time (months)

2.0

4.0

6.0

8.0

Time (months)

Figure 2. Variations in FWD deflection at the load plate (D0) at 40-kN (9000-lbf) load level with time for formed asphalt and asphalt emulsion-based FDR (left eastbound, right westbound) (1 mil = 0.0254 mm).

deflection values for the emulsified section were higher than pre-construction levels (baseline deflections) for the entire 7 months of monitoring on the eastbound section and first 2-1/2 months on the westbound section. The opposite is true for the foamed sections which exhibited relatively lower deflections compared to both emulsified and the baseline deflection levels throughout the monitoring period. The lower deflections observed on the foamed sections could be due to two reasons: 1) the stiffer PG 64-22 binder used and 2) the relatively lower binder content of 3.0% used compared with 3.5% used on the emulsified sections. 3.2 Structural capacity Effective pavement modulus (Ep) and effective structural number were used as measures of pavement structural capacity for this study. Ep is the effective modulus of all the pavement layers above the subgrade (AASHTO, 1993). Ep was backcalculated from the FWD deflection data (D0) that had been normalized to a temperature and a load level of 68°F and 40 kN (9000 lbf), respectively, using the ModTag program. Following the reclamation procedure, the division between the emulsion and foamed sections occurred at approximately milepost 12.17 for the westbound direction and 12.19 for the eastbound direction. Figure 3 compares the change in average effective pavement modulus with time for the completed FDR sections. The results show that the foamed sections have relatively higher effective pavement modulus compared with the emulsion asphalt section. Structural number is a function of both pavement layer thickness and the Ep. Effective structural number (SNeff) was computed using Equation 1 (AASHTO, 1993). FWD testing of the existing pavement sections indicated average structural numbers of 3.69 and 3.08 respectively for the eastbound and westbound sections. The coefficient of variation (COV) of the pre-construction structural number in the eastbound and westbound directions was calculated as 9.1% and 8.9%, respectively which suggests both sections were reasonably uniform in terms of variation in structural capacity. It is to be noted that a hypothetical new pavement section with similar material properties and layer thicknesses as the existing pavement sections would be assigned design structural numbers of 4.24 and 3.72 for the eastbound and westbound sections respectively based on VDOT specifications. Table 2 shows the layer thicknesses used in the FWD analysis based on ground penetrating radar testing and core collection. 882

400000

400000

300000

300000 Modulus (psi)

Modulus (psi)

Foam

200000 Emulsion 100000

Foam 200000 Emulsion 100000

Before reclamation

Before reclamation

0

0

0

2

4

6

8

0

2

Time (months)

4

6

8

Time (months)

Figure 3. Variations in effective pavement modulus (Ep) with time for foamed asphalt and asphalt emulsion-based FDR (left eastbound, right westbound) (1 psi = 6.89 kPa). Table 2.

Layer thicknesses for Route 40 Virginia (1 in. = 25.4 mm). Milepost

Layer thickness (in.)*

Direction

Material

From

To

Layer 1

Layer 2

Layer 3

Eastbound

Emulsion Foam Emulsion Foam

11.85 12.17 11.85 12.11

12.17 12.39 12.11 12.39

2.5 2.5 2.2 2.2

9.1 10.4 10.5 8.3

3.0 3.8 2.5 3.6

Westbound

* Layer 1 HMA, Layer 2 FDR, and Layer 3 aggregate.

SNeff = 0.0045D 3 E p

(1)

where D = total thickness of layers above the subgrade. The initial FWD test showed the reclaimed pavement within the emulsion section to have an average structural number of 2.53 and 2.62 in the eastbound and westbound directions, respectively. For the foamed sections, tests taken after reclamation showed a structural number of 3.41 and 3.45 in the eastbound and westbound directions, respectively. Results of deflection testing including mean SNeff and COV, in the eastbound and westbound directions for the 7-month testing period are summarized in Table 3. Also shown in Table 3 is the coefficient of variation (COV) values for SNeff which compares quite well with previous studies. The structural capacity on the reclaimed pavements increased with time as shown in Figure 4 for eastbound and westbound directions, respectively. Examination of Table 3 and Figure 4 suggests the foamed asphalt section gained a higher structural capacity initially for both eastbound and westbound directions. From Figure 4 it can be seen that the effective structural number (SNeff) of the foamed asphalt on the eastbound direction exceeds the pre-construction values approximately 2 months after construction compared with approximately 6 months for the emulsified asphalt section. Figure 4 also shows that the effective structural number (SNeff) of the foamed asphalt on the westbound direction exceeds the pre-construction values approximately 1 month (the date of 883

Table 3.

Effective structural number for Route 40 Virginia (determined from FWD testing).

Eastbound Time emulsion Foamed (month) mean COV (%) mean

Westbound emulsion Foamed COV (%) mean COV (%) mean COV (%)

1.0 1.5 2.0 2.5 3.0 4.0 7.0

8 5 8 6 3 4 8

2.53 2.72 2.78 2.95 2.97 3.12 4.05

15 15 16 16 15 14 18

3.41 3.69 3.84 3.97 4.08 3.93 4.53

2.87 2.87 2.87 3.02 3.07 3.25 3.77

5.0

3.45 3.40 3.52 3.62 3.67 3.75 3.77

31 15 16 14 13 12 16

5.0

4.5

4.5

Foam

4.0 3.5

Structural number (SN)

Structural number (SN)

14 14 13 13 12 10 11

Before reclamation

3.0 Emulsion

2.5 2.0 1.5

4.0

Foam

3.5 3.0

Before reclamation

Emulsion

2.5 2.0 1.5

1.0

1.0 0.0

2.0

4.0

6.0

8.0

0.0

Time (months)

2.0

4.0

6.0

8.0

Time (months)

Figure 4. Variations in structural number with time for foamed asphalt and asphalt emulsion-based FDR (left eastbound, right westbound).

the first test) after construction compared with 3 months for the emulsified asphalt section. For both the emulsified and foamed sections, however, the effective structural number (SNeff) continued to increase 7 months after construction on the eastbound direction. For the westbound direction, the increase in effective structural number (SNeff) appears to taper off after approximately 4 months after construction for the foamed asphalt section while for the emulsion section, the effective structural number (SNeff) value appears to continue to increase. As noted in Figure 3, the structural capacity of the foamed asphalt sections, as indicated by the effective pavement modulus, is higher than the emulsion section. Examination of Figure 4 suggests the rate of gain in structural number of the foamed asphalt section with time (about 0.14 per month) is comparatively lower than the emulsion section (about 0.20 per month). The relatively higher rate in structural capacity gain observed on emulsion sections could be due to the greater amount of curing expected for an emulsified binder which typically contains more added water than foamed asphalt. Assuming the trends in structural capacity increase with time as shown in Figures 3 and 4 continue, it is expected that SN for the foamed sections would exceed a hypothetical new pavement with similar pavement structure as the before-FDR section in about 5 months. Similarly, the trends in Figures 3 and 4 suggest the time required for the emulsion sections will be longer than five months. If additional testing confirms this initial observation, this approach could be used to estimate suitable time-based SN to be used during FDR design. 884

Table 4. Calculated layer coefficients for FDR stabilized base layer on Route 40 Virginia. Eastbound emulsion

Foam

Westbound emulsion

Foam

Average emulsion

Foam

0.28

0.29

0.24

0.29

0.26

0.29

3.3 FDR layer coefficient For pavement design following VDOT’s currently used methodology (AASHTO, 1993) it is useful to use the FWD deflection testing data to develop typical layer coefficients for the emulsion and foamed asphalt FDR materials. Following the process employed by Romanoschi et al. (2004), the layer coefficients were determined. The AASHTO methodology defines the pavement structural number (SN) for a three layer system as the following (assuming the drainage coefficient is equal to one): SN = a1D1 + a2 D2 + a3D3

(2)

where ai = layer coefficient for layer i; Di = thickness of layer i. As the reclaimed pavement consists of a three layer structure (HMA, FDR, existing aggregate base), Equation 2 could be rewritten to solve for the layer coefficient of the FDR layer (a2) by determining the layer thicknesses and the in-place structural number and assuming a value for a1 and a3. VDOT’s current design procedures call for typical HMA and aggregate base layer coefficents of 0.44 and 0.12, respectively (VDOT, 2000). By rearranging, the FDR layer coefficient (a2) can be found as follows (Equation 3): ⎡ SN − 0.44 ∗ D1 − 0.12 ∗ D3 ⎤ a2 = ⎢ eff ⎥ D2 ⎣ ⎦

(3)

The pavement layer thicknesses used in the analysis are shown in Table 2. From this, a layer coefficient for the FDR material was calculated, using the last round of FWD deflection data measured in January 2009, as shown in Table 4. It can be seen that the layer coefficient values in Table 4 compare quite well with previous studies. 4

CONCLUSIONS

The results of this study show an increase in structural capacity of emulsion and foamed asphalt FDR over time based on FWD deflection testing. In addition, the results allowed for the calculation of a structural layer coefficient, derived from FWD testing, for the FDR pavement sections containing different binding agents. Data used in this study suggests initial differences in structural capacity of FDR sections based on binding agent used; however, after 7 months the differences appear to diminish in value. The approach used in this study could be used by other highway agencies looking to adopt FDR technology for pavement rehabilitation. Additional laboratory testing and field monitoring of the projects is recommended. This project has the potential to provide VDOT with the means to assess another option for pavement rehabilitation. As the pavement network continues to age, certain locations will require full-depth repair. The use of FDR is anticipated to give VDOT a viable option for performing needed full-depth repair while reducing costs and delays incurring by using traditional methods. It is expected that the results of this study can be implemented when evaluating future pavement rehabilitation projects. ACKNOWLEDGMENTS The authors acknowledge the assistance of Affan Habib, Trenton Clark, and David Thacker of VDOT’s Materials Division; Michael Wells and William Hughes of VDOT’s Richmond 885

District; David Lee, Allen Williams, and Jeff Wright of VDOT’s Salem District; Richard Ferron of Lanford Brothers Co. Inc.; Mike Marshall, Wirtgen GmbH; Tim Kowalski, Wirtgen America, Inc., and Matthew Kroge, SemMaterials. The authors acknowledge Randy Combs, Ed Deasy, and Linda Evans of VTRC for their assistance with the graphics and editorial process. REFERENCES American Association of State Highway and Transportation Officials. 1993. Guide for design of pavement structures, Washington, DC. Bemanian, S., Polish, P. and Maurer, G. 2006. Cold in-place recycling and full-depth reclamation projects by Nevada Department of Transportation—state of the practice. In Transportation Research Record No. 1949. Transportation Research Board, Washington, DC, pp. 54–71. Berthelot, C., Marjerison, B., Houston, G., McCaig, J., Werrener, S. and Gorlick, R. 2007. Mechanistic comparison of cement- and bituminous-stabilized granular base systems. In Transportation Research Record No. 2026. Transportation Research Board, Washington, DC, pp. 70–80. Dai, S., Skok. G., Westover, T., Labuz, J. and Lukanen, E. 2008. Pavement Rehabilitation Selection. Minnesota Department of Transportation, St. Paul, http://www.cts.umn.edu/Publications/ ResearchReports/pdfdownload.pl?id=874, accessed September 9, 2008. Guthrie, W.S., Brown, A.V. and Eggett, D.L. 2007. Cement stabilization of aggregate base material blended with reclaimed asphalt pavement. In Transportation Research Record No. 2026. Transportation Research Board, Washington, DC, pp. 47–53. Hilbrich, S.L. and Scullion, T. 2008. Evaluation of the laboratory mix-design and field performance of an asphalt emulsion and cement stabilized full-depth reclamation project in Texas. Paper presented at the 87th Annual Meeting of the Transportation Research Board, Washington, DC. Lewis, D.E., Jared, D.M., Torres, H. and Mathews, M. 2006. Georgia’s use of cement-stabilized reclaimed base in full-depth reclamation. In Transportation Research Record No. 1952. Transportation Research Board, Washington, DC, pp. 125–133. Mallick, R.B., Teto, M.R., Kandhal, P.S., Brown, E.R., Bradbury, R.L. and Kearney, E.J. 2002a. Laboratory study of full-depth reclamation mixes. In Transportation Research Record No. 1813. Transportation Research Board, Washington, DC, pp. 103–110. Mallick, R.B., Bonner, D.S., Bradbury, R.L., Andrews, J.O., Kandhal, P.S. and Kearney, E.J. 2002b. Evaluation of performance of full-depth reclamation mixes. In Transportation Research Record No. 1809. Transportation Research Board, Washington, DC, pp. 199–208. Marquis, B., Peabody, D., Mallick, R. and Soucie, T. 2003. Determination of structural layer coefficient for roadway recycling using foamed asphalt. Final Report Submitted to University of New Hampshire, Recycled Materials Resource Center, Project 26, http://www.rmrc.unh.edu/Research/past/P26/ p26final.pdf, accessed June 5, 2008. Maurer, G., Bemanian, S. and Polish, P. 2007. Alternative strategies for rehabilitation of low-volume roads in Nevada. In Transportation Research Record No. 1989. Transportation Research Board, Washington, DC, pp. 309–320. Mohammad, L.N., Abu-Farsakh, M.Y., Wu, Z. and Abadie, C. 2003. Louisiana experience with foamed recycled asphalt pavement base materials. In Transportation Research Record No. 1832. Transportation Research Board, Washington, DC, pp. 17–24. Romanoschi, S.A., Hossain, M., Gisi, A. and Heitzman, M. 2004. Accelerated pavement testing evaluation of the structural contribution of full-depth reclamation material stabilized with foamed asphalt. In Transportation Research Record No. 1896. Transportation Research Board, Washington, DC, pp. 199–207. Saleh, M.F. 2004. New Zealand experience with foam bitumen stabilization. In Transportation Research Record No. 1868. Transportation Research Board, Washington, DC, pp. 40–49. Virginia Department of Transportation, Materials Division. 2000. Guidelines for 1993 AASHTO pavement design. Richmond. Virginia Department of Transportation. 2006. Average Daily Traffic Volumes with Vehicle Classification Data on Interstate, Arterial, and Primary Routes. Richmond. Virginia Department of Transportation, Materials Division, and Cornell University Local Roads Program. 2007. ModTag users manual. Version 4.0. Richmond. Wen, H., Tharaniyil, M.P., Ramme, B. and Krebs, S. 2004. Field performance evaluation of class C fly ash in full-depth reclamation—case study history. In Transportation Research Record No. 1869. Transportation Research Board, Washington, DC, pp. 41–46.

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Structural design systems for new construction & rehabilitation

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A probabilistic approach to flexible aircraft pavement thickness determination G.W. White Fulton Hogan, Brisbane, Australia

ABSTRACT: Whilst most pavement design input parameters are stochastic in nature, pavement thickness design remains deterministic, with the designer responsible for the selection of a single value of each parameter to represents the aggregate of all the variable values over the design life. Whilst pavement thickness design has been proven by field performance over many years to be highly reliable, the actual reliability of the deterministic methods was not known. Through Monte Carlo type simulation and comparison to deterministic analytical values, the reliability of the traditional approach to thickness design of aircraft pavements was demonstrated to be in the order of 92% reliable. Such high reliability resulted from the adoption of the 5 percentile CBR test result for conversion to the design subgrade modulus. If other common CBR value selection methods are used, the reliability changes significantly. The methodology presented could be combined with current mechanistic-empirical design methods to allow routine modeling of thickness design reliability. Significant further improvement in the modeling of pavement thickness reliability could be achieved by investigation and development of more complex models for the various design input parameters. 1

INTRODUCTION

The nature of virtually all inputs to pavement design is stochastic (Hudson, 1975). There will therefore always be variations in subgrade support, pavement materials, pavement thickness, environmental conditions and aircraft traffic. Current aircraft pavement design methods are limited by their deterministic approach (Kunt, 2006). That is, single value, best estimates are made for each design input parameter and a single design output (i.e. pavement thickness) is determined. Reliability is incorporated into the design process by the conservative selection of each input parameter based on the information and data available to the designer. The resulting reliability of the deterministic design thickness is unknown, however, anecdotal evidence and existing pavement performance would suggest that the reliability of aircraft pavement thickness design is generally very high. This paper presents a methodology for reliability based determination of aircraft pavement thickness. This is achieved by the development of a Monte Carlo type simulation for the design thickness of pavements for common commercial aircraft. In order for this to be achieved, an analytical model approximating the output of a deterministic design solution was developed and preliminary probability distributions were adopted for each pavement input parameter. Using the simulation software @RISK, the simulation was performed and the statistical outputs analyzed to determine the reliability in comparison to that expected using the deterministic approach. As the methods are more important than the results, simple models were adopted for the various input parameters and an analytical model was used for the calculation of pavement thickness. 2

RELIABILITY BASED DESIGN

Using a probabilistic approach to design, it is often possible to quantify the design risk or to design for a specified level of reliability (Hudson, 1975). In a probabilistic design method, pavement 889

reliability can be considered as an input to the design process (Lemer and Moavenzadeh, 1971). Such models are commonly developed for a number of reasons, including (Bratley, et al, 1987): • Tractability. Sometimes it is not time or cost effective to create the entire system. This would include the design of a pavement rather than construction and full scale testing. • Training. Sometimes the implications of using the actual system are too great to be considered. Flight simulators and military war games are examples of this. • Black box. Often we are trying to understand what is happening inside a system that is not transparent or not readily understandable, making analytical methods impractical. Monte Carlo type simulations can be used to assess the reliability of pavement thickness design. Monte Carlo simulation is the process of developing a deterministic model and assigning probability distributions to each of the inputs. By generating combinations of inputs that conform to these distributions, a large number of deterministic outputs can be calculated. The distribution of the outputs can be treated as an approximation to the distribution of the outputs from the system. Such simulations have only become practically achievable with the relatively recent increase in computational power of PCs (Ross, 1997). A useful simulation model must simplify and idealise the system that it is trying to replicate (Bratley, et al, 1987). For a model to be useful, given a limited set of descriptors, all its relevant behaviors and properties must be able to be determined in a practical way, usually analytically or numerically (Bratley, et al, 1987). In this paper reliability of the design system is defined to be the probability that the deterministically calculated pavement thickness will equal or exceed that derived from a Monte Carlo type simulation using stochastic input parameters. 3

CURRENT DESIGN PROCEDURES

Current procedures for aircraft pavement thickness design are deterministic. That is, single values are adopted for all input parameters and a model is used to determine a damage indicator for a given pavement composition. That damage indicator could be stress, strain or deflection. These procedures, such as the Australian developed APSDS (Mincad, 2000) are often best fit models which imply a 50% design reliability. Increased reliability is commonly incorporated into design by the conservative selection of the input parameters. By adopting values of input parameters other than the mean or average values, a factor of safety is introduced into the design. These safety factors could be more appropriately termed ‘ignorance factors’ as the change in reliability resulting from the alternate input values is not readily identifiable (Hudson, 1975). For example, it is common practice to adopt the conservative value of subgrade CBR for design purposes. As pavement thickness is very sensitive to CBR, adoption of a conservative CBR value will add a considerable, but unknown, factor of safety to the resulting design thickness. 4

@RISK—ADVANCED RISK ANALYSIS FOR SPREADSHEETS

@RISK allows for advanced risk modeling by Monte Carlo type simulation to be performed in spreadsheets such as Microsoft Excel (Palisade, 2005). By modeling each of the input parameters stochastically, the distribution of the output values can be predicted and then assessed. This allows the variability of each design input parameter to be examined and the reliability of the default or traditional approach to input parameter value selection to be assessed in a scientific manner. To develop a reliability based design methodology using @RISK, the following steps were performed, which are discussed in the following sections: • • • •

Development of analytical model. Input Parameters and their variability. Simulation. Analysis of results. 890

5

DEVELOPMENT OF ANALYTICAL MODEL

An analytical model that expressed pavement thickness as a function of other pavement thickness input parameters was required. Normally, a thickness design tool such as COMFAA (FAA, 2006), APSDS or LEDFAA (FAA, 2004) would be used to determine pavement thicknesses. These packages do not currently provide for interfacing with @RISK. To implement reliability based design into common practice, pavement thickness determination software would need to be modified to allow interfacing with @RISK or other simulation software. For the purposes of demonstrating how such a system could work, an analytical proxy was used in place of a design package. White (2005) investigated sensitivities of aircraft pavement thicknesses to various input parameters using the deterministic tool APSDS. The input parameters considered are detailed in Table 1. The resulting data was utilized to develop an analytical model for pavement thickness for each of the aircraft detailed in Table 2. The resulting analytical models are detailed as Equations 1 to 3 for the B747, B767 and B737 respectively. These were adopted as a proxy to APSDS for this design reliability investigation. TTB747 = 1145–6.65 × SM–0.0349 × W + 5.80 × M–1.24 × TP + 0.00409 × P–0.0318 × AM–0.797 × AT–0.260 × BT (R2 = 81.4%)

(1)

TTB767 = 1038–5.93 × SM–0.0370 × W + 5.67 × M–1.34 × TP + 0.00327 × P–0.0318 × AM–0.813 × AT–0.225 × BT (R2 = 80.2%)

(2)

TTB737 = 837–4.62 × SM–0.0321 × W + 4.61 × M–0.564 × TP + 0.00309 × P–0.0264 × AM–0.698 × AT–0.210 × BT (R2 = 88.7%)

(3)

where: TTXXX = Total Thickness of pavement for aircraft XXX. SM = Subgrade Modulus (MPa). W = Aircraft Wander (mm). M = Aircraft Mass (% of maximum). TP = Tyre Pressure (% of standard). P = Aircraft Passes (number). AM = Asphalt Modulus (MPa). AT = Asphalt Thickness (mm). BT = Base Thickness (mm). 6

INPUT PARAMETERS AND THEIR VARIABILITY

In order to develop a Monte Carlo simulation model, each of the input parameters in each of Equations 1 to 3 was expressed as a stochastic variable with a distribution function assigned. This was the greatest challenge for conducting meaningful simulation work. While there exists an opportunity to refine and improve these models, the initial models detailed in Table 3 were Table 1.

Design input parameters.

Design input parameter

Units

Values

Subgrade Modulus (SM) Aircraft Wander (W) Aircraft Mass (M) Tyre Pressure (TP) Aircraft Passes (P) Asphalt Modulus (AM) Asphalt Thickness (AT) Base Thickness (BT)

MPa mm % of maximum % of standard Number MPa mm mm

30, 60, 100, 150 200, 800, 1400, 2000 60, 80, 100 80, 90, 100 5000, 10000, 20000 1000, 2000, 3000 20, 40, 100 100, 300, 500

891

Table 3.

Table 2.

Aircraft details.

Aircraft

Maximum mass (t)

Standard tyre pressure (kPa)

B747-400

397

1380

B767-300

180

1240

B737-800

79

1360

Input values and distributions.

Parameter

Deterministic value

Mean Std Dev Distribution Limits

Subgrade Modulus Aircraft Wander Aircraft Mass Tyre Pressure Aircraft Passes Asphalt Modulus Asphalt Thickness Base Thickness

60 12 775 80 100 10000 2000 40 200

Normal

40.2 (5%-ile value) Fixed value N/A 775 User defined Min 60 Max 100 80 Uniform Min 80 Max 100 100 Normal Min 1000 Max 100,000 15000 Normal Min 500 Max 3000 1500 Pareto Min 40 Max 70 40 Pareto Min 200 Max 300 200

N/A N/A N/A 1000 500 N/A N/A

Min 30 Max 150

0.40

0.35

0.30

Frequency

0.25

0.20

0.15

0.10

0.05

0.00 50

Figure 1.

60

70

80 % of Maximum Mass

90

100

110

Aircraft mass distribution.

assigned to each of the input parameters. Table 3 also details the deterministic values that would typically be assigned by a pavement designer based on the distribution shown. Aircraft Mass was modeled with a user defined distribution which is shown in Figure 1. This distribution has been determined based on experience from real-life aircraft pavement designs. It could be further refined based on statistical data from airlines in the future. 7

SIMULATION

The simulation was performed using the software @RISK. All inputs and outputs were entered into an Excel spreadsheet and the following parameters were used for the simulation: 892

Table 4.

Monte Carlo analysis statistics.

Statistic

B747

B767

B737

Minimum Maximum Mean Std Dev

570 1285 970 95

515 1174 885 90

470 995 765 70

100% 90%

Cumulative Frequiency (%)

80% 70% 60% 50% 40% 30% 20% 10% 0% 500

600

700

800 900 Pavement Thickness (mm) B747

Figure 2.

B767

1000

1100

1200

B737

Pavement thickness cumulative frequency by aircraft.

• Latin Hypercube sampling. • 100,000 iterations. Summary statistics for the resulting distributions of pavement thickness are presented in Table 4. Figure 2 shows the distribution of calculated pavement thicknesses for the three aircraft. Pavement thicknesses were considered to follow an approximately normal distribution. The traditional single thickness solution was also calculated using the deterministic values for each input parameter detailed in Table 3. The traditional pavement thicknesses calculated were: • B747. 1120 mm. • B767. 1015 mm. • B737. 876 mm. 8

ANALYSES OF RESULTS

The 95 percentile design thickness obtained from the Monte Carlo type simulation for the B747 was 1129 mm. This is slightly higher than the deterministic value of 1120 mm. The deterministic value of 1120 mm represents the 91 percentile value obtained from the simulation analysis. The deterministic approach is therefore considered to result in a 91% reliable design thickness. That is, 91% of the time, the deterministically derived pavement thickness will equal or exceed that predicted by the Monte Carlo type simulation. The equivalent statistics for the B767 and B737 are shown in Table 5. From Table 5 it can be seen the deterministic approach to pavement thickness calculation results in around 91–95% design reliability. This is considered to be consistent with field per893

Table 5.

Table 6. B747.

Pavement thickness reliabilities.

Statistic

B747

B767

B737

95%-ile thickness Deterministic thickness Deterministic reliability

1129 mm 1120 mm 91%

1030 mm 1015 mm 92%

881 mm 876 mm 92%

Alternate subgrade reliability for

Statistic Design CBR modulus Deterministic thickness Deterministic reliability

Lowest test result

Mean of test results

45

60

1088

989

88%

56%

Table 8.

Table 7. Alternate subgrade reliability for B767. Statistic Design CBR modulus Deterministic thickness Deterministic reliability

Lowest test result

Mean of test results

45

60

986

897

87%

54%

Alternate subgrade reliability for B737.

Statistic

Lowest test result

Mean of test results

Design CBR modulus Deterministic thickness Deterministic reliability

45 853 88%

60 784 59%

formance of aircraft pavements over many years where relatively few structural failures that can be attributed to pavement thickness design have been found. The high reliability of the deterministic pavement thicknesses results from the selection of the 5 percentile value for the subgrade modulus, to which pavement thickness has been shown to be most sensitive (White, 2005). Whilst some design guidelines suggest that the 5 percentile value of the CBR test results should be adopted for conversion to the design subgrade modulus, this is not always used in practice and in many circumstances there is inadequate test data to reliably determine a 5 percentile value. In these cases, the minimum value obtained from testing or the average soaked CBR may be used instead. Table 6 details alternate design subgrade moduli that may be reasonably selected from the same set of test data and demonstrates its effect on the deterministic pavement thickness and associated reliability. All design subgrade modulus values in Table 6 were derived from fictitious data that had a mean of 60 and standard deviation of 12, as adopted for the original deterministic and simulation analyses. Table 6 shows that selecting the lowest test result, from the fictitious data provided, results in a slight reduction in design reliability to just under 90%. By selecting the average CBR test result, the reliability dropped to just above 50%, which is not considered acceptable. This confirms the importance of appropriate and conservative selection of design subgrade CBR in achieving reliable deterministic pavement thicknesses. Table 7 and Table 8 shows the same information for the B767 and B737 aircraft with the same trends. 9

CONCLUSIONS

Whilst most pavement design input parameters are stochastic in nature, pavement thickness design remains deterministic, with the designer responsible for the selection of a single value 894

for each parameter, intended to represent the aggregate of all the variable values over the design life. Whilst pavement thickness design has been proven by field performance over many years to be highly reliable, the actual reliability of the deterministic methods was not known. Through Monte Carlo type simulation and comparison to deterministic analytical values, the design reliability of the traditional approach for aircraft pavements was demonstrated to be in the order of 92%. Such high reliability resulted from the adoption of the 5 percentile CBR test result for conversion to the design subgrade modulus. If other common CBR value selection methods are used, the reliability is affected significantly. Great improvement in the reliability based design of aircraft pavements could be achieved by utilizing the actual design software or an artificial neural network to calculate the pavement thicknesses rather than simple analytical models. Such improvement would require an interface between the pavement thickness design tool and the Monte Carlo simulation tool. Substantial improvement in the understanding of pavement thickness reliability could also be obtained by adopting more complex models, derived from statistical data, for the various input parameters. For example, asphalt modulus is known to be affected by mix type, binder type and atmospheric temperature, all of which could be incorporated into a reliability based design tool. ACKNOWLEDGMENT Greg White would like to thank his employer, Fulton Hogan, for supporting the preparation of this paper and attendance at this conference. REFERENCES Bratley, P., Fox, B.L. and Schrage, L.E. (1987). A Guide to Simulation. Springer-Verlag. 2nd Edition. USA. FAA. (2004). Computer Program LEDFAA Help file. Version 1.3. Federal Aviation Administration. William J. Hughes Technical Centre. Atlantic City. June. Available from www.airporttech.tc.faa. gov/naptf. FAA. (2006). Computer Program COMFAA Help file. Version 11/2006. Federal Aviation Administration. William J. Hughes Technical Centre. Atlantic City. Available from www.airporttech.tc.faa. gov/naptf. Hudson, W.R. (1975). State-of-the-Art in Predicting Pavement Reliability from Input Variability. Contract Report S75-7. US Army Corps of Engineers. Waterways Experiment Station, Vicksburg, USA. August. Kunt, M.M. (2006). ‘Probabilistic modifications of FAA Rigid Pavement Design Procedure. Proceedings 2006 Airfield and Highway Pavements Specialty Conference. American Society of Civil Engineers. Atlanta, United States of America. 1–3 May. Lemer, A.C. and Moavenzadeh, F. (1971). ‘Reliability of Highway Pavements’. Proceedings 50th Annual Meeting of the Highway Research Board. Department of Civil Engineer. Massachusetts Institute of Technology. Mincad. (2000). APSDS 4 Users’ Manual. Mincad Systems Pty Ltd. Richmond. Australia. September. Palisade. (2005). @RISK Professional User Manual. USA. Ross, S.M. (1997). Simulation. Academic Press. 2nd Edition. USA. White, G. (2005). ‘A Sensitivity Analysis of APSDS, an Australian Mechanistic Design Tool for Flexible Aircraft Pavement Thickness Determination’. Proceedings First European Aircraft Pavement Workshop. The National Information and Technology Platform for Infrastructure, Traffic, Transport and Public Space (CROW). Amsterdam, Netherlands. 11–12 May.

895

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Comparison of design thickness between the 1993 AASHTO Guide and MEPDG for full depth reclamation pavement Y. Ji & T.E. Nantung Indiana Department of Transportation, W. Lafayette, Indiana, USA

ABSTRACT: A research project was initiated by Indiana Department of Transportation to estimate the structural contribution and feasibility of Full Depth Reclamation (FDR) bases for pavement structure under a low-medium volume traffic loading. Falling Weight Deflectometer (FWD) tests were conducted and the layer moduli were backcalculated on different construction phases: the surface of existing Hot Mix Asphalt (HMA) pavement, the FDR base, the new HMA final surface, and the nine months’ traffic opening, respectively, for a total of four times. The results indicate the promise of this recycled base material in pavement construction compared to traditional granular base. In addition, this paper discusses how the lab test results relate to the expected performance in a pavement structure by the MEPDG software and its parameter effects. Research indicated the MEPDG provided comparable thickness to the 1993 AASHTO Guide if the failure criteria are set up reasonably. Therefore, the MEPDG could be used as a design tool to estimate layer thickness for FDR pavement with a low-medium traffic volume. 1

INTRODUCTION

Rehabilitation strategies such as milling and filling or simply overlaying worn-out pavements can lead to premature failures due to weak bases or reflective cracking. On the other hand, Full Depth Reclamation (FDR) has been proposed as an alternative in road construction (Asphalt Institute, 2007). This process makes roads better by combining the old asphalt surface materials with the underlying base to produce a rejuvenated road base that is stronger than new aggregate. The process is performed entirely on site, so the costs of removing, hauling away, and disposing of the old pavement are eliminated. Therefore, FDR has been a technique widely used by DOT, city, and county agencies. A research project was initiated by Indiana Department of Transportation (INDOT) to estimate the structural contribution and feasibility of the FDR bases for a low-medium volume typical pavement structure. Falling Weight Deflectometer (FWD) tests were conducted on the different construction phases. Several lab tests have been performed in order to quantify and verify the design thickness. Currently, INDOT is moving from the practice of the empirical design guide (AASHTO, 1993) toward the implementation of the M-E design guide (NCHRP, 2004). This new Mechanistic-Empirical Pavement Design Guide (MEPDG) developed under the National Cooperative Highway Research Program (NCHRP) Project 1-37A is a new pavement design method using a hierarchal approach; different levels of analysis are available depending upon desired reliability and available information. Although an empirical approach provided pavement design thickness in this engineering practice, it is still necessary to establish a comparison between empirical and MEPDG procedures. Such a comparison should highlight the difference between these two significant procedures. This difference is to be quantified in terms of HMA thickness, PG grade, and materials.

897

2

GENERAL CONCEPT OF SELECTED DESIGN APPROACHES

2.1 1993 AASHTO design guide-limitation The 1993 AASHTO Guide is typically used by agencies to design the thickness of pavement layers nationwide. This guide explains the empirical method based on field performance data measured at the AASHO road test in 1958–60. Today, traffic level and load spectrum has increased and changed tremendously. These changes include truck suspension, axle configurations, and tire types and pressures. Moreover, a significant amount of distress at the original AASHO road occurred in the pavement during the spring thaw. This condition does not exist in a large part of the country. Lastly, other important factors, including surface materials, base and subgrade materials, drainage, different pavement construction area, etc., have not been considered accurately in this empirical design method. 2.2 Mechanistic-Empirical Pavement Design Guide The National Cooperative Highway Research Program (NCHRP) initiated project 1-37A to develop a new pavement design guide for new and rehabilitated pavements based on a mechanistic empirical (M-E) approach (NCHRP, 2004). The resulting M-E Design Guide is accompanied with software that enables the design of both new and rehabilitated sections of flexible and rigid pavements. The researchers developed a greatly expanded capacity for describing the details of each axle configuration in the design traffic mixture and for accounting for the moisture and temperature impacts on the material properties. As INDOT moves the empirical design procedures towards the implementation of the M-E Design Guide, the need has risen for an evaluation of the incorporated design procedures and consideration of practical steps necessary for its proper implementation. More research is planned to improve these basic components and increase the flexibility of the new MEPDG for handling innovative materials. The work described in this paper is an example of how the MEPDG could be used in the future to incorporate a different type of layer, such as FDR made with emulsion and Portland cement, within the pavement cross section. Sensitivity runs were conducted by changing the design levels and input parameters of the base design case to input ranges typically used and experienced in Indiana. The results of this study will help determine the extent to which the various Design Levels and inputs need to be incorporated and further evaluated during INDOT’s implementation plan. Three levels are provided for the design inputs in our implementation plan recommended by NCHRP. 3

FDR CONSTRUCTION

3.1 Pavement condition and sampling For any rehabilitation project, a thorough pre-project evaluation and sound engineering practice are the keys to successfully achieving the desired results. FDR is recommended for pavement structures that lack capacity or integrity, including pavements with base or subgrade problems. Therefore, FDR provides a long-term pavement rehabilitation option for a deteriorated roadway at the end of its service life. An existing pavement condition survey was performed to determine the type of pavement distress and deterioration that had occurred. The second purpose of the survey is to study the in-situ pavement section. The thickness of the asphalt pavement and type and properties of underlying material must be known. Coring operations were performed to confirm the structural data. The FWD testing was conducted for estimating in-situ subgrade. In the field survey, pavements have experienced base failure, stripping, rutting, and fatigue cracking, indicating that FDR rehabilitation may be required. 3.2 Construction Design Identification Number 0710070 for the FDR pavement was constructed on SR-1 from 2.62 miles of Junction SR-32 to 0.5 miles south of Junction SR-32, Randolph County, 898

Greenfield district, Indiana. This asphalt structural section and a predetermined amount of underlying materials are pulverized and treated to produce an 8-inch stabilized base course. The full depth reclamation of pavement began on August 27th, 2007. First, linear grading was completed on both sides of the existing pavement prior to the pulverization process to widen the road from its original width to the new width of 25 feet. The existing asphalt and base was pre-pulverized to a depth of 11 inches using a Wirtgen 2500 reclaimer/ stabilizer. The pre-pulverized material was then graded to fill the road widening trench. Next, the project procedure included full depth reclamation. During this process, the pulverized pavement materials were treated with the design admixtures. The asphalt emulsion is transported to the road construction site by a transport truck. The transport truck fed the emulsion to the road in a Wirtgen 2000 reclaimer/stabilizer. The reclaimer pumped the emulsion from the delivery truck and metered the emulsion through a spray bar with nozzles into the mixing chamber. The emulsion spray rate was proportioned to the forward speed of the reclaimer. The application rate of emulsion and Portland cement was 1.3 gals/yd2, 3%, respectively. The amount of cement being placed was verified using a one square yard canvas and scale. Third, the surface of the treated material was moisture conditioned prior to the initial breakdown compaction using a Hamm vibratory padfoot roller. Once the material was initially compacted, a grader established profile in the treated section. Final compaction of the material was completed using a Hamm HD-120 vibratory double-drum roller, first in the vibratory mode, and finally in the static mode. Several applications of water were distributed, as needed, on the surface of the treated mat during the final compaction process. The reclamation was completed on August 29th, 2007. This final product of the road reclaimer and rolling process serves as a uniform stable foundation for a suitable wearing course. This newly constructed base layer is typically allowed to be open to traffic on the same day. Once the curing period was completed, the final surface was placed on September 4th, 2007. It should be noted that the reclaimed based course should be allowed to cure for at least 5 days after proper compaction. 4

FWD TESTING AND BACKCALCULATION

The objectives of the FWD tests are to: (1) obtain in-situ moduli of existing asphalt and subgrade; (2) obtain in-situ CBR of chemically treated FDR base layers; (3) compare CBR values with those of different cement treated FDR bases; (4) estimate the benefits of FDR pavement; and (5) provide reliable information for input of the 1993 AASHTO design and M-E design guides. FWD tests are conducted at about 100 meter intervals along a 4,000-meter long segment at this site. A pulse force is generated from a loading plate with the shape of a half-sine wave and a peak force of approximately 9,000 lbs. The radius of the loading plate is 5.9 inches. Nine geophone sensors are used to obtain the deflection basin curve on the pavement. The sensors are positioned aligned with the center of the loading plate. A Dynatest model 8000 is used for FWD tests, and the data processing code, ELMOD5, developed by Dynatest, is used for backcalculation of FWD deflection data. During the research project, FWD tests were conducted on the different construction phases: the surface of existing HMA pavement, the FDR base layer, the HMA final surface, and the nine months’ traffic opening, respectively, for a total of four times. The FWD testing sequence consisted of one drop at 7,000 lbs load level followed by a drop at 9,000 lbs load level and 11,000 lbs load level. The eight geophones were placed at 0, 8, 12, 18, 24, 36, 48, and 60 inches from the center of the FWD loading plate. The deflections recorded for the 9,000 lb-load level were used to backcalculate the elastic moduli of the pavement layers. 5

RESULTS AND DISSCUSION

5.1 Pavement condition and sampling Currently, there is no standard method for determining layer coefficients. Several methods have been used to determine layer coefficients for certain paving materials (Hossain, 1997 899

and Poloruto, 2001). In this study, the AASHTO Design Method and the Equal Mechanistic Approach were followed to determine the structural layer coefficient of the FDR base materials. In both approaches, AASHTO provides the following general equation for Structural Number (SN) reflecting relative structural contribution (using coefficients (ai) and thickness (Di)) and assuming no effect of drainage (Huang, 1993): SN = a1D1 + a2 D2 + a3D3

(1)

Considering that the FDR pavement structures in this study had only two layers on top of the subgrade soil, assuming that the HMA layer has a thickness of h1 = 4 inches, and a typical structural layer coefficient for the HMA is 0.44, the structural layer coefficient for the FDR base layer material can be computed as: a2 = (SNeff − a1D1 )/D2

(2)

where a2 = the layer coefficient for the FDR base layer material; SNeff = the effective structural number; and D2 = the thickness of the FDR base layer, in inches The deflections used in the calculations for the base layer structural coefficients are those measured corresponding to the last drop at the 9,000 lbs load level, on September 19th, 2007 and June 2nd, 2008, respectively. Figure 1shows the FDR layer coefficients versus the reference points. Table 1 summarizes statistic of layer coefficient for the FDR base. In the northbound section, it was found that with a 95% Confidence Interval (CI) level, the FDR Layer Coefficient (LC) values were from 0.16 to 0.22, with an average value of 0.19 in 2007. In 2008, the LC values were from 0.21 to 0.26 with an average value of 0.23. In the southbound lane, however, the FDR LC values were from 0.19 to 0.25 with an average value of 0.22 in 2007, from 0.25 to 0.30 with an average value of 0.28 in 2008, respectively. The average value of the layer coefficient for the FDR has increased since it was built. Then the overall average computed for two bounds with FDR material was 0.21 in 2007, 0.25 in 2008, respectively. The P values for both directions were less than 0.05, which means the values between 2007 and 2008 were significantly different statistically. This indicates that after nine months of curing, the stabilization improved structure capacity, and the layer coefficients increased significantly. Thus, a recommended structural layer coefficient for FDR base material is 0.25. Considering the layer coefficient for the traditional gravel base is 0.14 in the AASHTO design, FDR provides a 75 percent stronger base than do gravel materials.

South Bound 0.5

0.4

0.4

Layer Coefficients

Layer Coefficients

North Bound 0.5

0.3 0.2 0.1

0.3 0.2 0.1

0 82.0

0

82.5

83.0

83.5

84.0

84.5

82.0

Reference Points 2007

Figure 1.

82.5

83.0

83.5

Reference Points

2008

2007

Comparison for layer coefficients for FDR base.

900

2008

84.0

84.5

Table 1.

Summary statistic of layer coefficients at SR-1. North bound

Year Mean Standard Deviation Interval Lower Limit with CI 95% Interval Upper Limit with CI 95% P(Z ≤ = z) two-tail

Figure 2.

2007 0.19 0.083 0.16 0.22 0.02

South bound 2008 0.23 0.076 0.21 0.26

2007 0.22 0.081 0.19 0.25 0.01

2008 0.28 0.080 0.25 0.30

HMA surface and FDR base thickness based upon 1993 AASHTO.

5.2 Results and input of the 1993 AASHTO The thickness of the FDR pavement depends on the structural pavement design. The following inputs are required for designing an FDR pavement using the DARWIN 3.1 software developed by ARA that is incorporated with the current AASHTO Design Guide: the subgrade resilient modulus, the traffic count in terms of ESALs, the initial and terminal serviceability indices (PSI), the reliability level, and the overall standard deviation of the design. The output of the design procedure is an SN capable of carrying the traffic at the reliability level selected. The analysis used a design life of 20 years, an initial serviceability of 4.5, a terminal serviceability of 2.5, the structural coefficient used for HMA is 0.44, 0.25 for FDR, respectively. The allowable design ESAL is 1,000,000. Once moduli for subgarde and base layers have been determined, either from in-situ FWD testing or lab testing, the thickness of each layer can be calculated using this software. Figure 2 depicts design thicknesses for HMA and base layers under the input proposed. This shows that the modulus is the key factor in the thickness design of asphalt pavement. The reliability level in this empirical method also has an influence on the determination of thickness, but the difference of HMA thickness is in the range of around half an inch. On the basis of all considerations and specifications from INDOT, the resulting design procedure requires 4 inches of HMA over 8 inches of FDR over a lean clay subgrade. 5.3 Results and input of the MEPDG 5.3.1 General input Performance parameters calculated for each of the sections included: • • • •

International Roughness Index (IRI) Fatigue cracking (bottom up and top down) Thermal and transverse cracking Rutting (total and HMA layer). 901

The pavement design was made for a service life of 20 years as a new flexible pavement specified by INDOT. The software values were set up as follows: AC Top Down Cracking (ft/mile) is 2000, AC Alligator Cracking (%) is 35, AC Thermal Fracture (ft/mile) is 700, Permanent total Deformation (in) is 0.65, and Permanent Deformation for AC Only (in) is 0.25. The values for initial and terminal IRI were 70 and 200, respectively. A reliability level was set up at 90%. Summer months were used for pavement construction and traffic open days. 5.3.2 Traffic input The characterization and modeling of traffic loading and volume is one of the key components of pavement design procedures. Traffic characterization in the previous versions of the AASHTO Guide was based on the concept of an ESAL. This value represents the amount of damage caused by a standard 80 kN single axle load on a pavement. The new design procedure uses a more detailed approach to characterize traffic loading and evaluates pavement damage based on a combination of traffic volumes, axle type, spacing, speed, and weight. In this study, traffic input parameters were expected to reflect the real traffic conditions in the Indiana locations. Therefore, the monthly adjustment factors (fixed input parameter) and the vehicle class distributions were obtained from the reference (Li, 2005). The design section is typical of a low to medium traffic volume 2-lane State Route. The AADT (average annual daily traffic) is 5,000 with 4% trucks thus yielding a two-way AADTT (average annual daily truck traffic) of 200, with a traffic growth of 4% (INDOT, 2005). 5.3.3 Climate input The MEPDG allows climate input parameters for the pavement design locations to be generated by choosing climate data from a specific weather station or by interpolating the climate data from the surrounding locations. Due to the lack of climate data around this pavement section, the climate database for the cities of Indianapolis, Indiana (Indianapolis International Airport) was used. 5.3.4 AC layer properties input The |G*| and δ needed for Level 1 and 2 analyses were obtained from Dynamic Shear Rheometer tests on representative binders. Table 2 shows the relationship between G* and phase angle of the binders, whose values will be input into the MEPDG. As observed from the table, G* and phase angle are highly correlated with frequency in each temperature. The complex modulus (E*) procedure is given by the AASHTO standard tests specification TP 62 (AASHTO, 2007). Theses master curves are needed for Level 1 analysis. In this study, the Complex modulus (E*) for the design run was obtained from the Joint Transportation Research Program (JTRP) project SPR-2813 (Llenin et al., 2004). The mixture is a 9.55 mm and a SBS modified PG 76-22 binder. Tests were performed under five different temperature levels: –10, 4.4, 21.1, 37.8 and 54.4°C, and six frequencies.

Table 2.

Complex shear modulus G* and δ for Level 1 and Level 2.

Temp., °C

Hz

|G*|, MPa

δ, deg

Temp., °C

Hz

|G*|, MPa

δ, deg

20 20 20 20 20 20 37.2 37.2 37.2

25 10 5 1 0.5 0.1 25 10 5

4.2829 3.8265 3.3779 2.2515 1.6011 0.6756 1.4081 0.7353 0.4453

13.45 16.15 21.11 35.15 43.94 58 55.45 62.51 66.79

37.2 37.2 37.2 54.4 54.4 54.4 54.4 54.4 54.4

1 0.5 0.1 25 10 5 1 0.5 0.1

0.1352 0.0749 0.0195 0.1318 0.0603 0.0327 0.0076 0.004 0.0009

73.1 75.39 79.9 79.35 79.98 81.07 83.7 85.08 87.2

902

5.4 Results and inputs of the MEPDG The MEPDG software requires substantially more input information than needed by the empirical design procedure in the 1993 AASHTO Guide. Therefore, the MEPDG provided numerous charts and tables as outputs. Due to space constraints, it is difficult to present a full discussion of all the investigated input parameters in this paper. For this reason, one configuration consisting of an HMA layer with 4 inches placed on 8 inches FDR under the 90% reliability was selected as an example to compare with the results of the 1993 AASHTO Design Guide. Figures 3, 4, and 5 show the amount of IRI, alligator cracking, rutting, and thermal cracking in the asphalt layer in different hierarchical input levels. The distresses predicted by the MEPDG software for a typical application after 20 years of service were in good shape in IRI and fatigue cracking. As expected, there was no significant difference in predicted thermal transverse cracking affected by the modulus from base and subgrade because this is a top down distress, and the asphalt concrete surface was the same for all cases. Nonetheless, other performance values, such as IRI, rutting, and alligator cracking, were influenced by the modulus of base and subgrade. In these three distresses, rutting in most cases is surpassing the criteria of 0.65. With the expectation of the subgrade (SG) modulus, the weak subgrade creates the higher rutting in all three levels. The amount of rutting decreases with increasing layer moduli. The same trends are observed for alligator cracking and IRI. It is highly likely that the modulus have a great influence on these distresses. In the hierarchical design input level, the Level 3 results are slightly less than Level 2, and the Level 2 results are slightly less than Level 1. This indicates that the Level 1 must provide the greater thickness if Level 1 is required to meet the same results as the Level 2. Level 1, therefore, provides a more conservative design than does Level 2; the same conclusion can be made in Level 2 over Level 3 in reliability level. As far as design thickness is concerned, pavement consisting of 4 inch HMA, 8 inches base with the modulus of 50 ksi, and the modulus of 6 ksi subgrade can meet the current AASHTO requirements. On the other hand, MEPDG requires both combination of stiffness

150

1.5

IRI (in./mile)

AC (%)

2

1 0.5 0

SG 4 ksi

60 80 Base Modulus (ksi) SG 6 ksi

SG 8 ksi

100

40

SG 10 ksi

SG 4 ksi

60 80 Base Modulus (ksi) SG 6 ksi

SG 8 ksi

100

SG 10 ksi

2

1 0.9 0.8 0.7 0.6 0.5 0.4

Rutting (in.)

Rutting (in.)

120 110 100

40

1.5 1 0.5 0

40 SG 4 ksi

Figure 3.

140 130

60 80 100 Base Modulus (ksi) SG 6 ksi SG 8 ksi SG 10 ksi

40 SG 4 ksi

Effect of modulus on mechanical distress (Level 3).

903

60 80 100 Base Modulus (ksi) SG 6 ksi SG 8 ksi SG 10 ksi

150 IRI (in./mile)

AC (%)

8 6 4 2

140 130 120 110 100

0 40

80

60

100

40

60

SG 6 ksi

SG 8 ksi

SG 4 ksi

SG 10 ksi

SG 6 ksi

SG 4 ksi

60

80

3 2 1

100

40

60

SG 8 ksi

80

100

Base Modulus (ksi) SG 4 ksi

SG 10 ksi

SG 6 ksi

SG 8 ksi

SG 10 ksi

Effect of modulus on mechanical distress (Level 2).

10 8 6 4 2 0

150 140 130 120 110 100

IRI (in./mile)

AC (%)

SG 6 ksi

40

60

80

100

40

Base Modulus (ksi) SG 4 ksi

SG 6 ksi

SG 8 ksi

60

80

100

Base Modulus (ksi) SG 10 ksi

SG 4 ksi

SG 6 ksi

SG 8 ksi

SG 10 ksi

5

1 0.9 0.8 0.7 0.6 0.5 0.4

TC (ft./mile)

Rutting (in.)

SG 10 ksi

4

Base Modulus (ksi)

4 3 2 1 0

40

60

80

100

40

Base Modulus (ksi)

SG 4 ksi Figure 5.

SG 8 ksi

0 40

Figure 4.

100

5

1 0.9 0.8 0.7 0.6 0.5 0.4

TC (ft./mile)

Rutting (in.)

SG 4 ksi

80

Base Modulus (ksi)

Base Modulus (ksi)

SG 6 ksi

SG 8 ksi

60

80

100

Base Modulus (ksi) SG 10 ksi

SG 4 ksi

SG 6 ksi

SG 8 ksi

SG 10 ksi

Effect of modulus on mechanical distress (Level 1).

of 6 ksi for subgrade and 100 ksi for base under the criteria of 0.65 inches in rutting. If this failure threshold was changed to 0.75 inches, it only required 4 inch HMA, an 8-inch base with 40 ksi; a subgrade with 6 ksi. 904

Keeping in mind the uncertainty associated with the projection of design traffic and estimation of pavement performance criteria and pavement material and local climates, it is suggested that MEPDG could be used as a design tool to estimate layer thickness for FDR pavement with a low-medium traffic volume if criteria were set up reasonably. Nonetheless, AASHTO procedures should still be considered as a useful alternative method of design in the engineering practice.

6

CONCLUSIONS

The mechanistic-empirical design method provides a performance based design on a more advanced basis of science and engineering than methods that are purely empirical or experience based. Mechanistic-empirical design methods represent a particularly strong and comprehensive analysis tool in this regard. However, time and resources are needed to accomplish a rational and accurate design and analysis using the M-E Design Guide. These steps and processes include calibration and validation requirements, implementation guidelines, commitment of resources, equipment, training, input data requirements and balancing complexity/comprehensiveness with understandability and practicality. This paper presented the comparison of designing FDR pavement thickness using the DARWIN 3.1 and Version 1.003 MEPDG software. Limited runs for two methods were conducted varying AC thickness and modulus for base and subgrade. From the results presented, the following conclusions can be made: • FDR is a uniform material that can be placed and compacted easily, and it produces a rejuvenated road base that is stronger than the new aggregate base. This stabilization layer also gains stiffness over time. • The effective structural number computed from the FWD deflections measured on the as-constructed pavements suggested a structural layer coefficient of 0.25 for the asphalt stabilized FDR base material. • Level 1, the highest level in the design process, requires too many parameters and could cause a mismatch between lab test binder and in-situ properties, while it provided least conservative results for the pavement examined. • The difference between Level 2 and Level 3 is negligible in this study. This may be due to the accurate matched input to these two hierarchal levels. Therefore, the design will likely be implemented at the design input Level 2. However, in determining the sensitive design inputs, it was found that some combinations of design input levels yielded more rational results rather than setting all Level 2 design inputs. • The M-E design guide has compatible results to the 1993 AASHTO guide, therefore, it could be used as a design tool to estimate thickness for FDR pavement with low-medium traffic volume if failure criteria were set up reasonably; but the AASHTO procedure would still be considered a useful alternative method of design in the engineering practice.

REFERENCES American Association of State Highway and Transportation Officials. 2007. Standard Method of Test for determining Dynamic Modulus of Hot-Mix Asphalt (HMA), TP 62–07. American Association of State Highway and Transportation Officials. 1993. Guide for Design of Pavement Structures. Washington, D.C. Asphalt Institute. 2007. The Asphalt Handbook. 7th edition. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. 2004. www.trb. org/mepdg. National Cooperative Highway Research Program, Transportation Research Board, Washington, D.C. Hossain, M., Habib, A. and Latorella, T.M. 1997. Structural Layer Coefficients of Crumb RubberModified Asphalt Concrete Mixtures. Journal of the Transportation Research Board 1583: 62–70. Huang, Y.H. 1993. Pavement Analysis and Design. New Jersey: Prentice Hall. Indiana Department of Transportation. 2005. Road Design Manual Indianapolis.

905

Li, S., Nantung, T. and Jiang, Y. 2005. Assessing Issues, Technologies, and Data Needs to meet Traffic Input Requirements by Mechanistic-Empirical Pavement Design Guide: Implementation Initiatives. Journal of the Transportation Research Board 1917: 141–148. Llenin, A.J. and Pellinen, T.K. 2004. Validation of NCAT structural Test Track Experiment Using INDOT APT Facility, Interim Draft Final Report, Joint Transportation Research Program, SPR 2813 Project, Purdue University. Poloruto, M. 2001. Procedure for use of Falling Weight Deflectometer to determine AASHTO Layer Coefficients. Journal of the Transportation Research Board 1764: 11–19.

906

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Dynamic response of rigid pavements under moving traffic loads with variable velocities Y. Zhong & L. Geng School of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian, Liaoning, China

ABSTRACT: In this paper, the dynamic response of an infinite plate resting on an elastic foundation subjected to moving traffic load with variable velocity (accelerating or decelerating) is investigated by using a triple Fourier transform in time and space. The effects of the load varying velocity, acceleration and deceleration, are discussed respectively. The numerical results indicate that the main affecting parameters are initial velocity, acceleration or deceleration. Numerical examples are presented to compare the results of static analysis and those of dynamic analysis with a constant, varying velocity. The results show that the dynamic response of rigid pavement under a moving traffic load with variable velocity is not only different from that caused by static load, but also different from that generated by load with a constant moving speed. Displacement of the plate is reduced with increasing the varying velocity and acceleration. But, plate stresses increase with the varying velocity at a given acceleration. Both the velocity and acceleration of a moving vehicle should be considered in the analysis of rigid pavements. 1

INTRODUCTION

In the analysis of highway and airport pavements, a rigid pavement structure is usually regarded as a plate resting on an elastic foundation, which is often modeled as a Winkler foundation. In general, the loads exerted on the plate are moving traffic loads such as wheel loads from moving vehicles and from airplanes. When a vehicle accelerates or decelerates or a plane takes off or lands, the loads applied to the plate structure are moving loads with acceleration or deceleration. Therefore, the investigation of dynamic response of the plate resting on an elastic foundation subjected to moving traffic loads is interesting and important, as the results can be applied to understand the dynamic behavior of highway and airport pavements. Many research findings have appeared in the literature on the dynamic response of a beam resting on a foundation subjected to moving loads and free vibration of plates. In comparison, plates on an elastic foundation subjected to moving loads have only attracted the attention of a few researchers. Sun et al. (2005) studied the effects of initial stress on the dynamic response of an infinite long and simply supported composite plate under cylindrical bending using the model superposition approach. Huang (2002) used the finite element method to study the dynamic response under moving loads. Vallabhan (1991) discussed the dynamic behavior of a beam and a rectangular plate under moving loads, paying more attention to moving mass. Thambiratnam (1996) investigated the dynamic response of a rectangular plate with stepped thickness subjected to moving loads, including moving mass. Existing research on dynamic analysis of plates on elastic foundations pertains to analytical models with simple and regular boundary conditions. Gbadeyan & Oni (1992) gave a closed-form solution by using double Fourier sine integral transformation to analyze a simply supported rectangular plate resting on an elastic Pasternak foundation traversed by an arbitrary number of moving concentrated masses. Kim & Roesset (1998) investigated an infinite plate resting on an elastic Winkler foundation subjected to moving loads with transformed field domain analyses using Fourier transforms. The response to moving loads with acceleration (or deceleration) has not 907

been well studied before. Existing research on response to accelerated moving loads can only be found for plate and beam structures without an elastic foundation. Saha (1997) investigated the influence of the acceleration of the traveling load on the response of a finite beam. Matsunage (2000) used the finite element method to analyze response of elastic beams to a moving load, which could be specified as a general excitation force. This paper studies the dynamic response of an infinite plate resting on an elastic foundation. The effects of acceleration, initial moving velocity and initial position are investigated and discussed. In order to prove the correctness of formulations derived in the paper, the numerical results are presented and compared with results for the same problem with a constant velocity. The dynamic response of a plate resting on an elastic foundation subjected moving traffic loads is interesting and important. The results can be applied to understand the dynamic behavior of highway and airport pavements. 2

GOVERNING EQUATIONS AND SOLUTIONS

The governing differential equation for the dynamic vertical displacements w(x, y, t) in a Cartesian coordinate system {x, y}, based on the Kirchhoff small deflection plate theory, can be written as ⎡ ∂ 4w( x, y,t ) ∂ 4w( x, y,t ) ∂ 4w( x, y,t ) ⎤ D⎢ + + ⎥ + Kw( x, y,t ) ∂x 4 ∂x 2∂y2 ∂y 4 ⎣ ⎦ 2 ∂w( x, y,t ) ∂ w( x, y,t ) +C + ρh = F ( x, y,t ) ∂t ∂t 2

(1)

where D is the flexural rigidity of the plate defined by D = Eh3/12(1−μ2), the parameters ρ, h, E, μ and C are the unit density, thickness, modulus, Poisson's ratio and damping coefficient of the plate respectively. K is the reaction modulus of the foundation. F(x, y, t) is the external dynamic load acting on the surface plate. t represents time and x, y denote rectangular Cartesian co-ordinates. The plate is assumed to extend to infinity in the horizontal plane. The load pressure within the contact area is assumed to be uniformly distributed in a rectangular area. Herein, the loads moving along the x direction are considered, and the loads, for this case, can be expressed as: F(x, y, t) = F0{U [x + a − X(t)]U [ y + b] − U [x − a − X(t)]U [ y − b]}

(2)

where U is the unit step function and X(t) denotes a function describing the motion of the force at time t defined as 1 X (t ) = x0 + Vt + at 2 2

(3)

where F0 is the amplitude function of the load. x0 is the load position, V is the initial speed, and a, b and c are the constant acceleration and the half lengths of the rectangle sides of the load distribution respectively. This function describes a uniform decelerating or accelerating motion. The uniform velocity type of motion is given by X(t) = x0 + Vt

(4)

Equations (1), (2) and (3) are total formulations for the analytical model of the plate on elastic foundation, subjected to moving concentrated loads. In order to solve the problem described above a double dimension Fourier transform is adopted as defined by following: f (ς ,η ,t ) =

∞ ∞

∫ ∫ f (x, y,t )e

−∞ −∞

908

− i ( ς x + yη )

dxdy

(5)

The inverse Fourier transform is f ( x, y,t ) =

∞ ∞

1 i ( ς x + yη ) dς dη ∫ −∞∫ f (ς ,η ,t )e 4π 2 −∞

(6)

Using the Fourier transform defined as Equation (5), Equation (1) can be presented as d 2w(ξ ,η ,t ) C dw(ξ ,η ,t ) 1 F (ξ ,η ,t ) [ D(ξ 2 + η 2 )2 + K ] . w(ξ ,η ,t ) = + + 2 dt ρh dt ρh ρh

(7)

Fourier transforming equation (2) gives ∞ ∞

− i (ς x +η y ) dxdy ∫ ∫ {U [ x + b − X (t )]U [ y + c ] − U [ x − b − X (t )]U [ y − c ]} e

F (ξ ,η ,t ) = F0

−∞ −∞

⎡

= F0

⎛

1

⎞⎤

4 sin ξ b sinηc iξ ⎢⎣x0 + t⎜⎝V + 2 at ⎟⎠⎥⎦ e ξ η

(8)

Substituting Eq. (8) into Eq. (7) and using Duhamel Integration and the inverse Fourier transform, the solution for Eq. (1) in temporal domain can be obtained as w( x, y,t ) =

⎡

∞ ∞ t

⎛

1

⎞⎤

F0 sin ξ b sinηc iξ ⎢⎣x0 +τ ⎜⎝V + 2 aτ ⎟⎠⎥⎦ − B (t −τ ) sin A(t − τ ) i (ς x +η y ) e e dξ dηdτ 2 ∫ ∫ ∫ ρ hπ −∞ −∞ 0 ξη A

(9)

2 2 2 2 where B = C/2ρh; A = D(ξ + η ) / ρ h − B Using Mathematica and integrating for τ in Eq. (9) gives

( −1) F0 ρ hπ 2 2aπ 1/ 4

w( x, y,t ) =

∞ ∞

∫∫

e

⎡ ( A + iB −ξ B )2 ⎤ i ⋅ ⎢ξ ( x + x0 ) +η y + ⎥ − pt 2 aξ ⎢⎣ ⎥⎦

−∞ −∞

A

sin ξ b sinηc ξη

⎛ 2V + at ⎞ ⎧⎪ A⎛⎜ 2 B − it ⎞⎟ iA⎜ ⎟ ⎪⎫ ∗ ⎨e ⎝ aξ ⎠ [ erf (Z1 ) − erf (Z2 )] + e ⎝ a ⎠ [ erf (Z3 ) − erf (Z4 )]⎬ dξ dη ⎪⎩ ⎭⎪ x

(10)

where erf ( x ) = 2 / π ∫ e −t dt is the error function. 2

0

Z1 =

(1 + i )[ξ (V + at ) − A + iB ] (1 + i )(ξV − A + iB ) ; Z2 = 2 aξ 2 aξ

Z3 =

(1 + i )(ξV + A + iB ) (1 + i )[ξ (V + at ) + A + iB ] ; Z4 = 2 aξ 2 aξ

The transverse stresses are the longitudinal stresses at the bottom of the plate that can be obtained respectively from

σ x ( x, y,t ) =

Eh ⎛ ∂ 2w ∂ 2w ⎞ + μ ⎜ ⎟ (1 − μ 2 ) ⎝ ∂x 2 ∂y2 ⎠ ∞ ∞

e −( −1)1 / 4 F0 Eh (ξ 2 + μη 2 ) = 2 2 ∫ ∫ ρ hπ 2aπ (1 − μ ) −∞ −∞ ⎧⎪ ∗ ⎨e ⎩⎪

⎛ 2B ⎞ A⎜ − it ⎟ ⎝ aξ ⎠

[erf (Z1 ) − erf (Z2 )] + e

⎡ ( A + iB −ξ B )2 ⎤ i ⋅ ⎢ξ ( x + x0 ) +η y + ⎥ − pt 2 aξ ⎢⎣ ⎥⎦

⎛ 2V + at ⎞ iA⎜ ⎟ ⎝ a ⎠

A

sin ξ b sinηc ξη ⎫

[erf (Z3 ) − erf (Z4 )]⎪⎬ dξ dη ⎭⎪

909

(11)

σ y ( x, y,t ) =

− Eh ⎛ ∂ 2w ∂ 2w ⎞ μ + ⎜ ⎟ (1 − μ 2 ) ⎝ ∂y2 ∂x 2 ⎠

=

∞ ∞

e −( −1) F0 Eh ( μξ 2 + η 2 ) 2 2 ∫ ∫ ρ hπ 2aπ (1 − μ ) −∞ −∞ 1/ 4

⎧⎪ ∗ ⎨e ⎩⎪

⎛ 2B ⎞ A⎜ − it ⎟ ⎝ aξ ⎠

[erf (Z1 ) − erf (Z2 )] + e

⎡ ( A + iB −ξ B )2 ⎤ i ⋅ ⎢ξ ( x + x0 ) +η y + ⎥ − pt 2 aξ ⎢⎣ ⎥⎦

⎛ 2V + at ⎞ iA⎜ ⎟ ⎝ a ⎠

A

sin ξ b sinηc ξη ⎫

[erf (Z3 ) − erf (Z4 )]⎪⎬ dξ dη ⎭⎪

(12)

The stresses considered in this study are tensile stresses in the longitudinal direction at the bottom of the plate because the transverse stresses are smaller than the longitudinal stresses. 3

DYNAMIC RESPONSE TO MOVING ACCELERATED/ DECELERATION LOAD

An infinite plate resting on the elastic Winker foundation subjected to moving traffic load with variable velocity (accelerating or decelerating) is considered in this and the following sections. The data for the plate and load amplitude used in the all the numerical examples are E = 3.45 × 104 MPa given, μ = 0.15, K = 1.36 MN/m3, C = 2.0 × 105 MN/m3, b = 0.35 m, h = 0.30 m, c = 0.25 m, F0 = 1.0 × 105 N, t = 1.0 s, x0 = 0.0. A range of acceleration and velocity values are considered in the numerical examples treated in order to study the effect of acceleration and velocity on the dynamic response of the plate. Figures 1 and 2 show the maximum deflections of the plate with different acceleration, deceleration and velocity at time of 1 second and at load positions of 0.5 m respectively. Figure 3 shows stresses of the plate with different acceleration and velocity at time of 1 second and at load positions of 0.5 m. It can be seen that the maximum deflections and stresses of the plate change with the load varying acceleration, deceleration and velocity and have different maximum values. This feature can also be seen from Figures 4 through 9 which illustrate the dynamic deflections and stresses of the plate under the different varying load acceleration, deceleration and velocity when one of them is fixed. From Figure 4, it can be seen that when the load acceleration is fixed, the deflection of the plate increases with the load varying velocity and appears as a peak values. At the acceleration of 0.2 m/s2 and velocity of 100 km/h, the displacement reaches maximum value. When acceleration is given 2 m/s2 the displacement will have a peak value at the velocity of 130 km/h.

Figure 1.

Maximum displacements of the plate with different accelerations and velocities.

910

Figure 2.

Maximum displacements of the plate with different decelerations and velocities.

Figure 3.

Maximum stress of the plate with different accelerations and velocities.

Displacement (mm)

0.15 0.1 0.05 0 –0.05

0

100

200

–0.1 –0.15 Velocity (km/h) a = 0.2 (m/s2) a = 1.4 (m/s2)

Figure 4.

a = 0.6 (m/s2) a = 2.0 (m/s2)

a = 1.0 (m/s2)

Maximum displacement of the plate with different velocities and fixed acceleration.

Figure 5 shows the results of displacement with different velocities when the deceleration is given. It can be seen that these are similar to the results shown in Figure 4; the deflection of the plate increases with the load varying velocity and appears as peak value. But the increasing speed is larger than that when the load moves with acceleration. Also, at the deceleration of –0.2 m/s2 and velocity of 100 km/h the displacement has maximum value. But when deceleration is fixed at –0.2 m/s2, the displacement has a peak value at the velocity of 190 km/h. 911

Figures 6 and 7 illustrate the results of displacement with different acceleration and deceleration values when the load moving velocity is fixed. It can be seen that the displacement reduces with the acceleration and deceleration increasing when the load moving velocity is fixed.

0.08

Displacement (mm)

0.04 0

0

50

100

150

200

–0.04 –0.08 –0.12 Velocity (Km/h) a= –.2 (m/s2) a= –1.4 (m/s2)

Figure 5.

a = –.6 (m/s2) a = –2.0 (m/s2)

a = –1.0 (m/s2)

Maximum displacement of the plate with different velocities and fixed deceleration.

Displacement (mm)

0.03 0.02 0.01 0 –0.01

0

0. 5

1

1. 5

2

–0.02 –0.03 Acceleration (m/s2) V = 10 (Km/h) V = 150 (Km/h)

Displacement (mm)

Figure 6.

–2

V = 50 (Km/h) V = 200 (Km/h)

V = 100 (Km/h)

Maximum displacement of the plate with different accelerations and fixed velocity.

– 1.5

–1

– 0.5

0

0.05 0.04 0.03 0.02 0.01 0 –0.01 –0.02 –0.03 –0.04 –0.05

Deceleration (m/s2) V = 10 (Km/h) V = 150 (Km/h)

Figure 7.

V = 50 (Km/h) V = 200 (Km/h)

V = 100 (km/h)

Maximum displacement of the plate with different decelerations and fixed velocity.

912

3

Stress (Mpa)

2 1 0 0

0. 5

1

1. 5

2

–1 –2 –3 Acceleration (m/s2) V = 10 (Km/h) V = 150 (Km/h)

Figure 8.

V = 50 (Km/h) V = 200 (Km/h)

V = 100 (Km/h)

Maximum stresses of the plate with different accelerations and fixed velocity.

4 3 Stress (Mpa)

2 1 0 ‒1

0

50

100

150

200

‒2 ‒3 ‒4 Velocity (Km/h)

a=0.2 (m/s2) a=1.4 (m/s2)

Figure 9.

a=0.6 (m/s2) a=2.0 (m/s2)

a=1.0 (m/s2)

Maximum stresses of the plate with different velocities and fixed acceleration.

Figure 8 presents the results of the stresses of the plate with different acceleration when the load varying velocity is fixed. It can be seen that the stresses of the plate reduce with the acceleration and deceleration increasing when the load varying velocity is fixed. At small values of velocity (less than 50 km/h), the reduction is slow. At large values of velocity, the reduction is rapid. Figure 9 presents the results of the stresses of the plate with different velocity when the load varying acceleration is fixed. It can be seen that the stresses of the plate increase with the acceleration increasing when the load varying velocity is fixed. At the acceleration of 0.2 m/s2 and velocity of 140 km/h, the stresses of the plate reach the maximum value. When acceleration is given as 2 m/s2, the plate stresses appear as peak values at the velocity of 170 km/h. 4

CONCLUSION

In this paper, the dynamic response of an infinite plate resting on an elastic foundation subjected to moving traffic load with variable velocity (accelerating or decelerating) was investigated by using a triple Fourier transform. The effects of the load varying velocity, acceleration and deceleration were discussed respectively. The numerical results illustrate that the maximum deflections and stresses of the plate change with the load varying acceleration, deceleration and velocity. Both the deflection and the stresses reach different maximum values. The dynamic displacements and stresses of the plate increase with the load varying velocity and decrease with the load varying acceleration and deceleration. This phenomenon 913

suggests that the design of rigid pavements should consider the effect of the dynamic load caused by variable moving vehicles. REFERENCES Gbadeyan, J.A. & Oni, S.T. 1992. Dynamic response to moving concentrated masses of elastic plates on a non-Winkler elastic foundation. Journal of Sound and Vibration 154(2): 343–358. Huang, M.H. & Thambiratnam, D.P. 2001. Free vibration of rectangular plates on elastic intermediate supports. Journal of Sound and Vibration 354(6): 643–658. Kim, S.M. & Roesset, J.M. 1998. Moving loads on a plate on elastic foundation. Journal of Engineering Mechanics 124(9): 1010–1017. Fryba, L. 1971. Vibration of Solids and Structures under Moving Loads. In New York: Noorhoff International Publishing. Huang, M.H. & Thambiratnam, D.P. 2002. Dynamic response of plates on elastic foundation to moving loads. Journal of Engineering Mechanics 128(9): 1017–1022. Lu Sun. 2005. Analytical dynamic displacement response of rigid pavements to moving concentrated and line loads. International Journal of Solids and Structures 317(12): 1830–1844. Thambiratnam, D.P. & Zhuge, Y. 1996. Dynamic analysis of beams on an elastic foundation subject to moving loads. J. Sound and Vibration 198(2): 149–169. Vallabhan, C.V.G, Straughan, W.T. & Das, Y.C. 1991. Refined model for analysis of plates on elastic foundations. J. Eng. Mech. 117(12): 2830–2844. Saha, K.N. 1997. Dynamic stability of a rectangular plate on nonhomogeneous Winkler foundation. Comput. Struct. 63(6): 1213–1222. Matsunage, H. 2000. Vibration and stability of thick plates on elastic foundations. J. Eng. Mech. 126(1): 27–34.

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Design of pavement rehabilitation to reduce the reflective cracking in pavements with cement stabilized bases E. Padilla COSIC Consultants, Guadalajara, Jalisco, Mexico

ABSTRACT: The recycling of asphalt surface and base materials is a technique frequently used to rehabilitate pavements in Mexico; the recovered material is stabilized with Portland cement to produce the new base. The stabilized bases provide an excellent support for the asphalt surface but with the risk of having contraction cracks which can be extended to the surface. To reduce this risk, it has become necessary to consider in the project design the potential reflective cracking in the asphalt surface due to the contraction of the stabilized base. According to this situation, the pavement rehabilitation project, which uses cement stabilized bases, includes three different analyses: one is based on deflection measurements; the second analysis applies the method of effective thickness; and the third which minimizes the reflective cracking assuming the stabilized base as a rigid pavement. This work describes the application of the previous analyses in a rehabilitation project for a toll freeway having heavy traffic. 1

INTRODUCTION

Recycling materials from asphalt surface and hydraulic base is a frequently used technique to rehabilitate pavements in Mexico. In the case of freeways, the recoverable material is combined with fresh material and Portland cement to produce a new base. Next, an asphalt surface is placed to complete the rehabilitation. Generally, the results obtained after using this technique have been satisfactory since the stabilized bases provide an excellent support for the asphalt surface because stabilized materials are more uniform and more water resistant compared with non-stabilized materials. Thus, this higher resistance reduced the occurrence of failures in the base and subgrades. Additionally, there is a cracking occurrence reduction in the new asphalt surface because the vertical deflections and the deformations by tension of the asphalt surface are reduced (see Figure 1). Nevertheless, cement stabilized bases show contraction cracking during the hardening process which may affect the asphalt surface. These cracks are not the result of a structural deficiency but they are a natural feature of this base type. In order to reduce this risk, it is necessary to consider in the rehabilitation project the reflection cracking potential in the asphalt surface, due to the characteristics of contraction of the stabilized base. Considering the previous scenario, the design for the new pavement (using a cement stabilized base) is calculated using two conventional methods: the method based on deflection measurements and the “effective thickness” method based on soundings. In this case, we used a third method consisting of minimizing the reflective cracking considering the stabilized base as a concrete pavement. This work presents the application of the procedure described previously for the rehabilitation of a section of the Toll Freeway Cuernavaca—Acapulco. This section has high volumes of heavy traffic. The information includes the freeway pavement superficial and structural evaluation, the rehabilitation project, the constructive procedure, comments about the reflective cracking, design to reduce cracking by reflection, and the early results about the new pavement performance. 915

Figure 1.

2

Recovery of asphalt surface material.

DESIGN FOR THE PAVEMENT REHABILITATION

Two design approaches are followed to develop the project: – The required thickness for the asphalt overlay is calculated using a criterion which reduces the present level of the superficial deflection down to an acceptable level. This method is based on the composite resistance of the pavement structure measured with the superficial reflection. – The required thickness is calculated as the difference between the necessary thickness for a new pavement and the effective thickness of the existing pavement. This method is based on the analysis of each layer in the pavement structure. The first approach uses the method proposed by the Asphalt Institute (AI, 2000), while for the second, two methods are used: the method from the Asphalt Institute and one from the AASHTO (1993). In all cases a design period of 30 years is considered. In our study case, for the toll freeway section, studies of superficial evaluation of the existing pavement were performed. This works included the study of the condition of the pavement with the estimation of the present serviceability rating, the estimation of the international roughness index using laser or Mays Ride Meter equipment, and the quantification of superficial defects like distortions, cracking, rut depths, etc. The structural project can be started when the present serviceability rating has value smaller than 2.5 and the freeway shows deteriorations on the asphalt surface, which may collapse the pavement structure. The analysis of the structural condition of the pavement is achieved by using deflection measurements obtained with the falling weight deflectometer as well as performing exploratory soundings. Dynatest falling weight deflectometer was used in the case described in this article. This device has been replacing the use of the Benkelman beam which has been the most used procedure in the Country. The structural design used the maximum superficial deflection with an approximately load of 49.0 kN. The number of exploratory soundings is determined according to the deflection measures results. Additionally, classification and resistance tests are performed in the extracted samples to characterize correctly the materials for the effective thickness analysis. Table 1 shows the results after using the mentioned methods for the freeway case and assuming a design period of 30 years and accumulated equivalent transit 33.6 × 106 axles of 80 kN. Results shown in Table 1, make patent the limitations of the method based on deflections since there are cases, like the one shown in the table, where the required thickness determined by this method is very small compared with the method based on effective thickness (50% difference). This variation suggests that this method could generate an under-designed section. 916

Table 1. Results of the application of the rehabilitation design methods (equivalent sections). Asphalt concrete required thickness (mm) Method

Effective thickness

Deflection

Asphalt Institute AASHTO

270 260

180 –

(a) Pavement section after rehabilitation design Figure 2.

(b) Pavement section after reviewing to reduce reflective cracking

Pavement sections.

According to previous information and the fact where the pavement in the freeway had thick aggregates with an excellent quality and the analysis of other alternatives, it was decided to recover a fixed thickness (200 mm) of the existing asphalt pavement, using part the recovered material (150 mm), adding fresh crushed material and Portland cement to form a stabilized base having 300 mm thickness, and finally constructing a concrete asphalt surface having 50 mm thickness (Figure 2a). This solution provides a thickness index (TI) over the existing base (1) in terms of an equivalent granular base thickness (Asphalt Institute, 1999): TI = 300 × 1.5 + 50 × 2 = 550 mm

(1)

This thickness, 550 mm, is equivalent to 275 mm of concrete asphalt and satisfies the required thicknesses for the applied methods (see Table 1). 3

CONSTRUCTIVE PROCEDURE

The relevant aspects, required to build the cement stabilized base having 300 mm of compact thickness and a compression resistance of 6.9 MPa after seven days, are described as follows: The aggregates were obtained from two sources: recovered material and material of bank. The recycled material came from the existing asphalt pavement reaching 200 mm thickness. The project reused 150 mm of thickness which was stored on site. Next, 150 mm of fresh material of the quarry (this material has the quality of hydraulic base) was mixed with Portland cement in sufficient amount, 8% in weight, to meet the project resistance. The compaction process was performed using a sheepsfoot roller and it was finished vibratory smooth roller. This base was compacted to 100% of its maximum density (Modified AASHTO varying D) in one layer. The base curing was performed with water during three days. Additionally, contraction joints every 3.0 m were made on the surface of the stabilized base. These joints were created using a saw cut with a depth reaching 1/3 of the base thickness. The joint was filling with sealing materials. Next, the base surface was impregnated using a tack coat of asphalt emulsion. Then, an asphalt surface was placed above it to complete the constructive process. The asphalt surface was a SMA (Stone Mastic Asphalt) mixture having 917

50 mm thickness. This mixture has been used in Europe and USA for many years because it has a better durability and its ability to resist rutting. After finishing these works, some cracks appeared in the surface of the pavement. As part of the procedure, a structural revision of the pavement was performed where we decided to analyze the problem of the reflective cracking, comparing our specifications, with the recommended practice. 4

REFLECTIVE CRACKING

4.1 Generalities One of the important problems that an asphalt pavement can suffer is the reflective cracking. This problem may be originated by the presence of the cement stabilized base. An analysis of this phenomenon is presented as follows. The basic reflection mechanism for the cracking is the concentration of deformations in the asphalt surface due to the movement in the vicinity of the joints (or cracks) in the cement stabilized base (Adaska & Luhr, 2004). This movement can be by bending or shearing induced by the transit load or by horizontal contraction produced by the changes of temperature. The movements generated by the transit are influenced by the thickness of the new surface and the thickness and the rigidity of the stabilized base. The movements induced by the temperature are influenced by the daily and seasonal variations of the temperature, the expansion thermal coefficient associated to the stabilized base and the spacing between joints or cracks. In many cases the cracks by reflection are narrow (opening <3 mm) and they seriously do not affect the behavior of the pavement. Nevertheless, when wider cracks appear, they can remarkably alter the life of the asphalt surface. The deteriorations caused by these cracks, diminish the present serviceability rating of the pavement and requiring, at the same time, frequent maintenance actions such as superficial asphalt treatments including leveling, patching, etc. This type of cracks allows the infiltration of water within the structure of the pavement causing problems such as the lost of bound between the asphalt surface and the stabilized base, stripping over both layers, and softening of the granular layers and subgrades. 4.2 Causes for cracking by contraction The primary cause of cracking is the contraction by drying in the cement stabilized base. The degree of contraction by drying is affected by the type of ground, degree of compaction, curing, Portland cement content, temperature, and moisture changes. In this case, the crushed aggregates used for the base mixture produced less contraction than fine soils, but they generated wide cracks, spaced at intervals ranging from 3.0 to 6.0 m. The effect of the compaction of the stabilized material, analyzed by (George, 1968), states that a well compacted base reduces the contraction potential, because the aggregate particles are packed tightly together originating a voids reduction. The voids reduction and the diminution of water content aid to reduce the contraction. In this case, the stabilized base was compacted up to 100% of its maximum density. Studies have shown that the prolonged curing has a limited benefit in relation to contraction. In other words, it does not reduce in appreciable form the contraction. In the study case, a prolonged curing was applied because it allows getting greater tension and compression resistance. Although prolonged curing could increase shrinking slightly, the net effect seems to be a decrement in the overall shrinkage. The cement hydration contributes less to the contraction than other factors. However, excessive amounts of cement can aggravate the cracking: increasing cement contents causes greater water consumption during the hydration and increasing the contraction by drying. Also, high cement levels cause an increased rigidity and excessive tension and compression resistance. A high tension resistance produces cracks that are more spaced than those originated using smaller amounts of cement, but the width in each crack is greater. Then, to 918

diminish the effect of the cement content on the contraction, it is important not to exceed the cement content required for an adequate durability. In this case, the project stated to use 8% of cement. According to the typical practice, this value is the upper limit to keep in control the resistance as the contraction of the stabilized base (Molenaar & Pu, 2008). 4.3 Methods for controlling the reflection cracking The methods to control the cracking by reflection are classified in three categories: 1) reduction of the width of the cracks in stabilized base, 2) providing a crack relief layer between the base and the surface, and 3) diminution of the susceptibility of the new asphalt surface by increasing their thickness. Two approaches were analyzed to reduce the size of the cracks in the stabilized base: the first approach is based in fitting the base constructive procedure to reduce the contraction by drying, as discussed in section 4.2; the second approach uses the pre-cracking procedure which consists of applying several passes using a large vibratory roller on the stabilized base for one or two days after the final compaction of that base. This action generates network of very fine cracks, with very small separations in the stabilized base (Scullion, 2002). That network allows releasing those contraction stresses in the early ages of the curing process and provides a pattern of cracks which minimizes the width of the contraction cracks. There are successful references in some countries using this technique. We do not have references about experiences of this technique in Mexico. Other method to reduce the cracking by contraction is achieved by relieving the stress concentrations originated by cracks in the stabilized base. This relieving is achieved by using layers denominated “stress relief layers” (TRB, 1982) which are placed between the base and the surface. The material for this relief layers can be asphalt, granular materials or geotextiles. The granular materials have been frequently used in Mexico. The increase of thickness in the new asphalt surface reduces the bending and the vertical shearing under the traffic loads and it also reduces the variation of the temperature in the stabilized base. The experience has shown that this procedure is an effective solution in delaying the occurrence and deterioration of the reflective cracking. 5

DESIGN TO REDUCE THE CRACKING BY REFLECTION

According to exposed in section 4, we took care of details during construction of the cement stabilized base to reduce the base contraction. When the placement of the asphalt surface was finished, scarce superficial deteriorations in the new pavement appeared. Thus, a detailed revision of the rehabilitation design was done where we looked for an additional solution to reduce the cracking by reflection. The solution was to increase the thickness of the asphalt surface. This action was an effective and feasible solution given the existing conditions. The selection of the minimum thickness for the asphalt overlay was based on using the criterion of the Asphalt Institute (AI, 2000). This criterion has been developed for the case of asphalt overlays on rigid pavements. We considered the cement stabilized base as a rigid pavement for using the AI criterion because the stabilized base compression resistance was similar to a poor concrete resistance (6.9 MPa). In this procedure, the surface thickness is related with the slab length and the annual average temperature differential. For the case study, we considered a slab length of 3.0 m (we have joints every 3.0 m in the stabilized base) and a local gradient of temperature of 30°C. This data provided a minimum thickness of 100 mm. Since the asphalt surface had already 50 mm, the additional required asphalt overlay is only 50 mm. We used the chart Figure 11-2 in (AI, 2000) as basis for this analysis. 6

FINAL COMMENTS

The structural revision showed that it was necessary to place additional thicknesses of concrete asphalt, because some defects in the constructive procedure of the pavement occurred. 919

The additional thickness was around 70 mm (30 mm SMA and 40 mm HMA, Figure 2b), thus, this structural reinforcement also fulfills the required thickness to reduce the cracking by reflection. For ensuring good bounding between the two AC layers a tack coat of asphalt emulsion was applied prior placement of overlay. Consequently, it was constructed an asphalt overlay having 70 mm of thickness completing a 120 mm thickness in the asphalt surface. At the time of writing this article, the freeway does not show damages in the pavement, but it is premature to emit any final conclusion with respect to the behavior due to the short time of operation, 6 months after finishing the pavement rehabilitation. This case, like others, has allowed the author to study with detail the problems associated to reflective cracking and it is planned for future rehabilitations, where cement stabilized bases are used, to include the analysis of this phenomenon as well as to prove some of the proposed solutions, like the relief layers and the pre-cracking. REFERENCES AASHTO, 1993. Guide for design of pavement structures. American Association of State Highway and Transportation Officials, Washington, D.C., USA. Adaska, W.S. & Luhr, D.R., 2004. Control of reflective cracking in cement stabilized pavements, 5th International RILEM Conference on Cracking in Pavements, Limoges, France. Asphalt Institute, 2000. Asphalt overlays for highway and street rehabilitation. Manual series No. 17, College Park, Maryland, USA. Asphalt Institute, 1999. Thickness design-highways & streets, Manual series No. 1, College Park, Maryland, USA. George, K.P. 1968. Shrinkage characteristics of soil-cement mixtures. Highway research record 255, Washington, D.C. USA. Molenaar, A.A.A. & Pu, B. 2008, Prediction of fatigue cracking in cement treated base courses, 6th International RILEM Conference on Cracking in Pavement, Chicago, IL, USA. Transportation Research Board, 1982. Minimizing reflection cracking of pavement overlays, NCHRP, Synthesis of highway practice 92, Washington, D.C., USA. Scullion, T., 2002, Field investigation: precracking of soil cement bases to reduce reflection cracking. Transportation research record 1787, Washington, D.C., USA.

920

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Verification of mechanistic-empirical pavement design guide for the state of New Jersey N. Siraj, Y.A. Mehta & K.M. Muriel Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ, USA

R.W. Sauber New Jersey Department of Transportation, Trenton, NJ, USA

ABSTRACT: The objective of the paper is to present the results of the verification of the predicted rutting, alligator cracking, longitudinal cracking, thermal cracking, and roughness (IRI) using the Mechanistic-Empirical pavement design guide. In this study, nine Long Term Pavement Performance (LTPP) and sixteen non-LTPP sections in the state of New Jersey were evaluated. The level 3 material input and level 2 traffic input were used during analysis. The input data and measured field performance data were collected from multiple sources. The analysis showed that the average difference between measured rutting and the average predicted asphalt concrete layer rutting was statistically insignificant at 95% confidence level. The measured longitudinal cracking, thermal cracking and roughness (IRI) were statistically similar to the predicted values. In addition the difference between measured and predicted alligator cracking was reasonable considering the error of field measured data, and prediction error due to level 3 material input. 1

INTRODUCTION

1.1 Background For over 45 years, the development of pavement designs has been carried out according to the American Association of State Highway and Transportation Officials (AASHTO) design guide. This guide was developed based on the extensive AASHO Road Test conducted in Ottawa, Illinois, in the late 1950s and early 1960s, which was further revised in 1986 and then in 1993. These design procedures had some limitations because limited environmental factors, subgrade soils, pavement structures and traffic data were considered. In order to overcome these limitations, in February 2004, a Mechanistic-Empirical Pavement Design Guide (M-EPDG) (Hallin, 2007) was delivered to the National Cooperative Highway Research Program (NCHRP) under project 1-37A. This research project provided a major advancement for pavement design and moved the pavement community from the existing empirical based procedures to M-E based procedures. The M-EPDG unlike the AASHTO 1993 has three levels of input. The input levels can be mixed and matched. Regardless of the input level, the damage models remain the same. 1.2 Problem statement The performance models in the M-EPDG were calibrated using the Long Term Pavement Performance (LTPP) data from the highway sections in the United States. The state of New Jersey has taken the first critical step towards implementation of pavement designs using the level 2 and level 3 inputs of the M-EPDG. The level 2 inputs typically could be user-selected, possibly from an agency database, derived from a limited testing program, or estimated from correlations. The level 3 inputs rely heavily on national and regional default values. If the local and regional values for a given state agency are not reasonably close to the default 921

values, it may lead to grossly over designed or under designed pavement sections. This will lead to premature failure or uneconomical pavement design. Both of these cases can cause significant loss of resources. In addition, the level 3 inputs may not be applicable for all types of pavements and conditions. This makes it essential for state agencies to verify the level 2 and level 3 inputs of the design guide before implementation. The four modules of input (traffic, materials, environment and pavement structure) are required for the performance prediction models of the M-EPDG. The input data that are required to predict the pavement performance are available in the LTPP database for LTPP highway sections. However, for non-LTPP sections there are different sources of input data such as Vehicles Miles of Travel (VMT) database, Weight in Motion (WIM) database and PaveView (internal database of New Jersey) for traffic input. Significant inconsistencies between different sources of input data were observed. The required material data for the design guide analysis are not available for older (>5 years) existing pavement sections. Therefore, parameters such as gradation, air voids and binder content need to be assumed. It is necessary that these assumptions are consistent with typically material properties observed for that region, source and the contractor. These assumptions are the critical part of the analysis. Overall, the most challenging factor during the verification of the predicted performance of the design guide is to ensure that reasonable input data is selected. In addition, the measured performance data might be inconsistent between different sources for the same highway segment and the same pavement age. Furthermore, the measurements might be inconsistent between years within the same source due to change in pavement rater or equipment. The vital part of the verification process is to ensure that accurate input data is selected for design guide analysis, and the predicted performance is compared with accurate field measured performance data. Therefore, there is a need to establish a systematic verification process. 2

OBJECTIVE

The objective of the paper is to verify the accuracy of the predicted performance from the M-EPDG software for the state of New Jersey for level 2 and level 3 inputs. 3

RESEARCH APPROACH

In order to meet the objective, the study has been divided into five main tasks. These are: Task 1: Literature review Review past and contemporary research conducted on the mechanistic-empirical pavement design guide and to find the information on recent studies related to verification and calibration of M-EPDG with field measured data. Task 2: Data collection Collect extensive data on the pavement structure and materials of existing roadways. Select the routes on the basis of availability of data such as traffic, material, structural information and pavement performance. Task 3: Evaluate the accuracy of the input and the performance data Verify the accuracy of the input and the performance data from multiple sources to ensure that accurate data is used in the design guide software. Task 4: Predict performance using the M-EPDG version 1.0 software Predict pavement performance such as rutting (permanent deformation), alligator cracking (bottom-up fatigue), longitudinal cracking (top-down fatigue), thermal cracking, and roughness (IRI-International Roughness Index) of all the sections using the M-EPDG version 1.0 software after obtaining reasonably accurate input parameters. Task 5: Compare the predicted performance to measured field performance Compare the predicted performance data with measured performance data and evaluate the basis of the differences. A significant effort is conducted to determine the causes of the differences. 922

The authors would like to clarify that verification study was performed for nationally calibrated models using the latest version 1.000 of the MEPDG software. The models have not been calibrated for the state of New Jersey. 4

SIGNIFICANCE OF THIS STUDY TO RESEARCHERS AND PRACTITIONERS

This study includes the verification of the predicted performance from M-EPDG for New Jersey roads and the outline of the process of verification. New Jersey Department of Transportation (NJDOT) is developing a pavement design catalog using the level 2 and level 3 inputs of the M-EPDG. The objective of the pavement catalog is to facilitate the implementation of the design guide. This versatile tool will allow the state agency to obtain candidate pavement sections that are verified with the M-EPDG without requiring repetitive runs. Verifying the accuracy of the predicted performance is the critical step towards developing a pavement design catalog for New Jersey roads. The pavement catalog that is verified for soil, environmental and traffic conditions typically observed in this region will be a powerful implementation tool. To determine the causes of differences between predicted performance of the M-EPDG and field measured data is the challenging part of the verification process. The differences between predicted performance of M-EPDG and field measured data may be due to inaccurate input data, imprecise assumptions of input parameters, unrealistic measured data or level 3 prediction model. It is essential to ensure that reasonably accurate input data is used during the verification process. Due to unavailability of input data, assumptions were made for parameters such as modulus values, gradation, air voids and binder content of asphalt. However, these assumptions were consistent with the available sources of information, such as existing construction practice of the state and the standard specification of the state agency. The research team presents the process of selecting appropriate data, which can be utilized effectively by other researchers and also help the state agency to identify the appropriate sources that can facilitate this process. In addition, it is observed that for the same section the measured data may be different between sources at the same pavement age or measurements may be inconsistent between years within the same source. For example, it is observed that in the year 2002 and 2003, the alligator cracking is zero, and in 2004 the cracking is very high (for example 80%) and again it becomes zero in 2005 and in 2006. Two possible reasons may be responsible for these cases. One reason could be due to measurement error in 2004. Other reason could be that a minor maintenance work may have been done after 2004 and that might have improved the ride quality in 2005 and 2006. However, sometimes no record is found for minor maintenance. Thus it was very challenging to find the causes of these inconsistent measurements and to select an appropriate value for verification. The paper presents how the research team meticulously addressed these challenges during verification, which are typically observed when analyzing existing pavement sections and the field performance data. In the process of verification, the research team also identified error in field measurement, which is also presented in this paper. This study will also provide guidelines for a verification process for other state agencies. 5

FIELD EVALUATION STUDIES OF MECHANISTIC EMPIRICAL PAVEMENT DESIGN GUIDE SOFTWARE

The methodology of collecting field measured data varies significantly between sources. In most of the cases, measured data may have to be converted to the numeric M-EPDG in order to compare measured and predicted values. Sometimes it is difficult to convert non-numeric measured field data (for example, low, medium or severe) to the M-EPDG format. Few studies have been conducted that compare the predicted performance of mechanistic-empirical pavement design guide with measured field data. This section discusses the challenges faced when conducting studies of the M-EPDG that utilized field measured data. 923

An analytical study was conducted for the local calibration of the fatigue cracking model of the M-EPDG for the state of Wisconsin. The fatigue damage model was used to predict longitudinal cracking on flexible pavements and then it was calibrated by identifying reliable calibration factors that would balance predicted and measured performance data (Kang, 2008). Input data for the M-EPDG of the state of Wisconsin was collected from multiple sources which were of different formats; therefore a uniform format was developed to meet the input requirements in a consistent and organized way. In this study, an irregularity in the distress measures was observed. Occasionally, distress quantities appeared to increase then drop back down without explanation. According to the Wisconsin Department of Transportation (WISDOT) pavement design experts, minor maintenance might be applied and these minor maintenance activities were not considered as restoration or reconstruction that could be designed by the M-EPDG. Minor maintenance usually focuses on the ride quality, rather than structural improvement. Thus, the distresses seemed to disappear for a short period of time; however, they might appear after few years. In addition, the irregularity in the distress measures could be due to the method of collection of measured data. Prior to 1999 in Wisconsin the pavement performance data (except IRI) was collected manually by pavement crews and from 1999 the data was collected using equipment. Another related study was conducted to calibrate the M-EPDG for the state of North Carolina (Muthadi, 2008). The analysis was completed based on two distress models, permanent deformation and alligator cracking. The calibration effort consisted on the minimization of the differences between measured and predicted data of pavement performance. The permanent deformation model was validated using Microsoft Excel Solver, in which the predicted values of rutting depth were compared to the corresponding measured values and fitted together by varying coefficients. Due to the unavailability of trenches and cores of the evaluated pavements, total rut depth measurement was distributed to each pavement layer based on the ratio of the predicted total rutting depth to the predicted rutting in each layer. Likewise, the analysis of the fatigue cracking model consisted on the calibration of coefficients for the fitting of predicted and measured data. In this study, the M-EPDG predicted rutting values matched very well with the measured rutting values for the LTPP sections. However, the North Carolina Department of Transportation (NCDOT) measured rutting did not match the predicted rutting particularly well. This observation was attributed to the fact that the NCDOT rutting measurement techniques result in a single nonnumeric rating (i.e., low, medium, or severe) and, therefore, without having more objective data these measurement techniques could not be used in the calibration or fitting process of the permanent deformation model. Thus, only the LTPP sections were used for the calibration of the permanent deformation model. The two studies presented above faced unique challenges when dealing with field measured data. This study identifies similar but also unique challenges that the research team faced, and based on the lessons learned presents a systematic process of verification. This study also explains how measurement error in alligator cracking was identified during the process of verification. This error, if rectified by the state agency will significantly increase the accuracy of field measurement data. 6 DATA In this verification study, twenty five sections (summarized in Tables 1–3) were analyzed. It included nine LTPP and sixteen non-LTPP sections. These sections covered a broad range of soil properties, environmental factors, traffic volumes and pavement structures observed in the state of New Jersey. In all sections, level 2 traffic input and level 3 material input were used during analysis. 7

RESULTS OF THE VERIFICATION ANALYSIS

The distress modes evaluated in this study are rutting, thermal cracking, alligator cracking, longitudinal cracking and roughness (IRI). The predicted performance from the M-EPDG 924

Table 1.

Summary of the selected sections for north region.

Section

M.P

AADTT*

Route 183 Route 94 Route 124 Route 159 Route 23 S (LTPP 1030) Route 15 N (LTPP 1003) Route 139 L

1.3–1.8 21.8–22.3 4.0–4.2 0.1–0.3 23.9 10 0.4–1.1

365 550 625 728 875 1463 2170

* AADTT = Annual average daily truck traffic. Table 2.

Summary of the selected sections for central region.

Section

M.P

AADTT*

Route 64 Route 202 S (LTPP 1033) Route 70 Route 35 Route 31 Route 31 Route 195 E (LTPP 1011) Route I-195 W (LTPP 0508) Route 95 S (LTPP 6057)

0.0–0.2 4.1 55.8–57.9 21.4–21.7 8.7–9.4 5.9–6.3 10.2 10.8 1.2

409 626 739 1182 1746 1883 2868 3300 4740

* AADTT = Annual average daily truck traffic. Table 3.

Summary of the selected sections for south region.

Section

M.P

AADTT*

Route 9 Route 322 Route 322 Route 49 Route 70 Route 55 N (LTPP 1638) Route 55 S (LTPP 1034) Route 40 Route 55 N (LTPP 1031)

45.4–48.1 37.0–37.2 37.3–40.8 3.3–5.1 12.4–12.6 57.5 58.5 47.4–47.5 36.4

201 532 532 666 1780 2050 2050 2150 2860

* AADTT = Annual average daily truck traffic.

software is compared with the measured field performance. For LTPP sections the measured performance are obtained from two sources, LTPP and the New Jersey Database, PaveView. For non-LTPP sections the measured performance is obtained from only one source, PaveView. The comparison between the predicted performance and the measured performance is described in the following section. 7.1 Rutting The measured rutting is the average of two wheel path rutting values at the location. For the same pavement age the measured rutting from PaveView were taken from multiple points, which were located 150 m of each other. These multiple measurements provided the research team insight into the variability in the measured data (Mehta, 2008). 925

The measured rutting is reasonably close to the predicted asphalt concrete layer rutting in all analyzed sections. A typical plot of measured and predicted rutting is shown in Figure 1 for LTPP section 1003. In Figure 1, the measured rutting is reasonably close to the predicted asphalt concrete layer rutting, and considerably lower than that of the predicted total rutting. The predicted rutting in the subgrade is high, which is unusual because the pavement had been constructed 21 years previous to the overlay construction. This trend is observed for all other sections. A detailed explanation is provided in the DISCUSSION section of this paper. The average measured and predicted asphalt concrete rutting for 25 New Jersey sections are 0.37 cm and 0.36 cm, respectively (shown in Figure 2). The average total predicted rutting for 25 New Jersey sections is 0.82 cm and the variability of the data with 95% confidence interval can be observed in Figure 2. 1.6 Measured rutting - PaveView

1.4 Rutting Depth (cm)

Total Rutting

1.2

Measured Rutting - LTPP

1 0.8 Asphalt Concrete

0.6 Base

0.4

Subgrade

0.2 0 0

24

48

72

96

120

144

168

192

216

240

Pavement Age (month - started from May 1994) Figure 1.

Rutting prediction for all layers and measured rutting for route 15 N (LTPP section 1003).

2.4 2.2

Total Rutting - Design Limit

2 1.8 Rutting (cm)

1.6 1.4 1.2 1

Asphalt Concrete Rutting - Design Limit

0.8 0.6 0.4 0.2 0 Average Measured Rutting Figure 2.

Average Predicted Asphalt Concrete Rutting

Average Predicted Total Rutting

Average measured and predicted rutting for 25 New Jersey sections.

926

7.2 Cracking 7.2.1 Alligator cracking The average measured and predicted alligator cracking for 25 New Jersey sections are 2.22% and 0.04%, respectively, which is shown in Figure 3. The 95% confidence interval of the measured data (2%–4%) is higher than that of the predicted data (close to zero). However, the range of the measured data is well below the design limit of 25%. 7.2.2 Longitudinal cracking The computed average measured and predicted longitudinal cracking for 25 New Jersey sections are 12 m/km and 9 m/km respectively (Figure 4). The 95% confidence intervals overlap, and both the measured and predicted data are well below the design limit of 379 m/km. 7.2.3 Thermal cracking The predicted thermal cracking for 25 New Jersey sections is zero. The average measured thermal cracking for all sections is 9 m/km, which is below the design limit of 189 m/km. The low confidence intervals and standard deviations were due to overall good field performance of sections. In many cases the distresses were close to zero contributing to low confidence interval values.

30 Design Limit Alligator Cracking (% )

25 20 15 10 5

Close to zero

0 Average Measured Alligator Cracking

Average Predicted Alligator Cracking

Figure 3. Average measured and predicted alligator cracking for 25 New Jersey sections.

450

Longitudinal Cracking (m/km)

400

Design Limit

350 300 250 200 150 100 50 0 Average Measured Longitudinal Cracking

Figure 4.

Average Predicted Longitudinal Cracking

Average measured and predicted longitudinal cracking for 25 New Jersey sections.

927

3.5 Design limit

3

IRI (m/km)

2.5 2 1.5 1 0.5 0 Average Measured IRI Figure 5.

Average Predicted IRI

Average measured and predicted roughness (IRI) for 25 New Jersey sections.

7.3 Roughness (IRI) Figure 5 shows the average measured and predicted IRI for 25 New Jersey sections; these values are 1.6 m/km and 1.5 m/km, respectively. The 95% confidence interval of the measured data is close to the predicted data. In both cases, the values are below the design limit of 2.7 m/km. Siraj 2008 has presented the detailed performance data of all sections, including the comparison of predicted and measured performance data. The comparison of the confidence intervals provides an accurate sense of how the nationally calibrated values verify for New Jersey sections. 8

DISCUSSION

8.1 Rutting Over prediction of rutting in the subgrade was observed for both overlay and newly constructed sections. In the case of overlay sections, the analysis was performed from the overlay construction which was done recently. The underlying pavement layers and the subgrade have been extensively compacted over 20 to 30 years due to vehicular traffic load. Thus the stiffness of those layers has increased. High subgrade rutting values would be expected for new construction and not for sections compacted over a long period of time. This inaccuracy of the rutting predictions may be due to the error in the rutting model of the unbound layers. According to the design guide manual (Guide for M-EPDG, 2008), high values of subgrade rutting is observed using rutting model. The modified models have been developed but not incorporated. The patterns of measured rutting and predicted asphalt concrete layer rutting were analogous in all sections (Figure 2). The average total predicted rutting was 0.82 cm which is greater than twice of average measured values (0.37 cm). Thus considering over prediction of subgrade rutting in the state of New Jersey sections, the researchers compared measured field rutting with predicted asphalt concrete layer rutting in this verification study. 8.2 Cracking 8.2.1 Alligator cracking The measured alligator cracking showed significant variability at a given milepost and also between consecutive years. For example, in LTPP section 1011, the 2001 and 2002 PaveView 928

measured data was equal to zero and close to the predicted cracking. However 2004 measured data exceeded design limit and then back to zero in 2005 and again in 2006 measured data exceeded design limit. According to the state agency, (Robert Sauber, Personal Communications, 2008 Unpublished Data) this may be due to the field measurement error. Map cracking or block cracking is similar to alligator cracking. However, map or block cracking is not associated with the load. Sometimes it is very difficult to differentiate between load associated alligator cracking and block or map cracking. Whenever the inconsistency of measured cracking was observed, the research team checked all raw measured cracking. The field measurement error was found for alligator cracking in eleven analyzed sections out of twenty five, it was identified that when cracking values in any one of the categories were high, the alligator cracking values was unusually high. Therefore, the measured alligator cracking was corrected by subtracting the non-load associated cracking values in these eleven sections. For three LTPP sections, the measured alligator cracking (obtained from LTPP database) was higher than the measured field data from PaveView, and the predicted cracking. This discrepancy could be due to error in measured data from LTPP or may be due to prediction error at level 3 materials inputs. The standard error of the mean (value of 0.66%) of the alligator cracking based on 148 observations for this New Jersey verification study was within the standard error of the mean (value of 6.2%) of the level 3 calibration study of M-EPDG model based on 461 observations across the country. 8.2.2 Longitudinal cracking and thermal cracking The measured longitudinal (average value of 12 m/km) and thermal cracking (average value of 9 m/km) was close to the predicted longitudinal (average value of 9 m/km) and predicted thermal cracking (zero) in all sections. 8.3 Roughness The measured roughness (IRI) was close to the predicted roughness (IRI) for all sections, except for two non-LTPP sections (Route-35 and Route-40). The measured roughness of Route-35 and Route-40 exceeded the design limit after 1 and 2 years, respectively. However, at that time all other distresses were close to zero and the Surface Distress Index (SDI) values of these two sections at that time were close to 5 (5 = Good condition). Therefore, the measured IRI values were inconsistent with other distresses and the SDI values, possibly indicating measurement error for these two sections. Therefore, the measured IRI values were inconsistent with other distresses and the SDI values, possibly indicating measurement error for these two sections. 9

SUMMARY OF THE ANALYSES

The summary of the analysis for verification study based on twenty five sections is given below: − Over prediction of rutting in the subgrade was observed in overlay construction as well as in new construction for all analyzed sections in the state of New Jersey. − The difference between measured rutting (average value of 0.37 cm) and the predicted asphalt concrete layer rutting (average value of 0.36 cm) was statistically insignificant at 95% confidence level for all analyzed sections in the state of New Jersey. − The measured alligator cracking (average value of 2.22%) was higher than the predicted alligator cracking (average value of 0.04%). The variability of the measured data was higher than the predicted data at 95% confidence level for all analyzed sections in the state of New Jersey. − The measured longitudinal cracking (average value of 12 m/km) was statistically similar to the predicted longitudinal cracking (average value of 9 m/km) in all analyzed sections. 929

− For all analyzed sections, the measured thermal cracking (average value of 9 m/km) was statistically similar to the predicted cracking in all sections. − The difference between measured roughness (average value of 1.6 m/km) and predicted roughness (average value of 1.5 m/km) was statistically insignificant at 95% confidence level for all analyzed sections in the state of New Jersey. − A case-by-case comparison of performance was conducted for all sections and distresses to ensure thorough verification considering the variability of measured field data, incomplete input values, discrepancy of data between and within sources. 10

CONCLUSION

The rutting, top-down fatigue (longitudinal cracking), thermal cracking and roughness (IRI) predicted performances from M-EPDG were verified for level 2 traffic input and level 3 material input for the state of New Jersey. However, bottom-up fatigue (alligator cracking) predicted performance from M-EPDG was not statistically verified for level 2 traffic input and level 3 material input for the state of New Jersey. REFERENCES Guide for Mechanistic-Empirical Design Guide of New and Rehabilitated Structures Appendix II. Accessed on July 15th, 2008. Calibration of permanent deformation models for flexible pavements. http://www.trb.org/mepdg/2appendices_GG.pdf Hallin. 2007. Development of the 2002 guide for the design of new and rehabilitated pavement structures, National Cooperative Highway Research Program 1-37A. Kang, M. and T.M Adams. 2008. Local calibration of the fatigue cracking model in the MechanisticEmpirical Pavement Design Guide, In proceedings of the 87th Transportation Research Board annual meeting. Washington DC. Mehta, Y.A., Sauber, R.W., Owad, J. and J. Krause. 2008. Lessons learned during implementation of Mechanistic-Empirical Pavement Design Guide, In proceedings of the 87th Transportation Research Board annual meeting. Washington DC. Muthadi, N.R. and Y.R Kim, 2008. Local calibration of the MEPDG for flexible pavement design, In proceedings of the 87th Transportation Research Board annual meeting. Washington DC. Siraj, N. 2008. Verification of asphalt concrete performance prediction using level 2 and level 3 inputs of Mechanistic-Empirical Pavement Design Guide for flexible pavements of the state of New Jersey, Master of Science Thesis. Rowan University.

930

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Mechanistic evaluation of second generation preservation overlays D.A. Morian & S. Sadasivam Quality Engineering Solutions, Conneaut Lake, PA, USA

S.M. Stoffels, G. Chehab & T. Kumar Pennsylvania State University, University Park, PA, USA

ABSTRACT: The application of hot mix asphalt (HMA) overlays of rigid pavements is a common pavement rehabilitation practice. This paper provides an evaluation of the effect of the second generation hot mix asphalt (HMA) overlay on a 16 km section of Interstate 79 in western Pennsylvania. The project was constructed to provide a comparison of two second generation overlay strategies; one consisting of leveling and wearing and the other of binder and wearing courses. The evaluation included monitoring of the construction process, and assessment of the effect of the new overlays on pavement condition as measured by distress, deflection, and roughness. Additionally, the predicted performance of the two comparison cross sections was modeled using the proposed AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG), and other mechanistic analysis tools. Results from the work include structural evaluation of the two different pavement sections, and associated performance predictions. A methodology for performing long term monitoring of pavement performance and evaluation of life cycle cost was also provided to the highway agency. 1

INTRODUCTION

The placement of an asphalt overlay is a technique frequently used as a rigid pavement maintenance and rehabilitation strategy. Overlay placement can improve ride quality and surface friction, and may also increase pavement structural capacity (Hall et al., 2001). Frequently, the primary objective of a second-generation overlay is to improve pavement functional performance, making it a common preventive maintenance strategy. Often, second-generation asphalt overlays on rigid pavements are relatively thin, less than nine centimeters providing little structural contribution. The functional purpose of these overlays is to improve pavement serviceability, safety, and ride quality. In recent years, Pennsylvania Department of Transportation (PennDOT) has typically used a mill, level, and overlay strategy for pavement preservation of Interstate highways consisting of an original rigid pavement with existing asphalt overlay. First-time asphalt overlays of rigid pavements have been a minimum of 8.9 cm since the early 1980s. A typical secondgeneration overlay for PennDOT includes a 3.8 cm overlay on a 2.54 cm leveling layer, after 5 cm surface milling. Use of the saw and seal technique for controlling joint reflective cracking is common in Pennsylvania. In 2005 PennDOT initiated a research project to investigate the cost-effectiveness of using an asphalt binder layer rather than a leveling layer to achieve better cost effectiveness from second-generation overlays on rigid pavements. This project was constructed on Interstate 79 in Butler County, Pennsylvania approximately 20 miles north of the City of Pittsburgh. Both measured and predicted performance comparison of the overlay alternatives are discussed in the paper. While the thickness of the overlays is similar, other significant differences do exist. A typical leveling layer represents an average thickness, and because it is anticipated to have non-uniform thickness no compaction requirement is applied. The binder layer represents a minimum thickness of two inches, and compaction to 92% minimum density is required. 931

The 2004 average annual daily traffic (ADT) was 21,580 with 13 percent truck traffic. Construction of this ten-mile Superpave overlay from the Allegheny/Butler County line (approximately milepost 78) to MP 88 was completed between March and September of 2005. The experiment was designed such that the binder course and overlay section began at the southern end of the project and extended northward for approximately 6.1 km in both traffic directions of the divided highway. The leveling section began at the north end of the binder section and extended northward approximately 9.4 km to the end of the project in both directions of travel segment. 2

PRE-CONSTRUCTION PAVEMENT CONDITION EVALUATION

An assessment of the existing pavement conditions was made prior to pavement milling (Stoffels et al., 2005). Information was collected by performing distress surveys, coring, and deflection testing. A visual condition survey was conducted of both pavement sections for both the northbound and southbound lanes consistent with procedures contained in PennDOT Publication #336, Automated Pavement Condition Field Manual (PennDOT Publication 336, 2004). Distress generally consisted of transverse cracking, deterioration of the pavement surface at sawed and sealed pavement joints, and rutting. Significant longitudinal and transverse cracking was observed, with minimal fatigue cracking, prior to construction. Table 1 presents the preconstruction distress summary. Historic roughness values (IRI) for the period 2000 to 2004 were provided by PennDOT. Table 2 shows the average IRI values for the northbound and southbound lanes. The average increase in roughness from 2000 to 2004 was 16.5% for the northbound lanes and 30.6% for the southbound lanes. Deflection data was collected to assess the material properties of the existing pavement layers, and assess load transfer of the overlaid rigid pavement joints. Table 3 provides a summary of load transfer efficiency data by direction. Joint rehabilitation of low load transfer locations should improve overlay performance by reducing overlay stresses. However, this work item was eliminated from the contract. Table 1.

Preconstruction distress summary. Northbound

Southbound

Distress

Low

Medium High Low

Medium High

Fatigue cracking, m Transverse cracking, m Miscellaneous, m Edge cracking, m Longitudinal cracking, m Patching, m2 Slab patch, m2

184.7 3134.6 579.7 445.0 8119.9 5.8

158.5 314.6 361.5 0.0 932.7 7.1 8.7

152.4 705.9 427.6 0.0 878.4 0.0 8.5

0.0 0.0 0.0 0.0 0.0

165.8 3189.4 569.1 356.6 8217.4 3.7

0.0 11.0 0.0 0.0 24.4

Table 2. Historical IRI values (m/km). Year

Northbound

Southbound

2000 2001 2002 2003 2004

1.21 1.31 1.37 1.40 1.41

1.37 1.48 1.64 1.66 1.79

Table 3. Load transfer efficiencies before construction. Parameter

Northbound

Southbound

Average Minimum Maximum

80.6 26.6 96.8

77.6 20.4 92.6

932

Rutting measurements were collected every 0.16 km in both lanes. The maximum rut depth was 0.838 cm and 0.965 cm in the northbound lane and southbound lane, respectively. Core samples were tested for asphalt content, void content, and aggregate gradation. Typical construction variations were observed with asphalt contents within the acceptance ranges for both binder and wearing courses. PennDOT’s pavement management treatment matrices recommended mill-or-level and functional overlay for both north and southbound lanes on the basis of cracking distress and ride quality. Treatment recommendations were consistent throughout the project length. 3

CONSTRUCTION

The existing pavement consisted of 10.16 cm of hot mix asphalt concrete (HMA), 25.4 cm of jointed portland cement concrete (PCC) pavement, and 25.4 cm of subbase on a clay subgrade. Five centimeters of the existing asphalt overlay was milled prior to placement of the new overlay sections. The milling operation pattern generally removed the inside travel lane and shoulder in a single pass, followed successively by the outside travel lane, and then outside shoulder. Paving was accomplished following the same sequence. For the experimental section of the project, a 5.08 cm thick binder material consisting of 19 mm Superpave was placed, followed by 3.81 cm of 9.5 mm Superpave wearing course. The control portion of the project was paved with a nominal 2.54 cm leveling course consisting of 9.5 mm Superpave material, followed by the a second 3.81 cm surface course as used for the southern section. In general, the contractor performed good quality work meeting project requirements. The HMA plant produced consistent quality material, and the placement operation generally followed good industry practices. The compaction process was consistent and resulting density values obtained from pavement cores were within specifications. 4

ASPHALT MIX PROPERTIES

Both surface and binder course mixes used PG76-22 asphalt binder containing a cross-linked SBS block copolymer modifier. Both coarse mixes had different maximum aggregate size and 2.2% bag house fines. The surface and the leveling courses used the same mix design, but the leveling course required no minimum aggregate friction or density. The binder layer mix included 10% recycled asphalt pavement (RAP). Loose mix samples and field cores were collected and volumetric properties determined as part of PennDOT’s quality assurance/quality control (QA/QC) procedures of mixtures in accordance with the QA/QC requirements. Test results from the contractor and PennDOT are provided in Table 4, along with the job mix formula (JMF). No significant variation was identified between the contractor’s QC and PennDOT’s QA results.

Table 4.

Comparison of quality control/quality assurance test results. Wearing

Binder

Factor

JMF Contractor PennDOT JMF Contractor PennDOT

Binder content Passing # 200 Sieve In-place air voids

5.5 5.4

5.5 5.9 6.1

5.5 6.1 5.9

933

4.4 4.0

4.6 4.5 4.8

4.5 4.0 4.9

Figure 1.

Master curve projections on a log-log graph.

Dynamic modulus testing was performed in accordance with ASTM D3497 to characterize the mixes. The master curves for the binder and surface mixes (labeled CR1 and A26, respectively) at a reference temperature of 25oC are shown in Figure 1. The master curves were projected using a sigmoidal function on a log-log scale. The stiffness of the two mixes is similar at very high frequencies, which is representative of fast moving vehicles and low service temperatures. However, at very low frequencies, representing very slow moving traffic and very high service temperatures, the binder mixture is considerably stiffer than the surface mixture. The aged asphalt RAP portion of the binder coarse mixture may contribute to a change in the elastic part of the Complex Modulus E*, resulting in increased mix stiffness. Since the slope of the master curve is a measure of the viscoelasticity of a mixture, the slope of the |E*| master curve is greater for the surface mixture than for the binder mixture. For the binder course, the RAP resulted in reduced time and temperature dependency of the HMA mixture. 5

DESIGN REVIEW

A design review was conducted to assess theoretical structural differences between the control and experimental overlay sections. Little previous research information is available specifically addressing second generation overlays. A linear elastic layer analysis was performed using the Kenlayer program. The locations at which stresses and strains were computed are shown in Figure 2. The layer properties used for the linear layer elastic analysis are listed in Table 5. The visco-elastic properties derived from the material characterization of bituminous mixtures were used. The leveling course was not modeled as a separate layer, since it had a variable thickness across the pavement cross section and was not expected to contribute to the structural performance of the pavement. Table 6 provides detailed tabulation of the critical stresses and strains for the analyzed pavement sections and their effect on distress development. The mechanistic properties obtained from the linear elastic analysis were used in pavement prediction models presented in the Mechanistic Empirical Pavement Design Guide (MEPDG) in order to compare the failure resistance of the two pavement structures. 934

600 kPa H H I J K L M

A B C D E F

N

G

Surface Layer Binder Layer Existing HMA Layer Existing PCC Layer

Subgrade

Figure 2.

Locations at which Kenlayer output was obtained.

Table 5.

Table 6.

Material properties for layered elastic analysis.

Layer

Depth, cm

Elastic modulus (MPa)

Poisson’s ratio

Surface Binder Old asphalt Concrete Sub-grade

3.81 6.35 6.35 25.4 Infinity

8367 7618 6500 24000 103

0.35 0.35 0.35 0.15 0.45

Effect of inclusion of binder layer on pavement distresses.

Distress

Critical stress/strain

Point

Surface only

Surface + Binder

Rutting

Shear stress at edge of wheel

H I J A B B C G H A J C J C

1.42E+01 2.39E+01 2.21E+01 1.22E+02 8.72E+01 1.67E-05 1.17E-05 1.05E-05 4.51E+01 1.04E+02 2.21E+01 6.29E+01 3.70E+01 8.72E+01

1.24E+01 2.48E+01 2.35E+01 1.22E+02 8.71E+01 1.52E-05 8.16E-06 5.56E-06 4.76E+01 1.06E+02 2.35E+01 5.79E+01 3.33E+01 8.71E+01

Compressive stress under wheel Fatigue

Tensile strain at bottom of layer

Top-down cracking

Tensile stress at edge of wheel Radial stress under wheel Shear stress at interface Tensile stress at bottom of layer

Reflective cracking

Compressive stress at bottom of layer

935

5.1 Permanent deformation modeling Figure 3 shows the rutting progression from the linear elastic layer analysis and the MEPDG rutting model (NCHRP 1-37A, 2004). The linear elastic analysis showed that with the inclusion of a binder layer, the vertical compressive stress, as well as vertical strain, is much higher at the surface under the wheel but approximately the same at other depths. The increase in vertical strain is more pronounced at the edge of the wheel, where shear effects have greater influence. This might imply that any observed difference in permanent deformation could be due to shear effects rather than compressive effects. When the shear stress (and shear strain) is observed, it is noted that the values are lower at the surface under the wheel but considerably higher at greater depths down to the middle of the old asphalt layer. This analysis indicates that the overlay with binder layer would experience slightly greater rutting. However, the predicted rut depths for both cases are well below a functionally acceptable criterion of 1.27 cm. The MEPDG level 1 analysis predicts less rutting for the binder section than for the section with leveling. Slightly more rutting is predicted using level 2 and 3 analyses for the section including binder layer than for the section without. In all cases, predicted rut magnitudes remain small, and the differences between the control and binder sections are insignificant. In summary, the MEPDG software predicts very little difference in the performance of the pavement sections with binder and leveling layers during the first ten years of service. The software appears to be insensitive to differences between the two pavement sections. 5.2 Fatigue cracking Since fatigue cracking is associated with tensile failure, the tensile strain is used for εt. Table 6 shows that theoretically the tensile strains are significantly lower at each of the points A, B and C in the pavement with binder layer, as a result of the increased thickness. Table 7 provides the fatigue life estimate (Nf) for both pavement sections based on the MEPDG prediction model. This implies that the inclusion of a binder layer will improve resistance to fatigue cracking.

Permanent deformation (in)

0.120

0.100

0.080

0.060

0.040

0.020

Without binder layer With binder layer

0.000 0

5

10

15

20

25

30

Age (years)

Figure 3.

Permanent deformation based on MEPDG nationally calibrated model. Table 7. Phenomenological model output for fatigue cracking based on lea results. Case

Thickness

εt

Nf

Without binder layer With binder layer

10.16 cm 15.24 cm

11.70 × 10–6 8.16 × 10–6

8.85 × 1014 3.50 × 1015

936

35

However, fatigue cracking is typically not a problem in overlays on rigid pavements unless there is loss of bond between the asphalt overlay and the underlying concrete pavement. MEPDG analysis results for all three analysis levels provide similar performance predictions, as shown in Table 8. Virtually no fatigue cracking is predicted for these pavement sections. The presence of intact concrete pavement slabs beneath the overlay provides a high level of structural stiffness, making this a reasonable conclusion. 5.3 Top-down cracking Top-down cracking is a complex phenomenon and this model is a highly simplified one. For example, it does not account for thermal stresses, which are considered important for surface initiated cracks. Such stresses are expected to be independent of pavement structure since thermal strains will play a critical role only at the surface of the pavement. It was observed from the linear elastic analysis that the tensile stress at point H (under the wheel at the edge) as well as the radial stress at point A (under the wheel path centerline) exhibit negligible change with the inclusion of a binder layer. While there are variations in the relative MEPDG predictions among the various levels, the predicted magnitude of crack development in all cases is insignificant in the context of overall pavement performance. 5.4 Reflective cracking In freeze climates, it is common for concrete pavement joints to reflect through HMA overlays resulting in what is commonly referred to as reflective cracks. An evaluation of the two alternative pavement cross-sections indicated that the shear stress (and shear strain) is slightly larger at the asphalt—concrete interface for the case which includes a binder layer. For this Table 8.

Predicted performance from MEPDG. Rutting (mm)

Analysis level 1

Structure Surface + Leveling

Surface + Binder

2

Surface + Leveling

Surface + Binder

3

Surface + Leveling

Surface + Binder

Service life (years)

Top-down cracking (%)

Fatigue cracking (%)

AC

Total

IRI (m/km)

5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20 5 10 15 20

1.50E-05 3.10E-05 4.82E-05 6.07E-05 3.68E-06 7.06E-06 1.06E-05 1.39E-05 7.33E-04 1.47E-03 2.24E-03 2.98E-03 2.16E-04 4.55E-04 7.23E-04 9.89E-04 2.19E-04 5.13E-04 8.39E-04 1.15E-03 1.41E-04 3.25E-04 5.37E-04 7.39E-04

1.99E-09 4.21E-09 6.46E-09 8.95E-09 7.75E-09 1.77E-08 2.85E-08 4.16E-08 0 0 0 0 5.75E-10 1.27E-09 2.01E-09 2.83E-09 0 0 0 0 6.31E-10 1.34E-09 2.10E-09 2.95E-09

2.62 3.81 4.85 5.72 2.24 3.25 4.11 4.88 4.11 5.99 7.59 8.97 4.17 6.02 7.62 9.02 3.23 4.75 6.05 7.16 3.25 4.78 6.07 7.21

2.62 3.81 4.85 5.72 2.24 3.25 4.11 4.88 4.11 5.99 7.59 8.97 4.17 6.02 7.62 9.02 3.23 4.75 6.05 7.16 3.25 4.78 6.07 7.21

0.74 0.84 0.96 1.09 0.73 0.83 0.94 1.07 0.78 0.90 1.03 1.17 0.78 0.90 1.03 1.18 0.76 0.87 0.99 1.13 0.76 0.87 0.99 1.13

937

case the tensile stress is significantly lower but the compressive stress does not change. These results may reduce reflective crack effects, which correlates with observations that it takes longer to observe reflective cracking in thicker overlays. 6

POST-CONSTRUCTION MONITORING

Pavement condition data were again collected immediately after construction, and again one year after construction. Roughness measurements, deflection testing, and visual distress surveys were conducted (Stoffels et al., 2007). 6.1 Distress Post-construction distress data were collected immediately after construction, and again one year later. As expected, minimal distress was identified in the new overlay immediately after construction, and in September of 2006. The primary distress identified one year after construction was transverse cracking. These cracks generally represent joint reflective cracking resulting from improper location of saw and seal reservoirs, or reflection of mid-panel cracks in the reinforced concrete slabs. Significantly more cracks were identified in the southbound lanes than in the northbound lanes, with 18 transverse cracks and 3 longitudinal cracks in the southbound, and 4 transverse cracks and no longitudinal cracks in the northbound. The occurrence of cracking distress between the two sections clearly indicates that a higher frequency of cracking exists in the leveling section. Three transverse pavement cracks existed in the northbound pavement surface where leveling course was used and only one where the binder course was applied. For the southbound pavement, 17 transverse cracks were observed in the leveling section, with none in the binder section. In addition, a single location of shoving was identified in the section with leveling in Milepost 86 southbound. This relatively greater occurrence of reflective cracks in the thinner leveling layer is consistent with expectations. 6.2 Roughness Roughness measurements were collected twice in 2005 and once in 2006. The contractor collected ride quality immediately after construction using a lightweight inertial profiler. The roughness data were collected lot-wise at the project level, in accordance with PennDOT quality assurance specifications. Network level data was collected in December 2005 and in August 2006 by PennDOT using a high-speed, multi-point laser profiler. The data sets analyzed using roughness statistics generated with ProVAL version 2.6 software are provided in Table 9. The August 2006 data shows an increase in roughness approximately one year after construction. The network level roughness data indicate the development of more roughness in the leveling section as compared with the binder section after one year under traffic as shown in Table 10. Segment level IRI data indicate that the placement of the overlay resulted in a major decrease in roughness for both binder and leveling overlay sections. Placement of the overlay reduced the before construction roughness level by approximately 63% in the northTable 9. Network level roughness comparison. Mean roughness index (m/km) Northbound

Southbound

Year

Binder

Leveling

Binder

Leveling

2004 2005 2006

1.53 0.65 0.68

1.41 0.66 0.71

1.75 0.63 0.65

1.93 0.71 0.75

938

Table 10.

Percent change in smoothness.

Decrease in roughness from 2004 to 2005 Increase in roughness from 2005 to 2006

Table 11.

Direction

Binder

Leveling

Northbound Southbound

64.3% 68.0%

62.4% 72.4%

Northbound Southbound

27.7% 23.4%

30.2% 34.6%

Load transfer efficiency for sampled sections. Northbound

Southbound

LTE

Binder

Leveling

Total Binder

Leveling

Total

Average Good >70% Poor <70%

74.7 50 9

67.9 45 41

70.6 95 50

56.9 15 24

61.1 29 32

68.5 14 8

bound lanes, and 68% in the southbound lanes. The average IRI values after the placement of the overlay were 0.51 m/km and 0.52 m/km for the northbound and southbound lanes, with a variability of about 9%. After one year under traffic, roughness increased about 25% in the binder sections and 32% in the leveling sections. The roughness increase is more pronounced in the southbound lanes than the northbound. This roughness increase correlates with greater transverse cracking in the leveling sections. This early trend may not be representative of long term performance. 6.3 Deflection Deflection data were collected in selected locations available for testing within construction work zones established for other operations. Although load transfer in the northbound lanes was generally found to be acceptable, 50% of the joints in the southbound lanes had poor load transfer, as shown in Table 11. It is anticipated that this condition will result in greater overlay distress in the future. 7

CONCLUSIONS

This preliminary analysis of the placement of a second generation overlay on a jointed rigid pavement has resulted in some important observations. • Both the leveling and binder with surface course overlay sections resulted in a reduction in roughness of more than 50%, as measured by IRI. • Placement of the binder layer resulted in slightly lower IRI in those sections as compared with the corresponding leveling sections. • While accelerated testing indicated the binder layer developed rutting more rapidly initially, at a threshold value of 1.27 cm depth, predicted rutting of the two sections is not significantly different. • After one year in service, the new overlay in the binder sections has significantly less cracking than the leveling sections. • The rate of roughness development of the leveling sections, after one year in service, is two times that of the binder sections. It is not expected that this relationship will continue throughout the duration of the pavement life, but the general trend that the binder section will remain smoother longer can be expected. 939

• The mechanistic analysis predicts larger fatigue life for the section with binder layer, but this difference is not significant from the perspective of performance life. • Performance predictions utilizing the MEPDG software indicate no significant difference in the performance of the two alternative pavement sections. This is likely due to the lack of sensitivity of the prediction models employed. Reflective cracking was the predominant distress observed prior to placement of the overlay. It is again the primary distress mode observed one year after placement of the overlay. After one year in service two longitudinal cracks were identified in the southbound leveling section of the project, with none in the binder section. However, the primary modes by which this distress contributes to a need for resurfacing is in the form of increased roughness and intrusion of water into the base and subgrade. Pavement roughness triggers the need for overlay in the PennDOT pavement management system. 8

RECOMMENDATIONS

At the present time, the reduction in roughness resulting from the overlay has produced an acceptable ride quality throughout all sections of the project. Observations from the accelerated testing, analysis, and early field conditions, while not conclusive, indicate that the inclusion of the binder layer has the potential to result in improved performance. Therefore, it is essential that the performance of these sections continue to be monitored over the life of the overlays. The performance data, and any maintenance performed, should be logged in the provided performance database. Future analysis of cost-effectiveness can then be performed. A life cycle cost spreadsheet was provided to PennDOT to support this continued analysis. REFERENCES Hall, K.T., Correa, C.E., Carpenter, S.H. & Elliot, R.P. 2001. Rehabilitation Strategies for Highway Pavements, National Cooperative Highway Research Program, Washington D.C. NCHRP Report 1-37A, 2004. Design of New & Reconstructed Flexible Pavements, Mechanistic Empirical Design of Pavement Structures, National Cooperative Highway Research Program, Washington D.C. Stoffels, S.M., Chehab, G., Morian, D.A. & Kumar, T. 2005. Preventative Maintenance I-79: Summary of Literature and Interviews, Report submitted to Pennsylvania Department of Transportation, Harrisburg. Publication 336, 2004. Automated Pavement Condition Survey—Field Manual, Pennsylvania Department of Transportation, Harrisburg. Stoffels, S.M., Morian, D.A., Sadasivam, S. & Chehab, G. 2007. Preventive Maintenance I-79—Phase II, Report submitted to Pennsylvania Department of Transportation, FHWA-PA-2007-006-040213-2, Harrisburg.

940

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A robust approach for the evaluation of airport pavement bearing capacity Y.H. Lee Tamkang University, Taipei, Taiwan

Y.B. Liu & J.D. Lin National Central University, Taoyuan, Taiwan

H.W. Ker Chihlee Institute of Technology, Taipei, Taiwan

ABSTRACT: The ACN/PCN method has been adopted by the ICAO as the standard for reporting airfield pavement bearing strength. For a more conservative evaluation and design approach, the mean value minus one standard deviation (or the so-called 85% confidence level) may be used for obtaining evaluation or design inputs in general (AC 150/5320-6D). Nevertheless, it was found that this procedure was not based on sound statistical principles especially when the probability distribution of the population is almost always unknown. Consequently, the concepts of random sampling, central limit theorem, and confidence intervals for hypothesis testing were adopted. It was proposed that a single representative design input for the entire runway pavement be determined by the lower limit of 95% confidence level to derive a more consistent and repeatable PCN value. A case study was conducted to illustrate the potential problems of the existing ACN/PCN procedures and the benefits of the proposed revisions. 1

INTRODUCTION

The Aircraft Classification Number/Pavement Classification Number (ACN/PCN) method has been adopted by the International Civil Aviation Organization (ICAO) as the standard for reporting the airfield pavement bearing strength. Although it has been clearly recommended that the engineer should simultaneously consider the mean and standard deviation in the selection of an evaluation or design input value, many evaluation and design procedures currently only use the mean value in the analysis (AC 150/5370-11 A) (FAA 2004b). For a more conservative evaluation and design approach, the mean value minus one standard deviation (or the so-called 85% confidence level) may be used for obtaining evaluation or design inputs in general (FAA 2006a, b). This study will first illustrate its definitions, possible applications, and potential problems in arriving at a consistent and repeatable value based on the results of nondestructive testing. To derive a more consistent and repeatable PCN value, the concepts of random sampling, central limit theorem, and confidence intervals for hypothesis testing will be proposed for establishing the evaluation or design inputs. 2

REVIEW OF ACN/PCN METHODOLOGY

The ACN/PCN method is designated by the ICAO as the only approved method for reporting the bearing strength of pavements. Each aircraft is assigned a number expressing the relative structural effect on a pavement for a specified pavement type (R = Rigid pavement and F = Flexible pavement) and a standard subgrade category (A = High, B = Medium, C = Low, D = Ultra low). The concept of a single-wheel load has been employed to define the lading 941

gear and pavement interaction without specifying pavement thickness as an ACN parameter. This is done by equating the thickness derived for a specified airplane landing gear to the thickness derived for a single wheel load at a standard tire pressure of 181 psi (1.25 MPa). PCN is a number expressing the relative load-carrying capacity of a pavement. A particular PCN value can support an aircraft that has an ACN value equal to or less than the pavement’s PCN value for unrestricted operations without weight restrictions. The PCN value is for reporting pavement strength only and cannot be used for pavement design or as a substitute for pavement evaluation. However, ICAO has not specified regulatory guidance on how to determine a PCN value because many member countries are reluctant to agree on an international standardized method for pavement evaluation (FAA 2006b, Stet & Beuving 1993, 2004, Stet & Verbeek 2005, DeBord et al. 1998, ICAO 1983). Stet and Verbeek (2005) further discussed the recent and future developments of this methodology. An alpha-factor is used in the ACN procedure to account for load repetitions and coverages for different loading gears in flexible pavements (FAA 2004a, Hayhoe 2006). Due to the inherent limitations of the existing pavement design and evaluation procedure for some new types of larger airplanes (e.g., B-777 and A380-800), full-scale research projects have been undertaken to develop an alternative mechanistic-empirical procedure using layered elastic design approaches. The ICAO ACN study group (ACNsg) has initiated an investigation study on the impact of revising ACNs on the current ACN/PCN methodology based on full-scale test results. PCN assignments are related to design methodologies. Since the current ACN/PCN method does not dictate a specific design method for PCN assignment, the technically derived PCN values are likely to vary to a great exent. Many factors which have a profound influence on PCN assignment include: the PCN method used, the use of empirical or mechanistic based methods, the evaluation method used, the pavement structural life, the method to derive an annual traffic volume, the method to backcalculate material properties, and different transfer functions, etc. Stet and Verbeek (2005) also demonstrated the PCN values can vary over 200 percent using different theories and evaluation technologies. 3

GOODNESS STUDY OF EXISTING BACKCALCULATION RESULTS

Since Nondestructive Deflection Testing (NDT) has been recommended to evaluate the overall structural capacity of an existing airport pavement (FAA 2004b), a goodness study of the existing backcalculation results using the Long-Term Pavement Performance (LTPP) database was conducted (Wu 2006, Lin 2007). Starting from 1987, the LTPP program has been monitoring more than 2,400 asphalt and Portland cement concrete pavement test sections across the North America. Very detailed information about original construction, pavement inventory data, materials and testing, historical traffic counts, performance data, maintenance and rehabilitation records, and climatic information have been collected. There are 8 general pavement studies (GPS) and 9 specific pavement studies (SPS) in the LTPP program. Of which, only those GPS (3 to 5 for Portland cement concrete) pavements were used in this study. Initially, the DataPave 3.0 program was used to prepare the database. However, in order to obtain additional variables and the latest updates of the data, the LTPP DataPave Online (Release 18.0) database (retrieved from http://www.datapave.com) became the main source for this study. The database is currently implemented in an information management system (IMS) which is a relational database structure using the Microsoft Access program (FHWA 2004). Automatic summary reports of the pavement information may be generated from different IMS modules, tables, and data elements. The thickness of pavement layers was obtained from the IMS Testing module rather than the IMS Inventory module to be consistent with the results of Section Presentation module in the DataPave 3.0 program. 3.1 Comparison of laboratory tested and backcalculated moduli of PCC pavements The modulus of each pavement layer backcalculated using the ERESBACK 2.2 program (FHWA 2001) was retrieved from the IMS Monitoring module. The laboratory tested layer 942

moduli were compared with the backcalculated moduli so as to have a better understanding of their associated variability in this study. The variability of the relationship between the laboratory tested (or static) and backcalculated (or dynamic) moduli could not be ignored. Figures 1a–c depict the average ratios are approximately 1.4, 1.5, and 1.5 for surface, subbase, and subgrade layers for dense liquid foundation, respectively (Lin 2007). Note that very few laboratory tested modulus of subgrade reaction are available in the database. Likewise, Figures 1d–f depict the average ratios are roughly 1.0, 1.1, and 3.0 for surface, subbase, and

(b)

100

200

300

400

Backcal. Modulus (MPa)

0

0

20000

60000

Backcal. Modulus (MPa)

500

(a)

0

20000

40000

60000

80000

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PCC Modulus (MPa)

200

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400

500

Subbase Modulus (MPa)

(d)

60000 20000 0

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20

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Backcal. k (MPa/m)

80

Backcal. Modulus (MPa)

100

(c)

0

20

40

60

80

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20000

Subgrade k (MPa/m)

60000

80000

(f)

0

400 300 200 100 0

100

200

300

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Backcal. Modulus (MPa)

500

500

(e)

Backcal. Modulus (MPa)

40000

PCC Modulus (MPa)

0

100

200

300

400

500

0

Subbase Modulus (MPa)

100

200

300

400

500

Subgrade Modulus (MPa)

Figure 1. Comparison of laboratory tested and backcalculated layer moduli of: (a) surface, (b) subbase, and (c) subgrade for dense liquid foundation; and (d), (e), (f) for elastic solid foundation, respectively.

943

subgrade layers for elastic solid foundation, respectively. It is noted that the recommendation of dividing the backcalculated modulus of subgrade reaction (or k-value) by 2 as the static k-value by AASHTO (AASHTO 1993) may be a reasonable choice, though more research study is still needed to reduce the variability. 3.2 Relationship between elastic modulus and modulus of subgrade reaction For practical concerns, a relationship between the elastic modulus and the modulus of subgrade reaction is often needed. According to the literature (FHWA 2001), the following empirical relationship was developed from the GPS and SPS data analysis: k = 0.296Es Statistics: R2 = 0.872, SEE = 9.37, N = 596

(1)

In which, k is the modulus of subgrade reaction (MPa/m), Es is the subgrade elastic modulus (MPa), R2 is the coefficient of determination, SEE is the standard error of estimates, and N is the number of observations. According the available GPS data, very good agreements have been achieved using the above relationship. Nevertheless, Barenberg (2000) has indicated the theoretical difference using elastic solid foundation or dense liquid foundation for having same maximum deflections in backcalculation analysis. Assuming a Poisson ratio of 0.5 for subgrade, a Poisson ratio of 0.15 for concrete slab, and the elastic modulus of the slab is 4000 ksi (27.6 GPa), the following relationship was derived after some simplification process. In which, k is the modulus of subgrade reaction (pci), Es is the subgrade elastic modulus (psi), and h is the slab thickness (in). The effect of slab thickness has to be considered in such a relationship. (Note: 1 psi = 6.89 kPa, 1 in = 2.54 cm, and 1 psi/in = 1 pci = 0.271 MPa/m) Es 4/3 = 283.7 * h * k

(2)

300 200

Slab Thickness 18~23 cm 23~27 cm 27~32 cm 32~37 cm

100

Backcalculated Esg (MPa)

400

500

The aforementioned relationship was further verified by comparing the backcalculated subgrade elastic moduli with the backcalculated modulus of subgrade reaction from the LTPP database. Slab thickness did have significant effects on this relationship as shown in Figure 2. Consequently, the following relationship is developed using regression techniques. In which, k is the modulus of subgrade reaction (MPa/m), Es is the subgrade elastic modulus (MPa), and h is the slab thickness (cm).

20

40

60

80

100

120

140

160

Backcalculated k-value (MPa/m)

Figure 2. Comparison of elastic solid foundation versus dense liquid foundation based on backcalculated results.

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Es = 0.9015(k * h)3/4 Statistics: R2 = 0.9524, SEE = 15.87, N = 138

(3)

The aforementioned approach is based on the recommendation that the mean value minus one standard deviation (or the so-called 85% confidence level) may be used for obtaining a more conservative evaluation or design input (FAA 2004b, 2006a). Nevertheless, it was found that this proposed procedure is not based on sound statistical principles especially when the probability distribution function of the population is almost always unknown and is not always normally distributed. In engineering practice, a subset of the population or a random sample is often collected to represent the population characteristics of interest. Chebyshev provides the following relationship between the standard deviation and the dispersion of the probability distribution of any random variable. According to Chebyshev’s Rule, for any random variable X with mean ( μ) and variance (σ2) the probability that a random variable differs from its mean by at least k standard deviations is less than or equal to 1/k2, in which k > 1 (19–20). P ( X − μ ≥ κσ ) ≤

1 κ2

(4)

For example, the probability that any random variable differs from its mean by at least two standard deviations is no greater than 1/4, however, this probability is less than 0.05 for a normal random variable. Since the population distribution is unknown and is not necessarily normal in the above approach, the probability that a given random variable differs from its mean by at least one standard deviation is no greater than 1 (using k = 1). In other words, the above approach will result in a PCN value in which 0% of the runway length has a value equal to or higher than it. The so-called 85% confidence level (or reliability) is an over-statement and is only true when the population is normal. 4

DEVELOPMENT OF A PROPOSED ROBUST APPROACH

Consequently, the concepts of random sampling, central limit theorem, and confidence intervals for hypothesis testing were proposed for establishing the evaluation or design inputs to derive a more consistent and repeatable PCN value. This proposed robust approach include the following steps: (a) determine the number of sample units to be surveyed; (b) determine a representative design input for the entire runway; (c) obtain a single PCN value as usual. 4.1 Determination of the number of sample units to be surveyed Let X1, X2, …, Xn be a random sample from a population of any distribution shape with unknown mean μ and known variance σ2. If the sample size n is large (say n ≥ 30), using − central limit theorem one can find that the sample mean X has an approximate normal dis2 tribution with mean μ and variance σ /n. Since the standard deviation σ is often unknown and can be estimated from sample standard deviation S, thus the unknown population mean − μ can be estimated from the sample mean X and the estimation error (e) can be calculated using the following expression. In which, Zα/2 is the 100α /2 percentage point of the standard normal distribution; n is the number of samples; and α is the significance level or the type I error probability (Montgomery & Runger 2003, Lin & Chen 2006). X − μ = Zα / 2

S ≤e n

(5)

Furthermore, since the sample size n is usually small in most engineering problems and the population may be finite, the estimation error (e) becomes as follows: 945

X − μ = tn −1, α / 2

S n

N −n ≤e N −1

(6)

where tn–1,α /2 is the upper 100α /2 percentage point of the t distribution with n–1 degrees of freedom, N is the total number of sample units in the population, and N − n N −1 is the finite population correction factor. By rearranging the aforementioned equation and setting tn–1,α /2 = 2 for 95% confidence level (2-tail), one can obtain the following equation in determining the number of sample units to be inspected: n=

NS 2 (e / 4 )( N − 1) + S 2 2

(7)

Note that the above equation has been adopted by the American Society for Testing and Materials (ASTM) in pavement condition index (PCI) procedure (Shahin 1994, ASTM 1998) and is the result of simple statistical inferences. 4.2 Determination of a representative design input and a PCN value for the entire runway Since the material properties of an existing runway pavement may vary at different locations, subdividing the entire runway into many homogeneous sub-sections does not automatically solve the issue of random sampling and the need to have a reliable design input. According to the aforementioned statistical concept, a single representative design input for the entire runway pavement may be determined by the lower limit of 95% confidence level (1-tail) using the following expression:

μ = X − tn −1,α

S n

(8)

Thus, it is recommended that after the raw NDT data has been successfully backcalculated, one can compute the grand mean ( X ), sample standard deviation (S), sample size (n), and the lower 100α percentage point of the t distribution with n–1 degrees of freedom (tn–1,α ) (normally α = 0.05) and then determine the representative design inputs including the layer moduli of the surface and subgrade using the above equation. Subsequently, a PCN value for the entire runway is obtained as usual. 5

A CASE STUDY FOR TECHNICAL EVALUATION OF RIGID PAVEMENTS

To illustrate the potential problems of the current technical evaluation method and the advantages of the proposed robust approach in determining PCN values for rigid pavements, the following case study was conducted. Suppose a rigid airfield runway pavement with an effective subgrade k-value of 200 pci (54.2 MPa/m) and a slab thickness of 14 inches (35.56 cm). Assume the concrete has a modulus of rupture of 700 psi (4.82 MPa), an elastic modulus of 4,000,000 psi (27.56 GPa), and a Poisson’s ratio of 0.15. The runway has a parallel taxiway, and additional fuel is generally obtained at the airport before departure. The pavement life is estimated to be 20 years from the original construction. The traffic data as given in Table 1 was obtained from the Appendix 2, Advisory Circular AC 150/5335-5 A (FAA 2006b). Since additional fuel is generally obtained at the airport, and there is a parallel taxiway, thus, passes to traffic cycles (P/TC) = 1; traffic cycles to coverages (TC/C) = pass to coverages (P/C); and coverages (C) = annual departures * 20 years ÷ TC/C. The resulting coverages for each airplane are also listed in Table 1. The required thickness for each airplane at the operating weight and frequency is determined using the COMFAA program (FAA 2003, 2006b). Based on the required thickness for each airplane, the critical airplane was determined as the B747-400. All departures of the other traffic were converted to the B747-400 equivalent and the total equivalent 946

annual departures of the critical aircraft are 7,424. Since, P/TC = 1; P/C = 3.46; TC/C = 3.46; thus the anticipated total coverages of the critical aircraft = 7,424 * 20 years ÷ 3.46 = 42,913. By adjusting the gross airplane weight iteratively until the known pavement thickness 14 in. (35.56 cm) is obtained, the maximum allowable gross weight of the critical aircraft (B747-400) is determined as 762,000 pounds (3.39 MN). In which, the following additional parameters were assumed: percent weight on the main gear = 95%, tire pressure = 200 psi (1.38 MPa), and tire contact area = 260.4 in2 (0.168 m2). By switching the COMFAA program back to the ACN mode and entering in the allowable gross weight, an ACN of 61.3/R/C is obtained. The final recommended runway rating is PCN 61/R/C/W/T. Note that the tire pressure code for rigid pavement is normally set as W. Nondestructive Deflection Testing (NDT) was often conducted to determine the overall structural capacity of an existing airport pavement (FAA 2004b). Suppose that a total of 57 elastic modulus values of the concrete slab were successfully backcalculated. Based on the current recommended procedures (FAA 2004b, Chou et al. 2007), one could divide the entire runway into different sets of several structurally homogeneous sub-sections. For example, Figure 3 depicts different evaluation methods using grand mean, the averages of 5 subsections Table 1.

Rigid airfield pavement traffic example.

Airplane

Operating weight, lbs

Tire pressure, psi

ACN

P/C*

Annual departures

Coverages

B727-200 B737-300 A319-100

185,000 130,000 145,000

148 195 173

55 38 42

2.92 3.79 3.18

400 6,000 1,200

2,740 31,662 7,547

B747-400 B767-300ER

820,000 370,000

200 190

68 58

3.46 3.60

3,000 2,000

17,341 11,111

DC8-63 A300-B4 B777-200

330,000 370,000 600,000

194 205 215

62 67 77

3.35 3.49 4.25

800 1,500 300

4,776 8,595 1,412

* Rigid P/C determined at 95 percent of gross load on main gear. (Note: 1 lbf = 4.45 N, 1 psi = 6.89 kPa). 10 Subsections

6.50E+06

All Separated Data Grand Mean

6.00E+06

5 Subsections

5.50E+06 5.00E+06 4.50E+06

Epcc (psi)

4.00E+06 3.50E+06 3.00E+06 2.50E+06 2.00E+06 1.50E+06 1.00E+06 5.00E+05 0.00E+00 0

5

10

15

20

25

30

35

Test Location

Figure 3.

Variation of the backcalculated moduli of the slab.

947

40

45

50

55

60

and 10 subsections, all separated data. Figure 4 depicts the cumulative frequency of different evaluation methods and the resulting representative Epcc values. With random sampling and random variability in mind, the representative elastic moduli of the concrete slab (Epcc) are summarized in Table 2 using grand mean (Method I), 85% confidence of the averages of 5 subsections (Method III) and 10 subsections (Method IV), and 85% confidence of all separated data (Method V) according to the literature (Chou et al. 2007). In addition, Method II uses grand mean minus one standard deviation (or the so-called 85% confidence level) whereas Method VI uses the lower limit of the proposed 95% confidence level method (1-tail). In which, the grand mean X = 3,670,764 psi (25.29 GPa), sample standard deviation S = 1,272,451 psi (8.77 GPa), sample size n = 57, tn–1,α = 2 for 95% confidence level (1-tail). The slab modulus of rupture (Mr, psi) was estimated using the following equation: (Note: 1 psi = 6.89 kPa) Mr = 43.5 × Epcc/106 + 488.5

(9)

Likewise, the maximum allowable gross weight of the B747-400 aircraft (with 42,913 coverages) for each case is subsequently determined. As expected, the resulting runway PCN ratings range from PCN 47.8/R/C/W/T to 55/R/C/W/T as also shown in Table 2. Based on the ACNs in Table 1, it can be seen that several airplanes would be restricted in their operations on this runway if their respective ACNs are higher than the derived PCN of 48/R/C to 55/R/C. It is 6.00E+06

5.00E+06

Epcc (psi)

4.00E+06

3.00E+06

All Separated Data 5 Subsections

2.00E+06

10 Subsections Grand Mean 1.00E+06

0.00E+00 0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cumulative Frequency

Figure 4.

Cumulative frequency of different evaluation methods (Note: 1 psi = 6.89 kPa).

Table 2.

Results of using different evaluation methods.

Method no.

Different evaluation methods

Representative Epcc, psi

Estimated Mr, psi

Calculated allowable gross weight, lbs

PCN

I II III IV V VI

Grand mean Grand mean—1 Std.Dev. 5 Subsections (85%) 10 Subsections (85%) All separated data (85%) 95% Confidence

3.67 × 106 2.40 × 106 3.04 × 106 2.75 × 106 2.05 × 106 3.33 × 106

648.1 592.8 620.7 608.1 585.1 585.1

700,000 640,000 671,000 656,000 632,000 684,000

55.0 48.6 51.9 50.3 47.8 53.3

(Note: 1 lbf = 4.45 N, 1 psi = 6.89 kPa).

948

apparent that the pavement is inadequate to accommodate the existing traffic or the operating weights have to be restricted. Knowing that the goodness of existing backcalculation results is still in question for many occasions as previously described, it is desirable to use a robust approach to arrive at a more reliable PCN value for the entire runway. Using the lower limit of the proposed 95% confidence level method (1-tail) results in a PCN rating of 53.3/R/C/W/T. 6

CONCLUDING REMARKS

Although it has been clearly recommended that the engineer should simultaneously consider the mean and standard deviation in the selection of an evaluation or design input value, many evaluation and design procedures currently only use the mean value in the analysis. According to the Advisory Circular’s recommendation, the mean value minus one standard deviation (or the so-called 85% confidence level) may be used to obtain a more conservative evaluation or design input. Nevertheless, it was found that this proposed procedure is not based on sound statistical principles especially when the probability distribution function of the population is almost always unknown and is not necessarily normal. Consequently, the concepts of random sampling, central limit theorem, and confidence intervals for hypothesis testing were adopted. It was proposed that a single representative design input for the entire runway pavement be determined by the lower limit of 95% confidence level (1-tail) to derive a more consistent and repeatable PCN value. A case study was conducted to illustrate the potential problems of the existing ACN/PCN procedure and the benefits of the proposed revisions. The completion of this study will, hopefully, provide a sound basis for reporting the airfield pavement bearing strength. The proposed approach based on sound statistical principles could be similarly implemented in many engineering practices as well. ACKNOWLEDGMENTS This study was sponsored by National Science Council, Taiwan. The authors would like to acknowledge Ms. Chia-Huei Lin for her hard work in the goodness study of existing backcalculation results. REFERENCES AASHTO 1993. AASHTO Guide for Design of Pavement Structures. American Association of State Highway and Transportation Officials. ASTM 1998. “Standard Test Method for Airport Pavement Condition Index Surveys.” American Society for Testing and Materials D 5340-98. Barenberg 2000. “Introduction to Concrete Pavement Design.” Proceedings, A Workshop on Modern Concrete Pavement Design. Tamkang University, Taiwan, May 3–4. Chou, C.P., Wang, S.Y. & Tsai, C.Y. 2007. “Methodology of Applying Heavy Weight Deflectometer for the Calculation of Runway Pavement Classification Number.” Transportation Research Record 1990, Journal of the Transportation Research Board. Transportation Research Board, Washington, D.C., pp. 57–64. DeBord, K.J., Gervais, E.L. & Jenkinson, W.W. 1998. Precise Methods for Estimating Pavement Classification Number. Document No. D6-82203, Boeing Commercial Airplane Group, Airport Technology Organization (B-B210). FAA 2003. Development of a Computer Program—COMFAA—for Calculating Pavement Thickness and Strength, Federal Aviation Administration. FAA 2004a. Alpha Factor Determination from NAPTF Test Data. Letter Report, Airport Technology Research and Development Branch, AAR-410, Federal Aviation Administration. FAA 2004b. Use of Nondestructive Testing in the Evaluation of Airport Pavement. Advisory Circular 150/5370-11A, Federal Aviation Administration. FAA 2006a. Airport Pavement Design and Evaluation, Advisory Circular 150/5320-6D (including changes 1 ~ 4), Federal Aviation Administration.

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FAA 2006b. Standardized Method of Reporting Airport Pavement Strength. Advisory Circular 150/5335-5A, Federal Aviation Administration. FHWA 2001. Backcalculation of Layer Parameters for LTPP Test Sections- Slab on Elastic Solid and Slab on Dense-Liquid Foundation Analysis of Rigid Pavements. Publication No. FHWA-RD-00-086. FHWA 2004. Long-Term Pavement Performance Information Management System: Pavement Performance Database Users Reference Guide. Publication No. FHWA-RD-03-088. Hayhoe, G.F. 2006. Alpha Factor Determination Using Data Collected at the National Airport Pavement Test Facility. DOT/FAA/AR-06/7, Federal Aviation Administration. ICAO 1983. Aerodrome Design Manual. Part 3, Pavements, 2nd Edition, International Civil Aviation Organization. Lin, C.H. 2007. Development of Performance Prediction Models for Rigid Pavements Using LTPP Database. Master Thesis, Tamkang University, Taiwan. (In Chinese) Lin, H.L. & Chen, J.C. 2006. Applied Statistics. Third Edition, Yeh Yeh Book Gallery, Taipei, Taiwan. (In Chinese) Montgomery, D.C. & Runger, G.C. 2003. Applied Statistics and Probability for Engineers. Third Edition, John Wiley & Sons, Inc., New York, NY. Shahin, M.Y. 1994. Pavement Management for Airports, Roads, and Parking Lots. Chapman & Hall, New York, NY, p. 19. Stet, M. & Beuving, E. 1993. “ICAO’s ACN-PCN Method and Aircraft—Pavement Interaction.” Proceedings, ASCE Specialty Conference: Airport Pavement Innovations, Theory to Practice. Edited by Hall, J.W. Jr., Vicksburg, Mississippi, September 8–10, p. 75. Stet, M. & Beuving, E. 2004. “The PCN Runway Strength Rating and Load Control System.” CROW report 0409. Stet, M. & Verbeek, J. 2005. “The PCN Runway Strength Rating and Load Control System.” Proceedings, 1st European Airport Pavement Workshop, CROW, The Netherlands, May 11–12.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Influence of unbound materials on flexible pavement performance: A comparison of the AASHTO and MEPDG methods C.W. Schwartz University of Maryland—College Park, Maryland, USA

ABSTRACT: Anecdotal reports have suggested that the new Mechanistic-Empirical Pavement Design Guide (MEPDG) assigns less structural credit to unbound materials than does the empirical AASHTO procedure. A limited sensitivity study was performed to quantify the effect of base layer thickness and stiffness and subgrade quality on service life as predicted by the AASHTO and MEPDG procedures. The study found that the AASHTO and MEPDG methods agreed well at low to moderate traffic levels but diverged at higher traffic volumes. The sensitivity of predicted service life to unbound granular base and subbase properties was found for the scenarios in the study to be consistently higher for the AASHTO method than for the MEPDG. Limited field data suggest that the actual sensitivity may lie somewhere between the limits of the two design methods. 1

INTRODUCTION

Flexible pavements rely upon the contributions of all layers toward the overall structural capacity of the section. For pavements designed according to the AASHTO design procedure, the granular base and subbase layers may contribute as much as 50% of the total structural number for the section. Clearly, the performance or service life of flexible pavements will therefore be quite sensitive to the thickness and properties (resilient modulus/layer coefficient) of the unbound layers as well as to the stiffness of the underlying unbound subgrade. Anecdotal reports have suggested that the new Mechanistic-Empirical Pavement Design Guide (MEPDG) assigns less structural credit to the unbound layers than does the empirical AASHTO procedure (e.g., Masad, 2004; El-Basyouny et al., 2005; Carvalho & Schwartz, 2006, Kim et al., 2006). In order to investigate this more definitively, a set of analyses has been performed to quantify the effect of base layer thickness and material properties and subgrade quality on service life as predicted by the AASHTO and MEPDG procedures. Limited comparisons are also made against field performance of actual pavement sections. 2

SENSITIVITY ANALYSIS

Sensitivity of flexible pavement performance to base thickness, base resilient modulus, and subgrade resilient modulus was investigated for a scenario based loosely on the conditions at the AASHO Road Test (AASHO, 1961). This sensitivity study is intentionally limited and focused only on the key unbound material properties. More comprehensive studies of the sensitivity of MEPDG performance predictions to a wide range of flexible pavement design inputs can be found in Masad (2004), El-Basyouny et al. (2005a, 2005b), Carvalho & Schwartz (2006), Graves & Mahboub (2006), and Kim et al. (2006). All evaluations in this study employed the 1993 AASHTO Pavement Design Guide (AASHTO, 1993) and Version 1.00 of the MEPDG (AASHTO, 2008). The baseline scenario consisted of asphalt concrete over a crushed stone granular base over an A-6 compacted embankment subgrade. The variables in the sensitivity analysis were the asphalt thicknesses of 7.6, 15.2 and 22.9 cm (3, 6, and 9 in.), granular base thickness from 7.6 to 61.0 cm (3 to 24 inches), granular 951

base moduli ranging 137.8 to 310.1 MPa (20,000 to 45,000 psi), and subgrade resilient moduli ranging 13.8 to 86.1 MPa (2,000 to 12,500 psi) (note: the AASHTO and MEPDG design methods are both formulated in terms of English Customary units, so these are used throughout this paper). Other inputs for the design methodologies are summarized in Table 1. Every effort was made to achieve compatible inputs across both design methods. In the case of the MEPDG, Level 3 inputs were specified for all materials. Compatibility of the performance criteria was particularly problematic, as the AASHTO and MEPDG definitions of serviceability are fundamentally different. For the AASHTO procedure, a value for ΔPSI of 1.7 (initial PSI = 4.2, terminal PSI = 2.5) was taken as typical of values used in practice (e.g., MDSHA, 2006). For the MEPDG, total rutting is the controlling distress for this pavement scenario. The performance criterion for total rut depth RD was set at 0.5 inches at 50% reliability based on a survey of pavement experts conducted by Witczak (2004). Service life is defined as the number of 18 K axle loads required to reach the respective performance criteria. Figure 1 summarizes the variations in predicted service life as a function of subgrade resilient modulus for three different asphalt thicknesses (D1 = 7.6, 15.2 and 22.9 cm or 3, 6, and 9 in.). The granular base thickness was fixed at 25.4 cm (12 in.), and all other properties were set to the baseline values in Table 1. As is clear in the figure, there is quite good agreement between the two design methods both in terms of service life and its sensitivity to subgrade stiffness. The AASHTO procedure consistently predicts a modestly longer service life than does the MEPDG, particularly for higher quality stiff subgrades, but this could easily be due to the differences in their respective performance criteria. Figure 2 illustrates the trends in predicted service life as a function of granular base modulus for three different asphalt thicknesses (D1 = 7.6, 15.2 and 22.9 cm or 3, 6, and 9 in.). The granular base thickness D2 was fixed at 12 inches, and all other properties were set to the baseline values in Table 1. There is good agreement in the trends of the two design methods for the thin (7.6 cm or 3 in.) and medium (15.2 cm or 6 in.) asphalt layer cases. However, for the thick (22.9 cm or 9 in.) asphalt case, the sensitivity of service life to base modulus for the AASHTO design procedure is much greater than that for the MEPDG, as indicated by the steeper slope in the curve. Moreover, there is a crossing point for the thick asphalt case; the AASHTO procedure predicts much longer service life for pavements with high quality stiff bases than does the MEPDG, but the reverse is true for low quality bases in this scenario. These results from the thick asphalt case should be viewed with some caution, though, as the

Table 1.

Design inputs for baseline scenarios (1 in. = 25.4 mm; 1 psi = 6.89 kPa).

Property

AASHTO

MEPDG

Performance criterion

ΔPSI = 1.7

Reliability Traffic type

50% 18 K ESALs

Climate

Drainage coefficient m2 = 1*

Asphalt

Thickness D1 = 3, 6, 9 in. Layer coefficient a1 = 0.44* Thickness D2 = 12 inches Modulus EBS = 30,600 psi a2 = 0.14* CBR = 3.3* MR = 5000 psi

Total rut depth RD = 0.5 in. (controlling distress) 50% Class 8 only 2–18 K load axles per truck Ottawa, IL climate file 20 ft GWT depth Thickness = 3, 6, 9 in. AASHO mixture properties Thickness = 12 inches Resilient modulus MR = 30,600 psi AASHO gradation, compaction MR = 5000 psi AASHO gradation, plasticity, compaction

Granular base

Subgrade

*

Consistent with properties at original AASHO Road Test.

952

Service Life N18 (x1M)

50 40 AASHTO D1 = 9

30

MEPDG D1 = 9 AASHTO D1 = 6

20

MEPDG D1 = 6 AASHTO D1 = 3 MEPDG D1 = 3

10 0 0

5000

10000

15000

Subgrade Mr (psi)

Figure 1.

Predicted service life vs. subgrade resilient modulus (1 psi = 6.89 kPa).

Service Life N18 (x1M)

50

40 AASHTO D1 = 9 MEPDG D1 = 9

30

AASHTO D1 = 6 MEPDG D1 = 6

20

AASHTO D1 = 3 MEPDG D1 = 3

10

0 20000

30000

40000

50000

Base Modulus (psi)

Figure 2.

Predicted service life vs. granular base modulus (1 psi = 6.89 kPa).

traffic levels are well beyond those in the AASHO Road Test upon which the AASHTO empirical design procedure is based. Figure 3 depicts predicted service life as a function of granular base thickness for the three asphalt thicknesses. All other properties were set to the baseline values in Table 1. There is good agreement in the trends of the two design methods for the thin (7.6 cm or 3 in.) and medium (15.2 cm or 6 in.) asphalt layer cases at thin to moderate base thicknesses; however, the AASHTO predicts substantially higher benefit (i.e., longer service life) than does the MEPDG for base layers thicker than about 25.4 to 45.7 cm (12 to 18 in.). For the thick (22.9 cm or 9 in.) asphalt case, the agreement between the AASHTO and MEPDG procedures is very poor; the sensitivity of service life to base thickness is extremely high for the AASHTO predictions and much lower for the MEPDG method. Overall conclusions drawn from the results of this limited sensitivity study include: (1) there is good agreement in the service life predictions from the AASHTO and MEPDG methods for cumulative traffic levels less than about 5 million 40-kN (18-kip) axle loads; (2) at higher traffic levels, the two design methods attribute dramatically different structural credit to the granular base both in terms of layer thickness and stiffness, with the AASHTO predicting much higher service life sensitivity to the granular base than does the MEPDG; (3) for high quality unbound materials (i.e., stiff subgrades, stiff and/or thick granular bases), the AASHTO procedure consistently predicts longer service life—i.e., attributes greater structural benefit to the unbound materials (although this could be due in part to the different 953

ways that service life is defined in the two methods). Recall that total rutting is the governing distress in the MEPDG predictions for these scenarios, which are all based loosely on the AASHO Road Test conditions. The overall conclusions could be different for scenarios having other controlling distresses (e.g., fatigue cracking). 3

AASHO ROAD TEST

The results in Figure 1 through Figure 3 show that the unbound material influence on service life as predicted by the AASHTO and MEPDG methods differs significantly under some conditions. However, demonstrating that the two methods are different does not address the question of which if either is correct. This question can only be answered by comparing predictions against field pavement performance. The difficulty, of course, is finding sets of field sections in which base thickness, base modulus, and/or subgrade modulus are varied at fixed values of the asphalt mixture, traffic, and other parameters. One source of these data is the original AASHO Road Test. Each flexible pavement test loop had fixed traffic but varying thicknesses of asphalt, granular base, and granular subbase. Lane 1 in Test Loop 4 was selected for evaluation, with key pavement section properties summarized in Table 2. Since all sections were constructed on the same embankment material, the influence of subgrade resilient modulus of course cannot be investigated. The traffic on all sections consisted of 18 kip single axle loads (two axles per truck), eliminating the need to compute ESALs in the AASHTO procedure. Measured service life at the AASHO Road Test was determined as the number of axle loads to reach a PSI value of 2.5. The AASHO experiment for Loop 4 implemented a full factorial combination of the asphalt, base, and subbase thicknesses, making it possible to evaluate the sensitivity of service life to local variations of each variable. A local sensitivity index Si for the influence of

Service Life N18 (x1M)

50

40 AASHTO D1 = 9 MEPDG D1 = 9

30

AASHTO D1 = 6 MEPDG D1 = 6

20

AASHTO D1 = 3 MEPDG D1 = 3

10

0 0

5

10

15

20

25

Base Thickness (in)

Figure 3.

Predicted service life vs. granular base thickness (1 in. = 25.4 mm). Table 2. Section properties for Loop 4 Lane 1 at AASHO Road Test (AASHO, 1961) (1 in. = 25.4 mm; 1 psi = 6.89 kPa). Properties Material

Thickness (in.) AASHTO

Asphalt concrete Granular base Granular subbase

3, 4, 5 0, 3, 6 4, 8, 12

a1 = 0.44 a2 = 0.14 a3 = 0.11

954

MEPDG Level 3 defaults MR = 30,600 psi MR = 15,200 psi

layer thickness Di around some reference condition DiR can be defined in normalized terms as (Saltelli et al., 2000): Si =

∂N18 ⎛ DiR ⎞ ⎜ ⎟ ∂Di ⎝ N18R ⎠

(1)

in which N18R is the service life measured/predicted for the reference condition and the partial derivative term is computed using a centered finite difference approximation. Equation can be interpreted as the percentage change in service life caused by a given percentage change in layer thickness. Figure 4 summarizes the local sensitivity index values computed around the reference condition D1 = 10.1 cm (4 in.), D2 = 7.6 cm (3 in.), and D3 = 20.3 cm (8 in.). The sensitivity of service life to asphalt layer thickness D1 is essentially the same for the AASHOmeasured and the AASHTO- and MEPDG-predicted values. This agreement breaks down for the granular base and subbase thicknesses D2 and D3, however. Figure 4 shows that the AASHO measured sensitivities for the granular layers are substantially higher than for either the AASHTO or MEPDG predictions; in fact, the measured sensitivity for the granular subbase thickness is even higher than that for the asphalt thickness. Although lower than the measured sensitivity, the AASHTO predicted sensitivities for the granular layer thicknesses are consistently more than twice as large as those for the MEPDG predictions. One complication in the interpretation of Figure 4 is that the modulus of the granular base material is approximately twice that of the granular subbase. This leads to some interactions as the effective layer stiffness of the combined granular materials will be a function of their relative thicknesses and moduli. The equivalent layer stiffness arguably provides a better measure for evaluating the overall influence of the granular materials on service life. Concepts similar to the Odemark method (Ullidtz, 1998) can be used to determine the equivalent stiffness for a homogeneous granular layer having a thickness equal to the combined granular base and subbase thicknesses. The combined moment of inertia I23 for the granular base and subbase thicknesses D2 and D3 can be determined using simple transformed section techniques with the subbase resilient modulus ESB as reference. The equivalent layer stiffness (EI)equiv can then be expressed as: ( EI )equiv = ESB I 23

(2)

The variations of service life with combined granular layer stiffness are illustrated in Figure 5. Note again that the differences in the absolute magnitudes of the N18 values may be due to the inconsistent ways that service life is defined in the AASHO (terminal PSI = 2.5),

6

Sensitivity Index

5 4

AASHO (measured) AASHTO 93

3

MEPDG

2 1 0 D1

D2

D3

Layer Thickness

Figure 4. Local sensitivity of service life to layer thickness for the AASHO Road Test sections (Loop 4, Lane 1).

955

3" Asphalt Thickness 1600 AASHO (Measured)

Service Life N18 (x1000)

1400

AASHTO 93 MEPDG

1200 1000 800 600 400 200 0 0

5000

10000

15000

Equivalent Granular Stiffness (EI)equiv (lb-in2 x 1000)

Figure 5. Service life vs. equivalent granular layer stiffness for the AASHO Road Test sections (Loop 4, Lane 1) (1 in. = 25.4 mm; 1 lbf = 4.448 N). AASHO (Measured)

1.2

AASHTO 93 MEPDG

Normalized Sensitivity

1.0 0.8 0.6 0.4 0.2 0.0 3" AC

4" AC

5" AC

Figure 6. Local sensitivity of service life to equivalent layer stiffness for the AASHO Road Test sections (Loop 4, Lane 1) (1 in. = 25.4 mm).

AASHTO (ΔPSI = 1.7), and MEPDG (RD = 0.5 inches) data sets. Nonetheless, the service life predicted by the MEPDG clearly varies insignificantly with effective granular layer stiffness while the service life predicted by the AASHTO methodology varies substantially. The measured data, although showing some degree of scatter, exhibit a slope for the overall trend line that is about midway between the MEPDG and AASHTO curves. Local sensitivity indices computed using Equation 1 for service life vs. equivalent granular layer stiffness are summarized in Figure 6 for each of the three asphalt thicknesses. The trends in Figure 6 are much more consistent than those for layer thickness shown previously in Figure 4. There is now generally good agreement in the sensitivity of service life to equivalent granular layer stiffness between the AASHO-measured and AASHTO-predicted values. These sensitivity values decrease with increasing asphalt thickness, which is sensible— for thicker asphalt conditions, one would intuitively expect less contribution to service life 956

from the granular layers. In contrast, the sensitivity values for the MEPDG predictions are consistently and significantly lower—by between a factor of 3 to more than 10 as compared to the AASHO measurements—and there is no rational trend with asphalt thickness. The overall conclusions to be drawn from the results in Figure 4 through Figure 6 are: (a) equivalent granular layer stiffness seems to provide a clearer and more consistent measure of the contributions of the granular layers when there are multiple granular layers with different thicknesses and moduli; and (b) there is generally good agreement in the normalized sensitivity of service life to equivalent granular stiffness between the AASHO measurement and the AASHTO predictions; and (c) the MEDPG shows negligible sensitivity of service life to equivalent granular stiffness. Of course, these conclusions are all limited to the particular conditions considered in this limited study. 4

UNIVERSITY OF ILLINOIS APT

It is arguably unfair to use the AASHO Road Test data to evaluate the AASHTO vs. MEPDG design methods. The foundation of the empirical AASHTO method is the AASHO Road Test, so one would reasonably expect close agreement between these predictions and measurements (although, as described in the preceding section and illustrated in Figure 5, this may be difficult to demonstrate in practice). Consequently, a second but more limited set of data from full-scale APT experiments conducted at the University of Illinois ATLAS test facility were evaluated (Al-Qadi et al., 2006, 2007; Kwon et al., 2007, 2008). The objective of the Illinois APT experiments was to evaluate the benefits of geogrid reinforcement of granular base layers for reducing total rutting in low volume roads. However, there was a set of three unreinforced control sections (A3, B1, and D3) consisting of asphalt over unreinforced granular base over subgrade in which only the granular base thickness was varied. These can be used for a clear evaluation of sensitivity of service life to base thickness without the complicating interactions from a granular subbase. The input values for the analyses as extracted from Al-Qadi et al. (2006, 2007) and Kwon et al. (2007, 2008) were as follows: − − − −

76 mm (3 in.) asphalt layer with typical PG 64∼22 dense-grade mix properties 203, 305, and 457 mm (8, 12, and 18 inch) granular base thicknesses with MR = 30,000 psi Subgrade with CBR = 4, MR = 6500 psi 44 kN dual wheel axle load, 690 kPa tire pressure, 8 km/h (5 mph) speed

5 AASHTO 93 Normalized Service Life

MEPDG 4

Measured

3

2

1

0 6

8

10

12

14

16

18

20

Granular Base Thickness (in.)

Figure 7. Service life vs. granular base thickness for the Illinois APT control sections (1 in. = 25.4 mm).

957

− Service life defined as the number of axle loads to 25 mm (1 inch) total rut (measurements, MEPDG) or ΔPSI = 1.7 (AASHTO) − 50% reliability As with the AASHO Road Test evaluations, the incompatibilities in the performance criteria among the data sets confuse direct comparisons of service life. In general, though, both the AASHTO and MEPDG service life predictions, although agreeing reasonably well with each other for all three sections, were several orders of magnitude higher than the measured number of axle loads to 1 inch of total surface rut. The reasons for this are unknown at present. In order to make a more meaningful interpretation of the results, the service lives have been normalized by the number of axle loads for the intermediate (20.3 cm or 8 in.) base thickness for each data set. The trends of normalized service life with granular base thickness are summarized in Figure 7. The results in overall terms are qualitatively similar to those from the AASHO Road Test (e.g., Figure 5), with the influence of granular base thickness on service life being only slight for the MEPDG, much more substantial for AASHTO, and intermediate for the measured values. This is also reflected in the normalized sensitivity indices calculated using Equation 1: S2 = 0.59, 2.82, and 4.59 for the MEPDG, measured, and AASHTO values, respectively. 5

CONCLUSIONS

In drawing conclusions from the analysis results, it is important to keep in mind that this study was very limited. It focused only on the key unbound material properties (resilient modulus, layer stiffness) for pavement scenarios having very simple traffic configurations and for which rutting is the controlling distress. The incompatibilities in the ways that the design methods and field studies define service life make direct comparisons difficult. Although the sensitivity analysis portion of the study considered all unbound material influences, comparisons to field measured performance could only be made for granular layer thickness and modulus as the field sections at each site were all on the same subgrade. These caveats notwithstanding, several important conclusions can be drawn from this study: • Service life predictions from the AASHTO and MEPDG design methods are in very good agreement for cumulative traffic levels less than about 5 million 40-kN (18-kip) axle loads; • At higher traffic levels, the two design methods attribute dramatically different structural credit to the unbound materials. The predicted service life in the AASHTO procedure is much more sensitive to granular base thickness and stiffness at high traffic levels than is service life predicted by the MEPDG. Similar differences at higher traffic levels were observed with regard to subgrade stiffness, but these are less pronounced. • For high quality unbound materials (i.e., stiff subgrades, stiff and/or thick granular bases), the AASHTO procedure consistently predicts longer service life—i.e., attributes greater structural benefit to the unbound materials—than does the MEPDG. However, this could be due in part to the different ways that service life is defined in the two methods. • In general terms, the normalized sensitivity of predicted service life to the granular layer properties in the AASHTO procedure is similar to (AASHO Road Test) or somewhat less than (Illinois APT) measured sensitivities. The corresponding sensitivities from the MEPDG were substantially smaller than both the AASHTO and measured values in all cases. It is important that these conclusions be viewed in correct context. The results from this limited study found that the AASHTO and MEPDG methods agree well where expected— low to moderate traffic levels—and diverge where expected—high traffic. Recall that one of the motivations for the development of the MEPDG was a lack of confidence in the extrapolation of the empirical AASHTO equations to traffic levels well beyond those in the underlying AASHO Road Test data. The field data from the AASHO Road Test and the Illinois APT sections suggest that the actual sensitivity of service life to unbound properties may lie between the limits of the two methods—i.e., the AASHTO method appears to overestimate the structural contributions from the granular layers in some cases while the MEPDG may tend to underestimate them. More extensive studies (including scenarios where the controlling 958

distress is other than rutting) and larger sets of field data are needed to confirm this hypothesis. At the very least, however, the very low sensitivities found for the MEPDG suggest that this may be an area that warrants further work, similar to work on other MEPDG enhancements currently underway (e.g., NCHRP Projects 1∼41, 1∼42A, and 9∼30A). ACKNOWLEDGEMENT Mr. Abel Berhe, an undergraduate student at the University of Maryland, assisted in the very early portions of this study. REFERENCES AASHO (1961). “The AASHO Road Test: Report.” Publication 816, No. 61A-61G, Highway Research Board, National Research Council, National Academy of Sciences, Washington, DC. AASHTO. (1993). AASHTO Guide for Design of Pavements Structures, American Association of State Highway and Transportation Officials, Washington, DC. AASHTO (2008). Mechanistic-Empirical Pavement Design Guide: A Manual of Practice. American Association of State Highway and Transportation Officials, Washington, DC. Al-Qadi, I.L., Tutumluer, E., and Dessouky, S. (2006). “Construction and Implementation of Full-Scale Geogrid-Reinforced Flexible Pavement Sections.” Airfield and Highway Pavements: Meeting Today’s Challenges with Emerging Technologies—Proceedings of the 2006 Airfield and Highway Pavement Specialty Conference, Atlanta, GA, pp. 131–142. Al-Qadi, I.L., Tutumluer, E., Kwon, J., and Dessouky, S.H. (2007). “Accelerated Full-Scale Testing of Geogrid-Reinforced Flexible Pavements.” Annual Meetings of the Transportation Research Board, Washington, DC, CD Preprint Paper 07–2317. Carvalho, R., and Schwartz, C.W. (2006). “Comparisons of Flexible Pavement Designs: AASHTO Empirical Versus NCHRP Project 1-37A Mechanistic-Empirical,” Transportation Research Record 1947, Transportation Research Board, National Research Council, Washington, DC, pp. 167–174. El-Basyouny, M.M., Witczak, M.W., Tam, K., Monismith, C., Harman, T., and Brown, S. (2005a) “Verification of the calibrated fatigue cracking models for the 2002 Design Guide,” Journal of the Association of Asphalt Paving Technologists, Vol. 74, pp. 653–695. El-Basyouny, M.M., Witczak, M.W., El-Badawy, S., Timm, D., Dongre, R., Heitzman, M., and Dunning, R. (2005b). “Verification for the calibrated permanent deformation models for the 2002 Design Guide,” Journal of the Association of Asphalt Paving Technologists, Vol. 74, pp. 601–652. Graves, R.C., and Mahboub, K.C. (2006). “Part 2: Flexible Pavements: Pilot Study in Sampling-Based Sensitivity Analysis of NCHRP Design Guide for Flexible Pavements,” Transportation Research Record 1947, Transportation Research Board, National Research Council, Washington, DC, pp. 123–135. Kim, S., Ceylan, H., Gopalakrishnan, K., and Heitzman, M. (2006). “Sensitivity Study of Iowa Flexible Pavements Using the Mechanistic-Empirical Pavement Design Guide,” Annual Meetings of the Transportation Research Board, Washington, DC, CD Preprint Paper 06-2139. Kwon, J., Tutumluer, E., Al-Qadi, I., and Anochie-Boateng, J. (2007). “Geomaterial Characterizations of Full Scale Pavement Test Sections for Mechanistic Analysis and Design.” Soil and Material Inputs for Mechanistic-Empirical Pavement Design: Geotechnical Special Publication 169, American Society of Civil Engineers, Reston, VA, pp. 1–10. Kwon, J., Tutumluer, E., Al-Qadi, I., and Sessouky, S. (2008). “Effectiveness of Geogrid BaseReinforcement in Low-Volume Flexible Pavements.” Geosustainability and Geohazard Mitigation: Geotechnical Special Publication 178, American Society of Civil Engineers, Reston, VA, pp. 1057–1064. Masad, S.A. (2004). “Sensitivity Analysis of Flexible Pavement Response and AASHTO 2002 Design Guide for Properties of Unbound Layers,” M.S. Thesis, Texas A & M University, College Station, TX. MDSHA (2006). Pavement Design Guide, Office of Materials Technology, Maryland State Highway Administration, Hanover, MD. Saltelli, A., Chan, K., and Scott, E.M. (2000). Sensitivity Analysis, John Wiley and Sons Ltd., Chichester, England. Ullitdtz, P. (1998). Modelling Flexible Pavement Response and Performance. Polyteknisk Forlag, Denmark. Witczak, M.W. (2004). “Assessment of the Allowable (Threshold) Rut Depths by Layers in Asphalt Pavement Systems.” Unpublished report, Department of Civil and Environmental Engineering, Arizona State University, Tempe, AZ.

959

Bearing capacity designs for challenging conditions & load effects

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The premature failure of slab pavements on heavily trafficked industrial sites C. Van Geem & O. De Myttenaere Belgian Road Research Centre, Brussels, Belgium

ABSTRACT: On two industrial sites, serious damage has been observed in recently built concrete slab pavements. In both cases techniques were used that are best suited to indoor floor applications. The slabs are too thin. No dowels are present. Severe cracking occurred soon after construction. Voids under slabs were filled by grout injection and slabs were anchored, but load transfer between them is lacking, as shown by FWD measurements. Both sites are intensively used by heavy goods vehicles, but the structures as designed do not have the required bearing capacity. On one hand, full reconstruction was at first considered unacceptable, as the industrial sites have to remain in operation at all times. On the other hand, operators would prefer solutions that last at least twenty years without further major maintenance. This paper will discuss the types of distress, their most likely causes, and possible solutions for repairs. It will demonstrate by calculation that complete reconstruction can improve bearing capacity without increasing the total thickness of the road structure. 1

DESCRIPTION OF THE SITES

On two industrial sites, serious damage has been observed in recently built concrete slab pavements. Although the sites are used for different purposes, they have many characteristics in common. The first site is a distribution centre where goods of many different origins are collected, sometimes repacked, and then redistributed to supermarkets. On this site large numbers of heavy vehicles circulate around and in the buildings. Three zones can be distinguished on the site: a parking area for trailers, a trafficked area, and loading and unloading bays at the buildings. A lot of manoeuvres take place in the trafficked area: incoming trailers are parked and subsequently moved to the right bay when available. Once loaded or unloaded, the trailers are moved back to the parking area before being picked up again. Owing to significant growth in the company’s activities, more and more vehicles are handled and activity on the site now continues during weekends and at night. An expansion is planned within in the next five years, with extra buildings. On the second site, waste is collected and sorted before being transferred to other places where the sorted waste is recycled, reused, destroyed, or stored. Again, the site is visited by high and ever increasing numbers of heavy vehicles, which move in a very similar way on the concrete slabs. When looking at the design of the “road” structures in the trafficked areas, we can only conclude that: • the potential bearing capacity of the structures as designed must have been inadequate (even in the design phase before construction) and, • the structures were not even built as designed. Generally speaking, although very good “standard designs” and “guidelines for high quality execution” for roads exist in Belgium (Code de bonne pratique CRR, 2005 or Hendrikx 1990), the relevant documents are rarely used when constructing industrial sites. “Outdoor” areas are often designed and constructed by the same people who construct the buildings and the 963

indoor floors rather than by road specialists and this may lead to poor design or construction. The difference in requirements can be seen at once when comparing the “standard designs” for roads with the “technical information notes” for “indoor floors” (Carpentier, 1997). In addition, the construction of industrial sites is mainly commissioned by private companies, which prefer to make large investments in buildings and equipment rather than in roads or industrial pavements. As a result, many technical choices are based on considerations of economy, and this may lead to ill design as well. The structures on the two sites considered are very similar, both in design and in actual construction. On the first site, the natural soil in place was stabilized with lime to reach a compressibility modulus of up to 35 MPa. The subbase consists of 50 cm of unbound crushed stone and is topped by concrete slabs with a nominal thickness of 18 cm. The concrete for the slabs was reinforced with steel fibres. The whole structure is covered by a thin asphalt layer. The slabs were meant to be anchored by their shapes, but additional joints—many of which may not have been provided for in the design—were sawn during construction. In practice, core samples taken from the pavement have revealed that the thickness of the slabs is only 16 cm or 13 cm in some places. Standard design practice for roads would require at least 20 cm of concrete. On the second site the soil in place consists of lime, the subbase was made of recycled quarry waste (mainly large stones and dust), and the surface course is in steel fibrereinforced concrete. The theoretical thickness of the slabs is 20 cm. There are dowels, but only at the expansion joints. Other joints not wider than 7 mm were sawn, resulting in slabs of 6 by 6 m. In practice, during repair works it was observed that the thickness of the slabs varies between 15 and 22 cm and that the thickness of the subbase fluctuates between 20 and 45 cm. On both sites the inhomogeneous nature of the structure in place and the clearly inadequate thickness of the concrete slabs in some places are the greatest concerns to the road engineer. The wide variations in slab thickness observed can only be ascribed to poor-quality construction. 2

OBSERVATIONS ON THE SITES

After a few years of service, visual inspections revealed significant damage. On the first site the thin asphalt layer was cracked at almost all joints. Many joints had deteriorated and

Figure 1.

General view of the first site.

964

Figure 2.

Severe damage on site 2.

widened. Often two parallel cracks had appeared: one right above the joint and one at the end of the anchorage. The first repairs at these joints consisted in resealing them with new asphalt strips 10 to 15 cm wide, but these cracked again. In some places corner cracks and longitudinal cracks were observed. The area in front of the buildings was more severely damaged than that behind the buildings, probably owing to the higher intensity of traffic in front of the buildings than at the back. On the second site cracks appeared soon after construction, even before the provisional acceptance of the work. One year after construction, repairs were made: injections at joints, replacement of some slabs, treatment of joints and cracks. Eight years later, a huge number of slabs were fractured, mostly by transverse and longitudinal cracks at the centre of the slabs, by corner cracks and by cracks originating at inspection chambers of the drainage system. 3

FWD: METHOD AND CRITERIA

On the first site Falling Weight Defelctometer (FWD) measurements were taken with a view to an objective assessment of the overall performance for load transfer between the slabs. With these measurements it was also hoped to detect possible voids under slabs and differences in quality between areas. Surface temperature during the measurements varied between 4 and 6°C. Not all joints on the site were measured: a selection was made by concentrating on those that seemed to exhibit some visual damage. To evaluate load transfer efficiency (LTE) at a joint, the foot of the FWD is placed tangent to the joint and geophones are positioned on either side of the joint. The LTE is defined as the (percentage) ratio between the deflection, Du, measured 300 mm from the place of impact by the geophone on the unloaded slab and the deflection, Dl, measured by the geophone at the foot of the FWD on the loaded slab: LTE = Du / Dl · 100%. For a comprehensive overview of the technique we refer to (Khazanovich & Gotlif, 1990). The foot of the FWD can be placed just before the joint (on the approach side) or just beyond it (on the leave side), resulting in a load impact on one or the other adjacent slab. For many joints on the first industrial site both configurations were used. An impact force of about 40 kN was generated. Under these conditions an LTE value of 70% is the critical value below which load transfer at the joint is considered inadequate. To assess the presence of voids under slabs, the FWD was placed near the joint in the same manner as for the LTE evaluation, but the measurements were repeated with three different drop heights resulting in three different impact forces of approximately 40, 50, and 60 kN. The corresponding measurements were plotted as three points on a graph showing force on 965

Figure 3.

FWD measurements on site.

the X-axis versus deflection Dl under the foot of the FWD on the Y-axis. The “straight line” with equation y = mx + b best fitting these three points will intersect the Y-axis in y = b. If this value is too high (b > 75 μm), the presence of a void is generally accepted, whereas if b < 50 μm it is generally accepted that there is no void (Crovetti & Darter, 1995). Opinions vary on how to interpret b values in the range between 50 and 75 μm. LTE is an easy and useful indicator as such, but further analysis of the measurement results can yield additional evidence to load transfer inefficiencies. In order to have an empirical reference from the site, additional measurements were made at the centre of a few undamaged slabs. In case of perfect load transfer LTE should, by definition, always be smaller than 100%. In fact, Du = D(300) (the deflection measured 300 mm from load impact) is supposed to be strictly smaller than Dl = D(0) at the centre of load impact. A verification at the centre of a few undamaged slabs, where load transfer could be assumed to be almost homogeneous and perfect, showed that the calculated value D(300)/D(0). Hundred percent ranged between 81 and 90%. The values for b on these spots, i.e., in the absence of joints and cracks, varied between –12 and –24 μm, which were all very reasonable values. Finally, it is worth noting that the maximum deflections measured at the centre of the slabs were very similar, i.e., approximately 100 μm under an impact force of 50 kN. On one spot six different forces ranging from 40 to 105 kN were applied, resulting in excellent linear behaviour of the maximum deflection over this range of forces. This linear behaviour justifies the choice of magnitude of the applied forces to calculate b, as we could expect a force of 30 kN to generate only a very small deflection close to the limit for which the calibration of the geophones can guarantee their accuracy. 4

FWD: RESULTS AND INTERPRETATION

A first observation is that the LTE values measured by applying the force on different sides of the same joint are very similar. For about three quarters of all joints investigated the LTE value is even smaller than 50%. At the back of the buildings the situation is better than in front, with an acceptable LTE value for about half of the joints investigated. For a few joints, the LTE values measured with the force applied on different sides of the joint are acceptable for only one of the positions. In these cases the deflection values at D(600) and D(–600) are very different, which is another indication of a problem with load transfer. 966

Somewhat surprisingly, sometimes the LTE values at a joint are higher than 100%. But the deflections D(0), D(300), D(600), D(–300) and D(–600) are extremely high in these places, whereas the deflections further away from the place of impact are extremely small. We think that this behaviour is due to repairs which only bonded the slabs together without stabilizing them. This is confirmed by the results on two spots where we were able to perform a test with another interesting configuration of the FWD. Here the foot was placed tangent to a crack, with the geophone at –300 mm between the crack and the original joint and the geophone at –600 mm on the other side of the joint. The deflexions D(0) and D(–300) are very high, D(–300) is higher than D(0) and there is an abnormal difference between D(–300) and D(–600). Almost everywhere in front of the buildings the value for b largely exceeds the critical value of 75 μm. Also, in the direction of traffic flow the value for b is higher when applying the forces on the second slab (beyond the joint). This corresponds to the expectation that voids are present and that they are larger under the slab beyond the joint (considering the main direction of traffic). At the back of the buildings the value for b exceeds the critical value of 75 μm at only four of the fifteen joints investigated. 5

THEORETICAL DESIGN

Since on both sites the structure as built is very inhomogeneous and the concrete slabs in place appear to be too thin, it seems appropriate to compare them with an optimum design for the structure using a theoretical calculation for a given hypothetical traffic load and traffic spectrum. All calculations were made with the software tool DimMET© developed by BRRC and FEBELCEM for the Walloon Ministry of Transport (Lemlin et al. 2006). It models the road structure as a multilayer system and calculates the life expectancy of the structure in terms of standard axle loads or number of years for a given traffic spectrum. The end of life for the road structure is defined as the moment of structural failure, i.e., the moment when the road surface is cracked over at least 50% of its surface area. The software is also capable of back-calculating elastic moduli from FWD deflection measurements. The hypothetical traffic spectrum consists of semitrailers with axle loads distributed as follows: 20% are 50-kN axles, 20% are 120-kN axles, and 60% are 90-kN axles. The latter correspond to tridem axles. It is assumed that in the first year there will be 100 heavy vehicles per day for 300 days per year and that the traffic will increase by 2% every year. The following structure is an example of a design with adequate bearing capacity, as demonstrated with the software tool DimMET©: • • • •

concrete slabs, 200 mm, without dowels; crushed stone base, Belgian type I, 400 mm; subgrade improved by lime stabilization, 200 mm; clayey natural soil.

In this theoretical calculation, no surface course has been considered. A thin asphalt surface course of 40 mm on top of this structure would be common practice for roads, but in this application on an industrial site the absence of this thin layer is not critical. The characteristics of the materials entered in the calculations are summarized in Table 1. Calculations result in a number of standard axle loads Nc equal to 1.81 * 106 before structural failure and a life expectancy of over forty years. When the thickness of the concrete slabs in the model is reduced, calculations show a consequent reduction in life expectancy. The results of the calculations are given in Table 2. 6

BEARING CAPACITY FROM MEASUREMENTS

The example of (Korsgaard et al. 2005) confirmed our views that further interpretation of FWD measurements can benefit the optimization of maintenance operations. On the first site FWD measurements were made on a few spots at the centre of slabs. The measured 967

Table 1. Characteristics of the materials entered in the calculations. Material

Modulus (N/mm2)

Poisson’s ratio

Cement concrete Crushed stone base Lime-stabilized subgrade Clayey natural soil

37,661 650 2,000 20

0.20 0.45 0.50 0.50

Table 2. Influence of slab thickness on life expectancy—results of the calculations. Slab thickness (mm)

200

Standard axle loads Nc Life expectancy in years

2.45 * 10 >40

190 6

6.60 * 10 18

180 5

1.52 * 105 5

Table 3. Deflections measured at different distances from impact (force: 55 kN). Distance (mm)

0

300

600

900

1,200

1,500

1,800

Deflections (μm)

91

76

59

46

36

30

26

deflections were used for back-calculations of elastic moduli, using the algorithm implemented in the software tool DimMET©. For the back-calculation we assumed the following structure: • concrete slabs 18 cm thick, Poisson’s ratio 0.20, expected E-modulus about 27,000 N/mm2; • subbase 50 cm thick, Poisson’s ratio 0.35, expected E-modulus about 2,000 N/mm2; • stabilized subgrade, Poisson’s ratio 0.50, expected E-modulus about 350 N/mm2. On one spot at the centre of a slab, the falling weight of the FWD applied a force of 55 kN and the following deflections (Table 3) were measured by the geophones at different distances from the place of impact: The back-calculation converged to the following E-moduli: 35,928 N/mm2 for the slab, 1,081 N/mm2 for the subbase, and 335 N/mm2 for the subgrade. The back-calculation yielded similar results for spots at the centres of other slabs. Since the E-moduli obtained by back-calculation from FWD measurements on site seem to be in agreement with the assumptions made in the theoretical calculations above and since the actual slab thickness on the site is only 18 cm, we can conclude that with no doubt the bearing capacity on the first industrial site is inadequate. 7

FURTHER CAUSES OF DAMAGE

On the first site it is fairly certain that the pumping effect of concrete slabs has resulted in the development of voids and in reflective cracking at the u-shaped anchorage of the slabs. Bearing capacity was reduced by inadequate layer thickness both at the design stage and during actual construction, leading to premature ageing. Additional saw cuts reducing the size of the slabs more than planned in the design certainly did not improve bearing capacity. 968

Although impossible to verify now, it is not to be excluded that some of the distresses at the first site are due to conditions during construction. Rainfall during the laying of the subbase may easily have contributed to the formation of initial voids. In one place a longitudinal crack has formed, which may have been caused by a rut in the subbase due to heavy loading by construction traffic (vehicles or machines). The damage on the second site is almost certainly the result of a combination of causes. Since the slabs were already too large (6 × 6 m) with respect to the design thickness (20 cm), the inadequate thickness as constructed has exacerbated the situation. We generally consider that the maximum length/thickness ratio of concrete slabs is 25 (which means that the maximum length of the slabs should have been 5 m). The slabs in place on the second site have a length/thickness ratio up to 40. This may lead to major cracking in the slabs, which certainly has occurred. Load transfer is inadequate owing to the absence of dowels or a continuous mesh at the joints. In addition, the pattern of the joints was inappropriately drawn in the design phase, resulting in local cracks. Furthermore, bearing capacity is inadequate in certain places due to locally insufficient thickness of the concrete slabs or the subbase and to the variation of these thicknesses. The structure is not sufficiently impervious to water, especially at the joints. It is recommended that joints are wider than on this industrial site, to allow effective application of a sealing compound. Additionally, the subbase was made of easily erodible waste material, which has worsened the formation of voids by pumping. In traditional road design a bituminous interlayer is sometimes used to improve the bond between the subbase and the concrete layer and to protect such an easily erodible subbase from water infiltration. However, an interface layer is nowhere present on the site. Since the soil in place is lime, the absence of an effective drainage system is another adverse factor. Moreover, it is worth noting that steel-fibre reinforced concrete is typically used for indoor industrial floors. It does not offer any improvement over well-designed unreinforced concrete slabs, nor will it replace conventional reinforcing bars or a mesh. Though tried in several test sections, it is not used at all for ordinary road construction in Belgium.

8

APPROPRIATE REPAIRS

Once the situation had been observed and the seriousness of the problems had been acknowledged, possible solutions were discussed between the operators and owners of the industrial sites on the one hand and technically skilled people including road construction companies on the other. For the operators of the first site, closing the site for traffic is not an option; the site must remain in operation. Reconstructing the pavement is not possible, so it was said at first by the industrial owner. However, they do prefer a long-term solution which guarantees a life of twenty years with ordinary maintenance. This seems impossible without full reconstruction. During the discussion it turned out that on the first site only part of the loading and unloading area is really difficult to close down, i.e., the part where non-standard lorries of different sizes and of different supply companies can be handled. This may be solved temporarily in a few years’ time, when a new building is constructed with more loading and unloading bays and equipment for non-standard lorries. Then, for a short period, the activities could be planned differently and there would be an opportunity for a final replacement of the severely damaged pavement. The pavement in front of the “non-standard” loading and unloading bays can be provisionally repaired with injections and an overlay, so that it can survive the five-year period up to the construction of the new building. It is suggested that for this site modern techniques with fast-track concrete (Lonneux et al. 2006) laid in several stages may be the best solution, at least for the trafficked area. Each stage could be completed in four days of work. The asphalt layer, which does not contribute significantly to the bearing capacity of the pavement, could be replaced by additional concrete. In this way a 20-cm layer could be placed. 969

Alternative solutions were discussed, but they were judged inadequate. The concrete layer is not thick enough for reinforcement with dowels; there is simply not enough material to anchor the dowels. Stabilization by grout injections is feasible and not very expensive. This solution could do for the parking and bay areas and could result in an additional life of at least seven to ten years. Since there is a lot of free parking space in the area where other buildings will be constructed later, it is still easy to repair parking areas without interrupting operations on the site. As the classical bay area for standard size lorries is not yet used at its full capacity during weekends, repairs in this part of the bay area can be planned in a few stages and carried out on Friday afternoons. But stabilization by grout injections represents only a short-term solution for the trafficked area, for which an additional life of only three to five years can be expected by experience. It also does not improve bearing capacity to anything better than what can be expected from the previously ill-designed structure. In the trafficked area a new overlay with asphalt may be necessary to prevent further water infiltration. At the end of the discussions, it was decided to reconstruct the whole surface of the first site, since this was considered as the only way to guarantee full operability without major maintenance works for a long period of time. The operators of the second site sought a solution for the observed damage without jeopardizing operational needs that may be very different in future. In particular the spatial organization of the site may have to be reviewed in future, in response to the rapidly changing needs for, and techniques of, waste disposal. For the second site four different solutions were considered. A first solution consists in the replacement of a limited number of damaged slabs in the area where heavy vehicles circulate. The success of this operation depends highly on the following conditions: • • • • • • • • •

checking the design parameters against the actual needs in terms of bearing capacity; replacing the slabs by new slabs of adequate thickness as provided for in the design; checking of the thickness of the subbase; checking of the aggregate bearing capacity of the subbase and the soil in place (determination of Westergaard’s modulus); replacing the top few centimetres of the subbase by a bituminous mixture (Belgian type BB-4C); appropriate sawing of contraction joints, with special attention to the presence of inspection chambers of the drainage system; proper sealing of the new joints; incorporating a continuous mesh at mid-depth in the new slabs; inserting dowels in order to connect the new slabs with the existing adjacent slabs.

Additionally, the joints between each pair of old slabs should be widened and properly sealed. This is certainly not the best solution, since the replacement of an isolated slab causes great difficulties in construction (compaction of the material) and involves a higher risk of low quality at the connections between old and new slabs (risk of erosion and local loss of compaction of the subbase). Also, the slabs that remain in place may deteriorate rapidly over time, especially when traffic conditions on the site change in future. The second solution consists in a bituminous overlay. In this case the whole level of the surface is raised by at least 90 mm (and even at least 120 mm if a regulating course is needed). The success of this operation depends on the following conditions: • • • • •

cracking and seating of the concrete slabs; replacement of slabs that are too severely damaged; treatment of joints and cracks wider than 3 mm; incorporation of an interface layer to control reflective cracking; adding at least two bituminous layers as an overlay, to compensate for the loss of bearing capacity due to cracking and seating. The layers should be thick enough to allow later replacement of the surface course without risk of damaging the interface layer; 970

• incorporating a regulating course if the concrete surface is too uneven; • adding a surface course in grouted asphalt where loads stand still for long periods of time (parking area for lorries or storage area for containers). This solution is the cheapest, but it is worth mentioning that cracks will appear again in time and that the allowance made for changes in traffic conditions is very limited, since the pavement differs in nature between trafficked areas on the one hand and parking and storage areas on the other. Furthermore, the raise in surface level may require additional measures: drains may have to be adapted, the access to the site from the adjacent road may have to be redesigned, and adjacent buildings may put a constraint on the maximum extra height. The third solution is a concrete overlay. In this case the whole level of the surface is raised by at least 260 mm. The success of this operation depends on the following conditions: • cracking and seating of the existing concrete slabs; • adding a bituminous interlayer for optimum regulation and bond between layers; • appropriate sawing of contraction joints, with special attention to the presence of inspection chambers of the drainage system; • proper sealing of the new joints; • incorporating a continuous mesh at mid-depth in the new slabs. This solution is very costly. It does allow all imaginable changes in operation of the industrial site, but the raising of the surface level may require additional measures—like in the case of a bituminous overlay. The forth solution is the complete demolition of the existing concrete slabs and the construction of a new pavement. The success of this operation depends on some of the conditions already mentioned for the first solution: • checking the design parameters against the actual needs in terms of bearing capacity; • checking the thickness of the subbase; • checking the aggregate bearing capacity of the subbase and the soil in place (determination of Westergaard’s modulus); • replacing the top few centimetres of the subbase by a bituminous mixture (Belgian type BB-4C); • appropriate sawing of contraction joints, with special attention to the presence of inspection chambers of the drainage system; • proper sealing of the new joints. The disadvantages of local repairs mentioned for the first solution do not apply in this case. This solution also allows all imaginable changes in the future operation of the site. The owner of the second site has opted for the forth solution, since it is considered as the best trade-off between the effectiveness of the intervention, the modularity of the site for future operation, and the costs involved. 9

CONCLUSIONS

These and other examples in Belgium have increased awareness among construction companies that there is a need for specific guidelines for the design and construction of highly trafficked industrial sites. FWD measurements have shown that inadequate bearing capacity is an important issue on industrial sites. Not only the needs for bearing capacity, but also other technological aspects of design are very similar to those applying to ordinary roads. Other aspects not related to road technology have to be taken into account as well. Such aspects include the vicinity of buildings and the adjacent industrial floors inside these buildings, specific demands on surface smoothness for the sensitive tyres of forklifts used indoors, aesthetics. In June 2008, a working group was formed to compile a document with specific guidelines to be published by the end of 2009. Designers of industrial sites who are less familiar with road design will find in this document the specific guidelines they need for a successful design of the trafficked areas of such sites. 971

REFERENCES Carpentier, G. 1997. Sols industriels à base de ciment, NIT 204, Centre Scientifique et Technique de la Construction (ed.). Code de bonne pratique pour l’exécution des revêtements en béton. 2005. Centre de Recherches Routières (ed.). Crovetti, J.A. & Darter, M.I. 1985. Void Detection for Jointed Concrete Pavements. Transportation Research Record 1041, Transportation Research Board, National Research Council, Washington, D.C. Hendrikx, L. 1990. Bedrijfsverhardingen van beton. Verbond der Cementnijverheid (ed.). Khazanovich, L. & Gotlif, A. 2003. Evaluation of Joint and Crack Load Transfer—Final Report. FHWA-RD-02-088. Korsgaard, H.C., Pedersen, J.P., Rasmussen, M. & Königsfeldt, S. 2005. Rehabilitation by Cracking and Seating of Concrete Pavement Optimized by FWD Analysis. BCRA 2005. Lemlin, M. et al., 2006. Walloon Design Method for Concrete Pavements, Improvements since 2003, Proceedings 10th International Sumposium on Concrete Roads, 18–22 Sept. 2006, Brussels. Lonneux, T. et al., 2006. (Ultra)Fast-track Concrete Paving: Belgian Experience. Proceedings 10th International Sumposium on Concrete Roads, 18–22 Sept. 2006, Brussels.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The discussion on the “b” value of the axle load conversion in China X. Wang Research Insitute of Highway, MOC, Beijing, China

L. Zhang Beijing Municipal Road Management, Beijing, China

ABSTRACT: There is a correlation between pavement deflection level and axle load. Generally, it has been accepted that the exponential relationship exists between deflection ratio and axle load, and the exponent b is the important parameter during axle load conversion. Based on dynamic and static tests on-site and statistical analyses, the calculation method as well as the recommended “b” value has been developed under over-load situation, which is also the basis of establishing specifications. 1

INTRODUCTION

In China, deflection is a major indicator in asphalt pavement structural design. For a good design, the design deflection (ld) should not be more than practical deflection value (ls). The latter can be calculated by multi-layered pavement model for practical pavement structures, as the equation below: ls = le ⋅ F

(1)

Follow the above, the le is the theoretical solution of multi-layered pavement model, and F is the overall modification parameter. On the other hand, design deflection is an experimental equation which is statistically regressed based on deflection test in various times of accumulative standard axle load. As given by Equation 2, the “a” and “c” are regression coefficients. According to the amount of practical data and statistical regression results, the coefficient c = 0.2 has been accepted for asphalt pavement design in China. ld = a ⋅ N−c

(2)

Alternatively, as the variable of asphalt pavement load design, the accumulative standard axle load can be achieved by transforming practical axle load (each axle weight) into 10-ton standard axle load referring to deflection equivalence principle. The experimental equation is presented below: K ⎛P ⎞ N = ∑C ⋅ ni ⎜ i ⎟ ⎝P⎠ i =1

4.35

(3)

where N = equivalent standard axle load based on design deflection criteria; C = converted vehicle coefficient; ni = axle load times of converted vehicle; P = standard axle load (100 kN); Pi = axle load of converted vehicles (kN); 4.35 = coefficient of axle load conversion equation. However, on account of inadequate practical over-load deflection tests for model validation, the axle load conversion equation can only be applied for the axle load under 13-ton, and there is no specific comments for above 13-ton.

973

Commonly, both theoretical analyses and practical tests illustrate that pavement deflection ratio is proportional to the “b” value of axle load ratio as in Equation 4: l1 ⎛ P1 ⎞ ≈⎜ ⎟ l2 ⎝ P2 ⎠

b

(4)

Based on Equation 2, the relationship between deflection ratio and number of axle load applications can be achieved as in Equation 5; furthermore, Equation 6 is the basic theoretical axle conversion equation between axle load ratio and no. of axle load applications based on deflection equivalence and is also given below: ld 1 aN1−c ⎛ N1 ⎞ = =⎜ ⎟ ld 2 aN2−c ⎝ N2 ⎠ N1 ⎛ P1 ⎞ =⎜ ⎟ N2 ⎝ P2 ⎠

−c

(5)

b/c

(6)

In accordance with the design coefficients in current specifications in China, b/c = 4.35 and c = 0.2, therefore, b = 8.7. This research is focused on the reasonable b value under overload situations, which can also provide theoretical basis for axle load times conversion under over 13-ton load. 2

FULL-SCALE ACCELERATED LOAD TEST DATA ANALYSES

In 1990s, the deflection of several full-scale pavement structures have been measured under various axle loads and tire pressures by applying the accelerated load facilities (ALF) in China, and the results are given in Table 1. In this table, structures 1 to 5 represent the old road, and structures 6 and 7 are new constructed pavement, which can explain that the deflections of the structures 6 and 7 are significantly smaller than those of the other five. Moreover, it is interesting to note that the deflections under 1.1-MPa tire pressure are less than those of the 0.9-MPa tire pressure in some structures for the same wheel load. Based on the data in Table 1 and Equation 1, the relationship between deflection ratio and tire load ratio can be represented as the regression equations for 50 kN tire load as in Table 2. The variable x = ln(P1/P2), y = ln(l1/l2), P1 and l1 represent the deflection level under other tire load conditions; P2 and l2 represent the 50 kN tire load and the corresponding practical deflection level. In the regression model, the coefficients actually are b values. Accordingly, as tire pressure is 0.7 MPa, b value ranges from 0.4369 to 0.8249 with average value 0.5992; the corresponding b value of 0.9 MPa is 0.3657 ~ 0.7342 and 0.5120 in average; to 1.1 MPa, the range lies in 0.3665 ~ 1.1249 with 0.6327 in average. Within all the regression equations, the correlation coefficient ranges from 0.8144 to 0.9953, in other words, the regression results are reliable. The b values in Table 2 are even smaller than the accepted value (0.87) in the current specifications. The smaller b value shows the low sensitivity of deflection to axle load change; however, it is against the deflection changes of semi-rigid pavement under over-load. Compared with the deflection data in Table 1, it is noted that larger deflection corresponds with smaller b value. Therefore, b value is not only related with deflection ratio and axle load ratio, but also indicates the overall structural strength, which is represented by deflection value. From Table 1, the deflection of various structures under 50 kN axle load can be classified by different tire pressure, and the relationship between the deflection and b value can also be presented as in Table 3. According to exponential regression analysis, there is a high correlation between the b value and deflections under the three tire pressures. 974

Table 1.

Deflections under various tire pressures and axle weights.

Tire load, kN Structure Structure 1

Structure 2

Structure 3

Structure 4

Structure 5

Structure 6

Structure 7

50

60

70

80

Tire pressure, MPa

Deflection 1/100 mm

0.7 0.9 1.1 0.7 0.9 1.1 0.7 0.9 1.1 0.7 0.9 1.1 0.7 0.9 1.1 0.7 0.9 1.1 0.7 0.9 1.1

114 118 115 93 94 87 97 106 105 103 115 108 112 118 117 38 39 28 55 56 40

125 123 116 103 107 96 109 115 105 120 124 120 125 127 128 44 44 31 61 63 46

134 126 127 107 109 109 116 114 109 130 123 129 136 135 134 49 51 39 69 71 51

142 141 134 122 120 113 127 126 123 135 141 129 141 145 137 57 56 48 73 76 66

90

100

150 146 143 128 131 124 141 137 131 150 150 144 151 158 150 61 62 55 81 82 78

149 157 154 137 134 132 148 146 144 155 152 154 155 162 163 68 62 63 90 92 86

Table 2. Regression results of deflection ratios and axle weight ratios in various pavement structures. Structure

Tire pressure, MPa

Regression equation

Correlation coefficients

Structure 1 Structure 2 Structure 3 Structure 4 Structure 5 Structure 6 Structure 7

0.7 0.7 0.7 0.7 0.7 0.7 0.7

y = 0.5419x y = 0.4369x y = 0.5444x y = 0.6041x y = 0.6181x y = 0.8249x y = 0.668x

R2 = 0.9945 R2 = 0.9635 R2 = 0.9796 R2 = 0.9904 R2 = 0.972 R2 = 0.9953 R2 = 0.9866

Structure 1 Structure 2 Structure 3 Structure 4 Structure 5 Structure 6 Structure 7

0.9 0.9 0.9 0.9 0.9 0.9 0.9

y = 0.3657x y = 0.5271x y = 0.4134x y = 0.4037x y = 0.4582x y = 0.7342x y = 0.6814x

R2 = 0.9196 R2 = 0.9715 R2 = 0.916 R2 = 0.9158 R2 = 0.986 R2 = 0.9776 R2 = 0.9921

Structure 1 Structure 2 Structure 3 Structure 4 Structure 5 Structure 6 Structure 7

1.1 1.1 1.1 1.1 1.1 1.1 1.1

y = 0.3665x y = 0.5983x y = 0.3653x y = 0.484x y = 0.4291x y = 1.1249x y = 1.0607x

R2 = 0.9137 R2 = 0.991 R2 = 0.8144 R2 = 0.9578 R2 = 0.9515 R2 = 0.9726 R2 = 0.9598

975

Table 3.

The relation between b value and deflection.

Tire pressure, MPa

0.7

Variables

Deflection 1/100 mm

b value

Deflection 1/100 mm

b value

Deflection 1/100 mm

b value

114 93 97 103 112 38 55

0.5419 0.4369 0.5444 0.6041 0.6181 0.8249 0.668

118 94 106 115 118 39 56

0.3657 0.5271 0.4134 0.4037 0.4582 0.7342 0.6814

115 87 105 108 117 28 40

0.3665 0.5983 0.3653 0.484 0.4291 1.1249 1.0607

Structure 1 Structure 2 Structure 3 Structure 4 Structure 5 Structure 6 Structure 7 Regression equation Correlation coefficient

Figure 1.

0.9

1.1

b = 2.7627l–0.3483

b = 6.4655l–0.5765

b = 17.047l–0.7837

R2 = 0.5464

R2 = 0.8789

R2 = 0.9155

The regression curve of b value and deflection.

As shown in Table 1, because there is no direct relationship between b value and tire pressure, and the influence of tire pressure on b value is reflected by deflection, regardless of tire pressure influence, the regression model can be established of three tire pressure with b value (see Figure 1 & Eq. 7); in this case, the deflection under 0.9 MPa and 1.1 MPa tire pressure can be considered as the deflection of another structure under 0.7 MPa. Therefore, the sample size can be enlarged in order to improve the reliability of analysis. b = 8.5746 × l−0.6235

r2 = 0.7724

(7)

From Equation 7, the b values can be calculated under various structural strength levels. Taking into account the range of deflection from 20 to 30 (1/100 mm) on China expressways, b values are about 1.324 ~ 1.029. 3

FWD DEFLECTION ANALYSIS

Falling weight deflectometer (FWD) is a new measurement of deflection based on simulation of dynamic vehicle load. The measure has been widely applied to pavement deflection testing due to the high precision and ease in operation. 976

Table 4.

Deflection data under various falling weights on Zhengzhou-Luoyang expressway.

Falling weight kN

Center point deflections 1/1000 mm 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

30 40 50 60 70 80

131 164 183 210 233 256

85 109 124 144 162 182

121 163 184 211 240 268

246 305 338 377 414 447

100 141 162 184 209 236

118 156 178 210 236 261

139 188 211 237 264 291

82 112 131 157 178 200

73 100 118 143 163 182

124 165 191 222 251 280

95 135 156 185 215 242

85 110 125 144 162 179

149 185 209 233 256 280

88 122 140 159 178 198

77 105 118 138 159 177

81 108 126 150 169 188

Table 5.

Regression analyses of b value on Zhengzhou-Luoyang expressway. Center point deflections 1/1000 mm

Falling weight kN 30 40 50 60 70 80 b value Correlation coefficient

<100

100~200

>200

average

83 113 130 153 173 194 0.8813

126 166 188 215 241 267 0.7857

246 305 338 377 414 447 0.625

152 195 219 248 276 303 0.7207

0.9997

0.9997

0.9998

0.9997

Table 4 illustrates the load/deflection data under various load levels on Zheng-Luo expressway in Henan province in China. The pavement structure considered was 15 cm of Asphalt Concrete surface + 15 cm of Cement Aggregate base + 40 cm Cement Soil sub-base in 17.5οC air temperature (surface temperature 25οC). The falling weights of 30 kN, 40 kN, 50 kN, 60 kN, 70 kN, 80 kN (equivalent to 6, 8, 10, 12, 14 and 16 tons axle load, respectively) were deployed in an orderly fashion. According to the deflections under 30 kN falling weight, the results can be classified into three types: less than 100 μm, 100 μm ~ 200 μm, over 200 μm. Then b values are tabulated in Table 5. As shown in the table, b value increases with the decrease of deflection. According to the regression coefficients, the correlation relationship of the two variables is stronger than that of Benkelman Beam Test; in other words, both accuracy and reliability of FWD test performed was better than the Benkelman Beam Test. Moreover, b value is much less than the previous one which is mainly due to the 6-ton standard axle load. By applying FWD tests on Badaling Expressway, the deflections under various falling weights on 15 points are tabulated in Table 6, and the b value is computed as 0.9711. Similarly, the relationship between deflection and b value is analyzed under various deflection levels. As in Table 5, the deflection on Zheng-Luo expressway can be categorized into three types, and the average value is the forth type; comparably, the deflection on Badaling Expressway is more stable which are below 100 mm, therefore, they can be considered as one type. Consequently, there are five points as shown in Figure 2, and the regression equation is b = 3.7532l−0.3261 with R2 = 0.9965. The high correlation represents the improved stability of FWD test. When the deflection is 20 ~ 30 (1/100 mm), the b value is 0.67 ~ 0.58. Based on the results of FWD test, the regression equation of b value was developed under various falling weights, with the b value 0.8079. ln

l1 P = 0.8079 ln 1 l2 P2 977

r 2 = 0.9648

(8)

Table 6.

Deflections under various load levels on Beijing Badaling expressway.

Number

Load (kPa)

Deflection (μm)

Load (kPa)

Deflection (μm)

Falling weight ratio

Deflection ratio

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Average b value

469.3 461.6 463 447 446.6 438.6 437.4 443.1 434.3 444.7 462.1 449.9 463.3 462.3 459.1 452 0.9711

63.3 65.2 51.2 49.3 70.3 71 70.9 64.8 66.8 84 86.4 56.1 55.2 46 52.6 64 –

895.2 900.1 896.7 889.1 884.2 878.4 877 878.9 876.6 881.1 893.6 884.1 893 893.2 891.7 888 –

125.2 124.3 97.4 95.4 132.6 130.2 129.7 131.9 132.2 156 157.4 108.2 106.9 93.3 106.7 122 –

1.9075 1.9500 1.9367 1.9890 1.9798 2.0027 2.0050 1.9835 2.0184 1.9813 1.9338 1.9651 1.9275 1.9321 1.9423 1.9637 –

1.9779 1.9064 1.9023 1.9351 1.8862 1.8338 1.8293 2.0355 1.9790 1.8571 1.8218 1.9287 1.9366 2.0283 2.0285 1.9258 –

Figure 2.

Regression curve of the b value under various deflection levels. Table 7.

Deflection test results on the Jinwei highway. Deflection 1/100 mm

Deflection range

10-ton

18-ton

Deflection ratio

b value

<10 10 ~ 20 20 ~ 30 30 ~ 40 40 ~ 50 50 ~ 60 60 ~ 70 70 ~ 80 80 ~ 90 90 ~ 100 >100

6.53 16.49 25.19 34.46 44.28 54.35 64.05 73.92 85.97 94.77 138.44

31.78 51.08 58.23 75.17 83.51 110.96 139.33 164.79 182.26 202.96 246.37

4.8673 3.0977 2.3117 2.1814 1.8860 2.0414 2.1753 2.2294 2.1201 2.1416 1.7796

2.6924 1.9234 1.4255 1.3268 1.0792 1.214 1.3221 1.364 1.2786 1.2955 0.9805

978

Figure 3.

4

Regression curve of the b value varying with deflections.

ON-SITE BENKELMAN BEAM TEST DATA ANALYSES

The Benkelman beam test was deployed at the same point under 10-ton and 18-ton axle loads on Jinwei highway (the arterial freight corridor in Tianjin). During the test, over 300 points were detected, and the data were classified by deflection level under 10-ton axle load, and the b value of various deflection levels are illustrated in Table 7. As the data in Table 8, the regression curve between b value and deflection level has been depicted in Figure 3, and the corresponding regression equation is b = 3.9603l−0.2766 with the correlation coefficient r2 = 0.7785. When the deflection is 20~30 (1/100 mm), the range of b value is 1.72 ~ 1.55. 5

CONCLUSIONS

Based on various test methods, the b values, which relate pavement deflections to axle load levels, were calculated in the condition of over 13-ton axle load, and the conclusions are presented below. 1. From the statistical analysis, it has been explored that the b value of static Benkelman beam test (such as ALF test sections and Jinwei highway) is over 0.87 (current specification standard); comparably, that of Dynamic Falling Weight Deflection Test is below 0.87. 2. The differences of b value between static and dynamic deflection tests reflect the responses of pavement structure varied with load conditions. Although Benkelman beam test is still applied as the design standard in China, the simulated condition of the dynamic falling weight test is closer to the real traffic load situation. Therefore, it is more practical to use dynamic measure to acquire b value. 3. Both static and dynamic tests illustrate the effects of various deflections on b value, which means the load ability of pavement structure is reflected by deflection. In other words, it also reflects the non-linear response characteristic of pavement material and structure under loading; moreover, as a dependent variable, b value has relationship with overall strength of pavement structure; as strength levels up, b value will increase with the decrease of deflection, and vice versa. REFERENCES Ministry of Communications. 2006. Highway asphalt pavment design specifications (JTG D50-2006), Beijing: China Communications Press. Research Institute of Highway, Ministry of Communications China. 2003. Over-load traffic asphalt pavement structure design specifications Research Report. China.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Load bearing analysis of EPS-block geofoam embankments D. Arellano The University of Memphis, Memphis, Tennessee, USA

T.D. Stark The University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

ABSTRACT: This paper presents a deformation-based load bearing analysis procedure that utilizes the elastic limit stress, i.e. the compressive stress at 1 percent strain, to design expanded-polystyrene (EPS)-block geofoam for roadway embankments. The procedure consists of determining the maximum vertical stress from dead and traffic loads at various levels within the EPS fill mass and selecting an EPS type that exhibits an elastic limit stress that is greater than the calculated vertical stress at the depth being considered. The higher the required elastic limit stress, the greater the required block density. However, the cost of EPS block increases with increasing density. Therefore, an advantage of the recommended deformation-based design procedure is that the calculation of stresses and strains within the EPS mass allows the selection of the type of EPS blocks to be optimized by selecting blocks with a lower density for the lower portions of the embankment and the higher density blocks for the upper part of the embankment. The selection of EPS blocks with the lowest possible density yields a cost efficient EPS block geofoam embankment. 1

INTRODUCTION

The American Society of Testing and Materials (ASTM) defines geofoam as a block or planar rigid cellular foam polymeric material used in geotechnical engineering applications. It also defines expanded polystyrene (EPS) as a type of foamed plastic formed by the expansion of polystyrene resin beads in a molding process (American Society for Testing and Materials 2007). The predominant geofoam that has been used for lightweight fill in geotechnical applications is EPS-block geofoam. Although EPS-block geofoam for road construction is an established technology and despite the extensive and continuing worldwide use of EPS-block geofoam since the early 1970s, it has been underutilized in U.S. practice because a comprehensive design guideline for its use as lightweight fill in roadway embankments has not been available. To meet this need, the American Association of State Highway and Transportation Officials (AASHTO), in cooperation with the Federal Highway Administration (FHWA), funded a study through the National Cooperative Highway Research Program (NCHRP), to develop a comprehensive design procedure for the use of geofoam in roadway embankments. The NCHRP Project 24–11(01) results are included in two reports. One report includes only the design guideline and the material and construction standard (Stark et al. 2004b). The second report includes the background for the design guideline and standard as well as a summary of the engineering properties of EPS-block geofoam and an economic analysis (Stark et al. 2004a). The primary objective of this paper is to present a deformation-based load bearing capacity analysis procedure to design EPS-block geofoam for stand-alone embankments over soft ground. The primary advantage of the recommended deformation-based design procedure is the calculation of stresses and strains within the EPS mass allows the selection of the type of EPS blocks to be optimized by selecting blocks with a lower density for lower portions of the embankment and higher density blocks for the upper part of the embankment. 981

Pavement System

Fill Mass (EPS Blocks & Soil Cover, if any)

Foundation Soil

Figure 1.

Major components of an EPS-block geofoam embankment.

Using EPS blocks with the lowest possible density yields a cost efficient EPS block geofoam embankment. The design of an EPS-block geofoam roadway embankment over soft soil requires an understanding of the interaction between the three major components of the embankment, i.e. foundation soil, fill mass, and pavement system. These components are shown in Figure 1. Therefore, the overall design process is divided into three phases that consider interaction between these three major embankment components. The external (global) stability phase considers how the combined fill mass and overlying pavement system interacts with the existing foundation soil and considers stability of the overall embankment. External stability consideration in the proposed design procedure include consideration of Serviceability Limit State (SLS) issues, such as total and differential settlement caused by the soft foundation soil and Ultimate Limit State (ULS) issues, such as bearing capacity, slope stability, seismic stability, hydrostatic uplift (flotation), translation due to water (hydrostatic sliding), and translation due to wind. The internal stability phase considers stability within the embankment fill mass and the primary consideration is the proper selection and specification of EPS properties so that the geofoam mass can support the overlying pavement system without excessive immediate and time-dependent (creep) compression that can lead to excessive settlement of the pavement surface. Internal stability in the proposed design procedure includes consideration of SLS issues such as the proper selection and specification of EPS properties so the geofoam mass can provide adequate load bearing capacity to the overlying pavement system without excessive settlement and ULS issues such as translation due to water (hydrostatic sliding) and wind, and seismic stability. The pavement system phase considers the subgrade support provided by the underlying EPS blocks and the primary consideration is the proper selection of pavement material types and thicknesses based on the underlying EPS-block geofoam properties. The load bearing analysis is part of the internal stability design phase. The basis of the load bearing analysis procedure is initially presented followed by a summary of the design procedure.

2

BASIS OF THE LOAD BEARING ANALYSIS DESIGN PROCEDURE

2.1 Design goals The primary internal stability issue for EPS-block geofoam embankments is the load bearing capacity of the EPS geofoam. A load bearing capacity analysis consists of selecting an EPS type with adequate properties to support the overlying pavement system and traffic loads without excessive EPS compression that could lead to excessive settlement of the pavement surface as shown in Figure 2. To ensure adequate performance of the EPS blocks, three design goals must be achieved. First, the initial (immediate) deformations under dead or gravity loads from the overlying pavement system must be within acceptable limits. Second, the long-term (for the design life of the fill) creep deformations under the same gravity 982

Figure 2.

Load bearing failure of the EPS blocks resulting in excessive deformation.

Figure 3. Stress-strain behavior of 21 kg/m3 (1.3 lbf/ft3) EPS block under rapid, strain controlled, unconfined axial compression (Horvath 1995).

loads must be within acceptable limits. Third, non-elastic or irreversible deformations under repetitive traffic loads must be within acceptable limits. Therefore, to accomplish these three design goals, an understanding of the compressive, time-dependent (creep), and cyclic stressstrain behavior of EPS-block geofoam is required. An overview of each of these three behaviors is subsequently provided. 2.1.1 Compressive stress-strain behavior Figure 3 shows the typical uniaxial compression stress-strain response of an EPS-block specimen. The test was performed on a block-molded EPS specimen with a density of 21 kg/m3 (1.3 lbf/ft3). However, the stress-strain response for other densities are qualitatively similar (Horvath 1995). As shown by Figure 3, EPS does not typically exhibit failure like other solid materials used in construction (metals, concretes, wood) by a physical rupture of the material when uniformly loaded. Additionally, EPS does not behave like soil or other particulate materials where inter-particle slippage occurs and a steady state or residual strength develops at large strains. The behavior of EPS is continuously work (strain) hardening in nature because the EPS essentially crushes one dimensionally back to its original solid polystyrene state. The stress-strain behavior of EPS shown in Figure 3 can be divided into the following four zones: (1) an initial linear response zone, (2) a yielding zone, (3) a linear and work hardening zone, and (4) a non linear but still work hardening zone (Horvath 1995). Horvath (1995) indicates that the limit of the initial linear response of Zone 1 extends to strains between 1 and 1.5 percent with the larger strain at the end of the linear region occurring with an increase in EPS density. Therefore, for design it can be conservatively concluded that the stress-strain behavior of EPS-block geofoam is both linear and elastic up to a compressive 983

Figure 4. Isochronous stress-strain curves for 23.5 kg/m3 (1.47 lbf/ft3) block-molded EPS based on unconfined axial compression creep tests (Horvath 1995).

strain of approximately 1 percent. The compressive stress at 1 percent strain, as measured in a standard rapid-loading compression test, is defined as the elastic limit stress, σe. Consequently, the design goal of limiting initial deformations under dead loads from the overlying pavement system can be achieved by limiting loads to less than the elastic limit stress of the EPS block. The slope of the initial linear portion of the stress-strain relationship (see Zone 1 of Figure 3) is defined as the initial tangent Young’s modulus, Eti. Although the compressive strength is not explicitly used in the load bearing design procedure that will be described herein because the compressive strength is typically defined as the compressive resistance at 10 percent deformation (American Society for Testing and Materials 1999) and this strength occurs in the Zone 1 and 2 transition area, the compressive strength is used during manufacturing quality assurance and control (MQA/MQC). 2.1.2 Time-dependent stress-strain behavior (creep) A reliable mathematical model to estimate long-term vertical strain of EPS blocks under sustained loads is currently not available (Arellano et al. 2001; Stark et al. 2004a). Therefore, the current state of practice for considering creep strains in the design of EPS block embankments is to base the design on laboratory creep tests on small specimens trimmed from the same EPS block that will be used in construction or to base the design on published observations of the creep behavior of EPS. Figure 4 provides isochronous stress-strain relationships based on the results of creep tests. As shown in Figure 4, EPS will exhibit large creep deformations almost immediately if stresses are near the compressive strength. Therefore, to produce acceptable strain levels in lightweight fill applications, stress levels must be kept low relative to the compressive strength. Also, the isochronous relationships tend to be predominantly linear up to strains of about 1 to 1.5 percent. Lower density EPS tends to creep more than higher density EPS at the same relative stress level. Horvath (1995) summarized the published observations about the creep behavior of EPS geofoam in terms of the immediate strain rate produced by an applied stress. If the applied stress produces an immediate strain of 0.5 percent or less, the creep strains will be negligible even when projected for 50 years or more. If the applied stress produces an immediate strain between 0.5 percent and 1 percent, the geofoam creep strains will be tolerable (less than 984

1 percent) in lightweight fill applications even when projected for 50 years or more. If the applied stress produces an immediate strain greater than 1 percent, creep strains can rapidly increase and become excessive for lightweight fill geofoam applications. Based on these general observations, the compressive stress at a vertical strain of 1 percent, i.e. the elastic-limit stress, appears to correspond to a threshold stress level for the development of significant creep effects. Therefore, the design goal of limiting long-term creep deformations within acceptable limits may be achieved by limiting field applied stresses to less than the elastic limit stress until more reliable creep models are developed. If the applied stress is less than the elastic limit stress, creep strains within the EPS mass under sustained loads are expected to be within acceptable limits of 0.5 to 1 percent strain over 50 to 100 years. 2.1.3 Cyclic stress-strain behavior Figure 5 provides a typical stress-strain plot of an EPS-block geofoam specimen subjected to cyclic loading. As the stress level extends beyond the elastic limit stress, there is both plastic deformation as well as a decrease in the magnitude of the average tangent, Young’s modulus. Therefore, the design goal of limiting non-elastic or irreversible deformations under repetitive traffic loads also may be achieved by limiting maximum applied stresses to less than the elastic limit stress. This conclusion concerning behavior under cyclic loads is based on testing relatively small specimens prepared from samples cut from full-size blocks of EPS. There is a lack of information at the present time concerning the cyclic loading behavior of full-size EPS blocks. 2.2 Recommended load bearing design approach The recommended load bearing design approach included the NCHRP design guideline for stand-alone embankments and the one presented herein is an explicit deformation-based design method. It is based on the recognition that the compressive strength of EPS does not quantify the deformation characteristics of EPS-block geofoam. As previously shown, based on a review of the general compressive, time-dependent (creep), and cyclic stressstrain behavior of EPS-block geofoam specimens, the three load bearing design goals can all be achieved by limiting dead and live loads to within the elastic limit stress of the EPS blocks.

Figure 5.

Cyclic load behavior for 13 kg/m3 (0.81 lbf/ft3) block-molded EPS (Horvath 1995).

985

Therefore, a designation system based on elastic limit stress is included in the NCHRP recommended material and construction standard. Table 1 provides the required elastic limit stress values for various EPS densities. EPS densities are provided because it is a useful physical property for MQA/MQC. The basis for the values indicated in Table 1 is presented in the NCHRP report and an overview is provided by Arellano and Stark (2001; Stark et al. 2004a). The use of EPS40 directly below the pavement system is not recommended because it possesses the lowest density. One advantage of a deformation-based design procedure is that the calculation of applied stresses at various locations within the EPS mass allows for location specific selection of EPS blocks with elastic limit stress values that exceed the anticipated applied stresses. Therefore, the density of the EPS blocks within the embankment can be optimized and specified for various portions of the embankment. Therefore, with a deformation-based design it is possible to select an EPS density that provides adequate load-bearing capacity within tolerable settlements without requiring an inefficient density. Because the applied vertical stress within an embankment decreases with depth under the pavement and side slopes, it is possible to use multiple densities of EPS blocks in an embankment. For example, lower density blocks can be used at greater depths and/or under the side slopes and higher density blocks used directly under the pavement system. One advantage of a deformation-based design procedure is that the calculation of applied stresses at various locations within the EPS mass allows for the explicit selection of EPS blocks with elastic limit stress values that exceed the anticipated applied stresses. Therefore, the density of the EPS blocks can be optimized and thus specified for various portions of the embankment. Therefore, with a deformation-based design it is possible to select an EPS Table 1.

EPS-block geofoam elastic limit stress and initial tangent Young’s modulus requirements.

Material designation

Dry density/unit weight of each block as a whole, kg/m3 (lbf/ft3)

Dry density/unit weight of a test specimen, kg/m3 (lbf/ft3)

Elastic limit stress, kPa (lbs/in2)

EPS40 EPS50 EPS70 EPS100

16 (1.0) 20 (1.25) 24 (1.5) 32 (2.0)

15 (0.90) 18 (1.15) 22 (1.35) 29 (1.80)

40 (5.8) 50 (7.2) 70 (10.1) 100 (14.5)

Figure 6.

EPS-block geofoam prices.

986

density that provides adequate load-bearing capacity within tolerable settlements without requiring an inefficient density. Because the applied vertical stress within an embankment decreases with depth under the pavement and side slopes, it is possible to use multiple densities of EPS blocks in an embankment. For example, lower density blocks can be used at greater depths and/or under the side slopes than higher density blocks that have to be used directly under the pavement system. The reason for minimizing the use of excessively high density EPS block is that the cost of EPS block is linked to the block density as shown by Figure 6. Therefore, there is a cost incentive to rationally select one or more EPS densities within a proposed embankment, with blocks of different density placed according to the applied vertical stresses. Therefore, an advantage of the recommended deformation-based design procedure is that the calculation of stresses and strains within the EPS mass allows the selection of the type of EPS blocks to be optimized by selecting blocks with the lowest density that will yield a minimum elastic limit stress that exceeds the anticipated applied stresses. As shown by Figure 6, the selection of EPS blocks with the lowest possible density yields a cost efficient EPS-block geofoam embankment. 3

DESIGN PROCEDURE

3.1 Overview The procedure for evaluating the load bearing capacity of EPS blocks as part of internal stability that was incorporated in the NCHRP 24–11(01) design guideline can be separated into two parts. The objective of Part 1 is to determine the traffic and gravity load stresses applied by the pavement system to the top of the EPS blocks to select the type of EPS that should be used directly beneath the pavement system. Part 1 consists of the following eight steps: (1) Estimate traffic loads, (2) Add impact allowance to traffic loads, (3) Estimate traffic stresses at the top of the EPS blocks, (4) Estimate gravity stresses at the top of the EPS blocks, (5) Calculate total stresses at top of the EPS blocks, (6) Determine minimum required elastic limit stress for the EPS blocks directly beneath the pavement system, (7) Select appropriate EPS block type to satisfy the required EPS elastic limit stress for underneath the pavement system, e.g., EPS50, EPS70, or EPS100, and (8) Select preliminary pavement system type and determine if a load distribution layer is required. The objective of Part 2 is to determine the traffic and gravity load stresses applied at various depths within the EPS block fill mass to select the appropriate EPS for use at these various depths within the embankment. Part 2 consists of the following five steps: (9) Estimate traffic stresses at various depths within the EPS block fill mass, (10) Estimate gravity stresses at various depths within the EPS blocks, (11) Calculate total stresses at various depths within the EPS blocks, (12) Determine minimum required elastic limit stress at various depths within the fill mass, and (13) Select appropriate EPS block to satisfy the required EPS elastic limit stress at various depths in the embankment. The details for each step of the load bearing design procedure can be found in the NCHRP reports (Stark et al. 2004a; Stark et al. 2004b). A brief synopsis of the key aspects of the load bearing design procedure is provided here. 3.2 Selection of EPS type directly below the pavement system In Step 1, the largest live or traffic load expected on the roadway above the embankment is estimated. In Step 2, an allowance for impact forces from dynamic, vibratory, and impact effects of traffic may be considered. The Japanese Public Works Research Institute (1992) recommends an impact coefficient of 0.3. Therefore, an impact coefficient of 0.3 can be applied to the live load for traffic that is determined in Step 1 and the total load applied is the dead plus live loads. The objective of Step 3 is to estimate the dissipation of vertical stress through the pavement system so that an estimate of the traffic stresses at the top of the EPS fill mass can be 987

obtained. Various pavement systems, with and without a load distribution layer between the pavement system and the EPS blocks, should be evaluated to determine which pavement system alternative is most cost effective. The live load stresses at the surface of the EPS fill mass can be reduced by including a load distribution layer between the pavement system and EPS blocks. In addition to reducing stresses through stress distribution, the load distribution layer may also provide lateral confinement of the overlying unbound pavement layers. This additional lateral confinement compared to the confinement provided by the EPS blocks may allow the use of a minimum pavement system thickness. Therefore, the use of a load distribution layer may also decrease gravity load stresses from the pavement system. The type of load distribution layer that has been predominantly used in practice since the earliest EPSblock geofoam lightweight fills in Norway in the 1970s is a 100 to 150 mm (4 to 6 in.) thick reinforced Portland cement concrete (PCC) slab. The primary disadvantage of a PCC load distribution layer is that PCC slabs generally represent a significant relative cost. Alternative load distribution layers for reinforcement that can be considered in pavement design include a geogrid, geocell with soil or PCC fill, and soil cement. Step 4 consists of determining the stresses resulting from the gravity load of the pavement system and any road hardware placed on top of the roadway. Step 5 consists of calculating the total stress at the surface of the of EPS blocks directly underlying the pavement system. This total stress, σtotal, is the sum of the live load obtained in Step 3 and the gravity stress obtained in Step 4. Step 6 consists of determining the minimum required elastic limit stress for the top layer of blocks. The minimum required elastic limit stress for the top layer of EPS blocks that will be located directly beneath the pavement system can be calculated by multiplying σtotal from Step 5 by a factor of safety as shown by Equation (1). σe ≥ σtotal ∗ FS

(1)

where σe is the minimum required elastic limit stress of EPS and FS is a factor of safety. The main component of σtotal is the traffic stress and not the gravity stress from the pavement. Because traffic is a main component of σtotal and traffic is a transient load like wind loading, a factor of safety of 1.2 is recommended for the load bearing analysis. This is the same value of factor of safety recommended for other transient or temporary loadings such as wind, hydrostatic, and seismic used for external stability analyses. Step 7 consists of selecting an EPS type from Table 1 that exhibits an elastic limit stress greater than or equal to the required σe determined in Step 6. The EPS selected will be the EPS block type that will be used directly beneath the pavement system. The required depth for the selected EPS type will be dependent on the stresses within the EPS fill mass that will be determined at various depths as part of Steps 9 through 13. However, the EPS type selected in Step 7 should extend to a minimum depth of 610 mm (24 in.). This minimum depth is recommended because it is typically the critical depth assumed in pavement design for selection of an average resilient modulus for design of the pavement system (Huang 1993). The use of EPS40 is not recommended directly beneath paved areas. If an EPS with an elastic limit stress greater than 100 kPa (14.5 lbs/in2), i.e. EPS100 is required, consideration can be given to contacting local molders to determine if EPS-block geofoam with an elastic limit stress greater than 100 kPa can be molded for the project. If EPS blocks with a higher elastic limit stress than what is currently available locally is required, consideration can be given to modifying the pavement system design to further distribute live loads and decrease stresses at the top of the EPS blocks or within the EPS block fill mass. Step 8 consists of performing a cost analysis to select an optimal pavement system that can be used over the type of EPS blocks determined in Step 7. Various types of pavement systems may be considered in the cost analysis such as asphalt concrete, Portland cement concrete, and a composite pavement system. The cost analysis can also be used to determine if a PCC separation layer between the pavement and EPS is cost effective. The optimal pavement system that is selected based on this cost analysis will be used in Steps 9 through 13.

988

3.3 Selection of EPS type at various depths within the EPS block fill mass Step 9 consists of estimating traffic stresses at various depths within the EPS blocks. This step estimates the dissipation of traffic induced stresses with depth through the EPS blocks of the embankment. The 1 (horizontal) to 2 (vertical) approximate or Boussinesq stress distribution theory can be used to estimate traffic induced stresses at various depths within the EPS fill mass. Based on an analysis performed during the NCHRP study and the results of a fullscale model test that was performed at the Norwegian Road Research Laboratory (Aabøe 1993; Aabøe 2000) to investigate the time-dependent performance of EPS-block geofoam, a 1 (horizontal) to 2 (vertical) distribution of vertical stresses through EPS blocks was found to be in agreement with the measured vertical stresses, which showed a stress distribution of 1 (horizontal) to 1.8 (vertical). At depths where the traffic vertical stresses overlap based on the 1 (horizontal) to 2 (vertical) method, the approximate stress distribution of closely spaced loaded areas provided by Sowers (1979) can be used to estimate the total stress resulting from the individual overlapping traffic stresses. In Step 10, the stresses resulting from the gravity load of the pavement system, any road hardware placed on top of the roadway, and the EPS blocks are estimated. The procedure used to obtain the stress distribution at the center of earth embankments (U.S. Army Corps of Engineers 1994) can be used to obtain an estimate of the increase in vertical stress at the centerline of the geofoam embankment at various depths due to the increase in gravity stress of the pavement system. This procedure is also described in the NCHRP report (Stark et al. 2004a). Step 11 consists of calculating the total stresses at various depths within the EPS fill mass. This total stress is the sum of the live load traffic stress obtained in Step 9 and the gravity stress obtained in Step 10. Step 12 consists of determining the minimum required EPS block elastic limit stress at various depths. Equation (1) can also be used in Step 12 to determine the minimum required elastic limit stress except that σtotal is the value determined in Step 11. Step 13 consists of selecting an EPS type from Table 1 that exhibits an elastic limit stress greater than or equal to the required σe determined in Step 12. In summary, the basic procedure for designing against load bearing failure is to calculate the maximum vertical stresses at various levels within the EPS mass (typically the pavement system/EPS interface is most critical) and select the EPS that exhibits an elastic limit stress that is greater than the calculated or required elastic limit stress at the depth being considered. 4

CONCLUSIONS

The primary internal stability issue for EPS-block geofoam embankments is the load bearing capacity of the EPS geofoam fill mass. Load bearing capacity analysis is Step 14 of the procedure to design EPS-block geofoam stand-alone embankments over soft ground that is included in the NCHRP design guideline. The recommended load bearing design approach is based on specifying EPS blocks that exhibit an elastic limit stress greater than the estimated total applied stresses to ensure that the three design goals of load bearing capacity design are achieved. These goals are limiting the initial (immediate) deformations under dead or gravity loads from the overlying pavement system, limiting the long-term creep deformations under the same gravity loads, and limiting non-elastic or irreversible deformations under repetitive traffic loads to within acceptable limits. The basic procedure for designing against load bearing failure is to calculate the maximum vertical stresses at various levels within the EPS mass (typically the pavement system/EPS interface is most critical) and select the EPS that exhibits an elastic limit stress that is greater than the calculated or required elastic limit stress at the depth being considered. An overview of the load bearing capacity procedure was provided. The primary advantage of the explicit deformation-based design method is that the calculation of stresses and strains within the EPS mass allows the selection of the type of EPS

989

blocks to be optimized by selecting blocks with the lowest density that will yield the required elastic limit stress. The selection of EPS block with the lowest possible density will yield a cost efficient EPS-block geofoam embankment. ACKNOWLEDGEMENTS Authors would like to thank NCHRP for providing funds for this research under Project NCHRP 24–11(01): Geofoam Applications in the Design and Construction of Highway Embankments. In addition, the authors would like to acknowledge the other principle investigators of this NCHRP project including Drs. John S. Horvath and Dov Leshchinsky. The findings, conclusions or recommendations either inferred or specifically expressed in this document do not necessarily indicate acceptance by the National Academy of Sciences, the Federal Highway Administration, or by the Association for State Highway and Transportation Officials (AASHTO). REFERENCES Aabøe, R. 1993. Deformasjonsegenskaper og spenningsforhold i fyllinger av EPS (Deformation and stress conditions in fills of EPS). Intern Rapport Nr. 1645, Norwegian Public Roads Administration, Oslo, Norway. Aabøe, R. 2000. Long-Term Performance and Durability of EPS as a Lightweight Fill. Nordic Road & Transport Research, 12(1), 4–7. American Society for Testing and Materials. 1999. Standard Test Method for Compressive Properties of Rigid Cellular Plastics. D 1621-94, West Conshohocken, PA. American Society for Testing and Materials. 2007. Terminology for Geosynthetics. D 4439, West Conshohocken, PA. Arellano, D., Aabøe, R. & Stark, T.D. 2001 Comparison of Existing EPS-Block Geofoam Creep Models With Field Measurements. Proc., EPS Geofoam 2001 3rd International Conference (CD-Rom), Salt Lake City, UT. Arellano, D. & Stark, T.D. 2001 Overview of the NCHRP Project Provisional Specification. Proc., EPS Geofoam 2001, 3rd International Conference (CD-Rom), Salt Lake City, UT. Horvath, J.S. 1995. Geofoam Geosynthetic, Scarsdale, NY, Horvath Engineering, P.C. Huang, Y.H. 1993. Pavement Analysis and Design, Englewood Cliffs, NJ, Prentice-Hall. Public Works Research Institute. 1992. Design and Construction Manual for Lightweight Fill with EPS. The Public Works Research Institute of Ministry of Construction and Construction Project Consultants, Inc., Japan. Sowers, G.F. 1979. Introductory Soil Mechanics and Foundations: Geotechnical Engineering, NY, Macmillan Publishing. Stark, T.D., Arellano, D., Horvath, J.S. & Leshchinsky, D. 2004a. Geofoam Applications in the Design and Construction of Highway Embankments. NCHRP Web Document 65 (Project 24–11), Available at http://trb.org/publications/nchrp/nchrp_w65.pdf, Transportation Research Board, Washington, D.C. Stark, T.D., Arellano, D., Horvath, J.S. & Leshchinsky, D. 2004b. Guideline and Recommended Standard for Geofoam Applications in Highway Embankments. NCHRP Report 529, Available at http:// trb.org/publications/nchrp/nchrp_rpt_529.pdf, Transportation Research Board, Washington, D.C. U.S. Army Corps of Engineers. 1994. Settlement Analysis: Technical Engineering and Design Guides as Adapted From the U.S. Army Corps of Engineers, No. 9, New York, ASCE.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A review of the influence of chalk on pavement performance in the South East of England, UK M. Zohrabi Mott MacDonald Ltd, UK

ABSTRACT: This paper aims to investigate if there is a direct correlation between the presence of chalk in the foundation level and the bearing capacity of roads where there is disintegration and cracking of the asphalt surface. Limited evidence has shown that the ingress of water through the surface cracks has resulted in premature failure of roads that are built on chalk substrate. Deflectograph surveys do not represent a valid method of assessing the residual life expectancy as the deflections will depend on the moisture impact on the chalk (i.e. long residual life when dry but no or negative life when chalk softens). The assessment methods and maintenance strategies for pavements resting on chalk will be different to that on other granular foundations. The main aim would be to seal the road surface from moisture ingress. This is particularly relevant to modern (porous) surfaces in comparison to conventional dense surfaces. 1

INTRODUCTION

This study is the outcome of one of four tasks undertaken under a research project into achieving best value through pavement performance monitoring. This paper first provides a review of available information from published literature and secondly, an analysis of available data on three case studies in the South of England within Area 3 of the Highways Agency in the UK. The intention is to understand failure mechanisms when defective pavements allow surface or drainage water to reach the chalk substrate. Chalk is a soft, white, porous form of limestone that is found over approximately 15% of the surface of England. The engineering properties of chalk may vary considerably, and can present significant problems for road construction and maintenance, with phenomena such as ‘puttification’ (i.e. softening into a slurry type material) when worked, and the natural occurrence of swallow holes discontinuities and variability in strength. The location of chalk in the UK can be divided into three general areas as illustrated in Figure 1: • The Northern Province that includes Yorkshire and the Lincolnshire Wolds. • The Southern or Anglo-Paris Basin Province that is south of the Chilterns and includes the North and South Downs together with Dorset and south-east Devon. • The Transitional Province of the Chilterns and East Anglia that includes some characteristics of the North and South Provinces as well as unique characteristics of its own. Further to the above descriptions, chalk is divided into what are referred to as Grey Chalk and White Chalk subgroups. These are further divided into nine formations in the south and five in the north of England. In the South of England, there are significant lengths of road that are built on chalk foundations, most notably being the southern sections of the A34 and the A3 trunk roads. These roads were built 30–40 years ago and have fully flexible or flexible composite pavement structures. In the past few years there have been instances where sections of the road have failed rapidly with little or no warning from ‘routine’ data obtained from TRACS (Traffic 991

Figure 1.

Distribution of chalk in England (after Lord et al., 2002).

Speed Road Assessment Condition Survey) and the Deflectograph. It is of concern that this may be repeated on other sections of the A3 and A34. The purpose of this paper is to explain if there are any correlations between road surface failures (i.e. cracking) when built on chalk as a result of water ingress to the substrate layers. This knowledge can then be used in future maintenance planning in anticipation of further failures. 2

MAINTAINING PAVEMENTS BUILT ON/WITH CHALK

2.1 Problems associated with maintaining pavements built over chalk When chalk comes in contact with water, it tends to soften such that its engineering and load bearing properties are affected. The need for carrying out efficient maintenance of the pavement surfacing layers covering chalk foundations is well-known in the UK. This is particularly applicable to pavements with flexible composite structures and also overlaid concrete pavements, which tend to develop reflection cracking. Reflective cracking allows the water to enter the foundation and come into contact with chalk. This problem (the prevalence of reflection cracking) was highlighted in 1989 in a survey of maintenance engineers in 39 county and metropolitan district authorities in the South East of England (Walsh, 1989). A summary of the main points of this study are given below, and although the survey focussed on SE England, the problem of reflective cracking is widespread throughout the UK. Intuitively the effect of reflective cracking in terms of ingress of water is serious although, records of definitive studies are not available. Due to economic considerations there is a large proportion of cement-bound roadbases in SE England (i.e. at certain times they have been less expensive than bitumen-bound roadbases) and may be generally considered to be more durable. In some counties cement-bound material (CBM) is used in preference to local aggregate because the natural local aggregate is flint gravel, which often does not adhere well to bitumen and thus makes relatively poor quality asphalt. Another relevant factor is that flint gravel has a high coefficient of thermal expansion when compared to limestone and some igneous rocks, which can exacerbate the bitumen-aggregate adhesion problem. The problem of poor adhesion can rapidly accelerate if water enters the pavement, resulting in serious structural and serviceability problems. 992

In addition to the above, the south east of England is an area where traffic levels on the motorway, trunk and principal road networks are typically high, and due to the high trafficking loads, pavements have had to be strengthened. Traditionally this has been carried out by overlaying with layers of asphalt, which have sometimes cracked and rutted with time and traffic. As chalk subgrade can soften when in contact with water, the prompt repair of cracked surfacings is a high priority to prevent more serious damage to unbound materials in the pavement structure. 2.1.1 Frost Early pavement engineering literature concerning the presence of chalk and road building is chiefly concerned with the detrimental effect of frost. Chalk subgrades were normally thought to be stable enough to carry heavy traffic loads with only a thin surface construction but it was recognised that most types of chalk were susceptible to frost heave. It was, therefore, recommended that the thickness of surface construction should be determined by the probable maximum depth of frost penetration (DSIR, 1949). At this time damage to roads was considered to be largely caused by frost heave in the subgrade with the recognition that some chalks subgrades were very susceptible to heave. In particular, soft chalks with a saturation moisture content of 20 to 30 per cent were identified as materials most likely to cause problems. Harder chalk varieties, with moisture contents less than 10 per cent, were less likely to give problems and in an undisturbed condition had little tendency to frost heave. However, if chalk was broken up and recompacted, the susceptibility to frost heave was increased with even the hardest chalks giving trouble. During severe winters frost heave was considered to be a common form of damage. Frost heave results from the formation in the soil of horizontal layers of ice. The water required for this phenomenon is drawn from the soil beneath the frozen zone by suction forces associated with the freezing process. Water moves upwards through interstices which, as a result of their small size, remain ice-free at temperatures below 0°C. However, if the permeability of the soil is very low, water cannot move upwards fast enough to promote the growth of the ice layers, and frost heave does not occur. Where the water in soil freezes insitu, most of the expansion takes place into the voids and no appreciable surface movement results. The strength of a subgrade is normally high whilst the soil remains frozen. There may, however, be a very sudden reduction in strength when a thaw sets in, due to the release of water from melting ice lenses in the upper soil strata. The position is aggravated where this water is prevented from draining by frozen soil below. The passage of traffic when the soil is in this condition is liable to cause failure of the surface, particularly where the form of construction possesses little or no rigidity. On thinly surfaced roads the slurried subgrades may be displaced by heavy vehicles and cause adjacent areas of the surfacing to heave up which has sometimes been confused with frost heave. It follows that the thaw may not affect the subgrade until several days after the air temperature rises above freezing point. This has often been found to be a more critical time (from the point of view of possible damage to roads) than the actual freezing period (Croney, 1949). The severe winter in 1963 was a cause of damage to the Maidstone By-Pass, and was largely due to an underestimation of the degree of likely frost penetration when designing the surface pavement layers. Damage was confined to lengths of the motorway which were constructed on clay and where chalk had been used to make up the total thickness of construction required. It was found that the frost heave damage was as a result of the formation of ice lenses in the chalk. Although chalk was known to be prone to frost damage and a minimum surfacing cover of 380 mm of non-frost susceptible material was specified, it was insufficient since the frost penetrated to 584 mm (Young and Currer, 1964). In the absence of freezing conditions natural chalk has considerable strength and even when excavated and re-compacted in embankments, strength comparable with that of the natural material is developed once any pore pressures generated by the compaction process have been dissipated. The harder varieties of chalk, again in the absence of sub-zero temperatures, will generally satisfy the strength requirements for sub-base materials. However, 993

due to the marked frost-susceptibility of all forms of chalk manifested by a temporary but severe loss of strength on thawing, in practice little advantage can be taken of the normally high stability of the material. A pavement of sufficient thickness to prevent the penetration of frost into the chalk must therefore be employed, and (Sherwood and Salt, 1966) stated that in no circumstances can chalk be used as a sub-base. As a consequence of these early observations the risk of damage from frost-heave is minimised at the design stage by excluding frost-susceptible materials such as chalk from the upper 450 mm of construction (Sherwood and Roe, 1986, Highways Agency et al. 1995). By the 1980’s it was thought that cold winters severe enough to cause damage to road foundations were infrequent in Great Britain. To avoid frost damage, therefore, the pavement surface should be sealed and well-drained. 2.1.2 Swallow holes Swallow holes relate to depressions in the ground that allow surface water to enter the underground passages (especially in limestone) and formed by solution or by collapse of a cavern roof. They are one of the natural dissolution features in chalk. Swallow Hole problems in chalk are a characteristic of areas where chalk is present beneath a cover of younger deposits and manifest as conical or dish-shaped depressions in the ground. They may vary in diameter from a few metres to 25 m but can be as large as 100 m. The configuring underground structure of swallow holes is not seen unless exposed at the side of an excavation. In this situation they are often seen to lie over a more-or-less vertical hole in the chalk known as a pipe. This usually becomes smaller or disappears with depth in the plane of section, and is filled with gravel, sand or clay carried down from overlying deposits. These pipes are not always accompanied by a surface depression. New swallow holes often appear at the surface without warning after a period of heavy rain or following the passage of construction plant across the site. They often have the form of a circular shaft with steep sides. Some seen on the Beaconsfield By-pass (M40) were 1–2 m in diameter and about 2 m deep. Normal weathering over a period of time reduces the swallow hole to the wider rounded depression usually seen at the surface. Sudden appearance of swallow holes at the surface results from the collapse of overlying material due to the solution of the underlying chalk either by percolating rainwater or by the movement of underground water at the water table or lower levels. If there is a more generally distributed lowering of the chalk surface (due to solution) below overlying deposits, the deposits may move gradually into the voids and replace the removed chalk, but with a more loose, less dense state of packing. This could account for the formation of a depression when runoff from a road onto the ground is concentrated at a point, as was observed during the construction of the M4 motorway in the Hermitage area in Berkshire, where it crosses fine sands of the Reading Beds overlying the Chalk. Pipes and swallow holes in chalk can give rise to engineering problems in building foundations and have been a cause of subsidence. Likewise, construction of pavements over chalk subgrades may present problems if undiscovered swallow holes occur, as they may cause subsidence during or after construction of the earthworks or pavement surfacing. In this regard site investigation for the M2 motorway discovered cavities that had to be infilled with compacted sand from nearby earthworks, but did not identify a swallow hole. This in time resulted in damage to the hard shoulder (Higginbottom, 1965). The occurrence of swallow holes and of unrecorded mines in chalk areas is a matter of concern in route planning and road construction, as if they remain undetected, they can lead to subsidence during construction or in service. There is always the possibility that subsidence may occur during service because 994

of the re-activation of old swallow holes or the appearance of new ones (West and Dumbleton, 1972). In April 2002, the eastbound carriageway of the A2 trunk road at the Blackheath Hill junction with Maidstone Hill was the scene of a collapse resulting in a void measuring 9 m long by 3 metres wide and 4 metres deep. Two further smaller voids appeared over subsequent weeks. Settlement of the ground surface and appearance of sink holes resulted from a loss of support from the ground beneath. Most undisturbed ground types are stable and the above mechanism tends not to occur to any significant degree, but at Blackheath Hill, the Thanet Sand is relatively young and unconsolidated and the quarry/mine fills are loose. Both are prone therefore to undergoing densification and a reduction in volume, which results in loss of support at the ground surface. A review of several possible causes of collapse showed that a sudden deluge of water washed the Thanet Sand under the road into an underlying void, causing settlement of the road. It was not possible to identify the source of the water but the hard surface cover of the road minimised the impact of a flash flood. A more likely source of water was thought to be a mains water leak that resulted in the localised subsidence (Transport for London, 2002). 2.1.3 Instability of reworked chalk In the 1960’s it became obvious that the construction of a network of new motorways and trunk roads in the South East of England would require the construction of large quantities of chalk earthworks. At that time limited information was available on the construction of mass earthworks using chalk, so a study was conducted into some of the problems associated on earthworks in soft chalk (Parsons, 1967). Investigations on major road construction sites indicate that the compaction of chalk fill material can be treated in a similar manner to the compaction of soils generally. The compaction of the softer varieties of chalk which are the types usually encountered in road works with saturation moisture content exceeding 20 per cent, requires a compaction effort fairly similar to that required for clay soils in this country (RRL, 1971). The natural moisture content of chalk can sometimes exceed 35 per cent and, during earthworks construction, ripping and compaction processes partly break down the natural structure of the chalk which releases some of the contained water. As water is expelled from the voids a chalk slurry can be created and if the moisture content and fines content generated are sufficiently high, a temporarily unstable fill material can result. This characteristic of chalk behaviour is the phenomenon of ‘puttification’ and is usually associated with soft, fine chalks below the water table. A consequence of this is that the putty chalk could be erroneously assumed to represent the true in-situ conditions, although if it is undisturbed and at a stable moisture content, the material can be suitable for construction. As noted above softer types of chalk are those most likely to exhibit unstable conditions. During the course of investigations instability has usually been found to occur within the upper layers of compacted fill. The passage of heavily loaded scrapers over soft chalk can cause severe rutting and ‘spongy’ conditions which can prevail for substantial periods. If this occurs, work often has to be suspended for a period of weeks until the stability of the material returns to a level that work can continue. Attempts to relate the onset of the unstable conditions to a unique value of moisture content have not been successful, but close observation of the earthwork operations have indicated that the major cause of unstable conditions is the crushing of chalk lumps that release water. However, during good drying weather the released water evaporates and chalk re-attains a condition that allows compaction of the material to be restarted and will produce a firm and stable layer. However, if sufficient drying does not occur, this free water causes positive pore-water pressures to be produced during compaction of the fill, resulting in spongy conditions under traffic. It was been noted that these pore-water pressures typically dissipate over a period of three to four weeks. During 1975 and 1976 eleven road construction sites involving chalk earthworks were visited to measure the physical properties of the chalk, including the crushing values and to relate these to the condition of the fill material (Ingoldby and Parsons, 1977). The relation established between the moisture content and the degree of crushing (percentage Passing 995

20 mm BS sieve) of the compacted fill at the onset of unstable conditions indicated that stable conditions are always likely at moisture contents below 23 per cent. If the moisture content increases above 23 per cent, stable conditions can be maintained by progressively reducing the degree of crushing. It follows that a classification for chalk related to its stability, as a freshly placed fill material, must be based on the prediction of both moisture content and degree of crushing. 3

CASE STUDIES

3.1 Case study 1: A34 Lichfield to Whitchurch, UK This stretch of road on the A34 in Hampshire and Berkshire includes 700 m of fully flexible pavement with a further 3.3 km of flexible composite constructions. This section of road has needed substantial maintenance treatments in the past decade due to the appearance of extensive cracking and potholes. It was stated that these defects appeared quite suddenly and unexpectedly, which was thought to be in some way linked to the chalk subgrade. Three different pavement investigations have been carried out in this study, including the analysis of ‘old’ deflection data, a multi-layer linear elastic stress analysis, and taking account of the opinions of experienced pavement and geotechnical engineers. The pavement has received a number of treatments in the northbound direction, including 40–100 mm overlay in 1993, with surface dressing the adjacent section in 1994 and a further 60 mm inlay treatment to the full length in 2004. The southbound carriageway was reconstructed between 1998, 2000 and 2004 after a series of holding works (i.e. temporary repairs to keep the road serviceable for a few years) in 1996 and 1998. An investigation was carried out by Hampshire County Council in 1995 which showed little correlation between surface distress and deflection measurements. This was consistent with a strong subgrade (i.e. low surface deflections). Deflectograph deflections showed deterioration from 1992 to 1994 (lower residual lives) but no correlation was found between surface distress and low residual life. Test pit results showed that chalk subgrade CBR was in excess of 10%. The subbase samples showed high moisture content in cracked areas (up to 14%) compared to 6% in sound areas. Limited CCTV survey showed some drainage blockages which may have been significant although they were not directly linked to pumping

Figure 2.

Comparison of deflections from Deflectograph between two periods.

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observed on the surface. Treatment design included either a bituminous overlay of some 120 mm including some inlay or full/partial reconstruction. One independent investigation carried out in 1995 showed that the bound layers had deteriorated but the unbound layers were in good condition. In 2001, a full investigation was also carried out on the same site. This showed that the bituminous surfacing was generally in poor condition throughout, with lean concrete roadbase being in ‘poor’ condition category (85th and 50th %ile). The equivalent foundation had a California Bearing Ratio (CBR) of 6–8%. Visual inspection showed cracking (predominantly transverse), rutting and ravelling (surface disintegration). The investigation report showed that the condition of surfacing and concrete had deteriorated, especially from back-calculated stiffnesses. Treatment design included substantial overlays (150–200 mm including some form of reinforcement in asphalt layers), full/partial reconstruction or crack and seat plus an overlay. A comparison between Deflectograph deflections measured in 1995 and 2001 has shown that in most cases the values had not increased between the two periods (see Figure 2). This is often the case with thicker asphalt pavements, as deflection values are dominated by the stiffness of the subgrade. This would indicate that the condition of the pavement as a whole, and the foundation in particular, has not changed at the sites under investigation. This in turn suggests the deflection of flexible composite pavements on strong foundations is not a particularly good indicator of the condition of the upper bound layers. In one section the deflections increased. This could be as a result of the softening of the foundation as this section was heavily patched before 2001 and had large amounts of transverse cracks away from the patches. Therefore, no direct correlation was found between the pavement failures and the presence of chalk substrate. 3.2 Case study 2: A34 South of Whitchurch This stretch of road had a flexible composite construction with a total thickness of no more than 200 mm. After opening in the mid 1970s the pavement received a deep inlay in the 1990s. Rutting and potholing became more evident in 2003 and 2004. A capital maintenance scheme was then carried out during 2005 including Lane 1 inlays where rutting and potholing and failing patches were present. The original design was thought to be for around 10 msa which equates to a commercial vehicle count of around 1300 per day. Since the road was opened, traffic has increased significantly and in 2004 the commercial vehicle count was approximately 2400 per day.

Figure 3. Deep patching and adjacent defects in February 2005.

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Figure 4. Variation in pavement structure from cored materials.

A detailed site investigation was carried out in March 2006 to measure the condition of the pavement using Falling Weight Deflectometer (FWD), Dynamic Cone Penetrometer (DCP), Ground Penetrating Radar (GPR) and visual measurements. From these measurements the foundation was shown to give good support with subbase CBR values all in excess of 100% and subgrade CBR values 40% or more. The estimated foundation stiffness from FWD ranged from 160 to 390 MPa. The condition of the bound materials was found to be variable. The pavement has relatively thin upper bound layer and, considering the large increase in traffic and limited maintenance over the 30 years since it was constructed, the pavement can be considered to have performed well since its construction. This case study gives a positive example of how well a good wet-mix base and relatively thin bound layer can perform when constructed on a sound foundation, when protected from moisture ingress. The reported increased incidence of defects in the last five years is compatible with the change in policy relating to regular surface dressing of pavements, which ended in the late 1990s, possibly leading to water ingress into underlying substrate. From the data examined there is no indication that the underlying chalk has played any significant or direct role in the deterioration of the pavement. 3.3 Case study 3: A34 Chilton This flexible composite pavement was opened in 1974 and has a variety of pavement layer thicknesses, comprising generally 140 mm asphalt over 175 mm of CBM. In 1995 a 100 mm inlay in Lanes 1 and 2 was carried out, followed by maintenance in 2000 when 60 mm of asphalt was planed out and replaced with 80 mm of asphalt. Cores showed the condition of the pavement layers to be extremely variable, and in many cases ‘deteriorated’, as illustrated in Figure 5. Most of the section of the road under consideration is founded upon chalk, with a limited amount on Coombe deposit (a compact silty and chalky deposit derived from frost shattered chalk fragments), sands, and grit. In 2002 narrow transverse cracks were seen to spread generally across the pavement, although more concentrated in the northern areas. A number of patches were required to remove spalling cracks and potholes before more serious and general deterioration was observed in 2003/04. As a consequence of the deterioration a number of small works schemes were carried out to remove severe cracking and potholes, similar to those seen in Figure 6. Figure 7 shows deflectograph deflections to increase dramatically between 1998 and 2004 in areas founded on ‘Lower Chalk’. The adjacent sections founded on “Chalk Rock” have also increased deflections between 1996 and 2004 but not to the same degree as that on “Lower Chalk”. This increase in deflection in the southbound direction may be due to a combination of the subgrade wetting-up and traffic loading. A number of trial pits excavated on the Southbound direction (see Figure 8) showed expansion of the clay subgrade founded on the chalk substrate with CBR values of around 5%. Drainage also appeared to be a problem through the sandy layer, causing waterlogging and very low strength and resistance to deformation.

Figure 5. An example of the variation in pavement structure from cored materials.

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Figure 6. An example of typical defects recorded at Chilton.

Figure 7. Southbound Deflectograph deflections in Chilton site between 1996 and 2004.

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Figure 8. Expansion and softening of the subgrade founded on chalk.

CONCLUDING REMARKS & THE WAY FORWARD

4.1 Literature review • Chalk is present over approximately 15% of the surface of England. The engineering properties of the material can vary greatly and may have the qualities of a soft rock or a puttypaste depending on the location, nature of loading and moisture content. • Historically, problems with chalk were thought to be linked to frost action, as due to its porosity chalk can hold a large volume of water. With proper design this problem is avoided if frost susceptible material is not placed within 450 mm of the surface. • When chalk is present as a subgrade and is in a ‘steady state’ (or ‘equilibrium’) with load and moisture conditions, it normally performs well. If, however, this equilibrium is disturbed by carriageway widening or similar engineering works, the material can change to a putty-like consistency which in turn can cause serious structural or serviceability problems that often require expensive maintenance treatments. In exceptional circumstances, it is considered that heavy dynamic loading could cause problems in pavements on chalk subgrades if present with softer sands and clays although documented case histories have not been found. Similarly, the effects of large changes of moisture in chalk subgrades are cause for concern although this is only likely to be a problem if accompanied by severe loading. • Taking into account the history of the road, deflection readings and the findings of the previous reports and the views of the engineers working on the schemes, it appears that the principal causes of the defects on this section of the A34 are quite typical of flexible composite pavements. Aged bituminous materials have cracked over shrinkage cracks in the lean concrete base. The pavement appears to have been designed in the 1970s for a traffic volume of around 12–15 msa and when sections of the pavement were inlaid and reconstructed it had carried more than 25 msa (million standard axles), i.e. the pavement had exceeded its design life. 4.2 Future maintenance considerations • Problems with pavements on chalk subgrades seem to be limited to situations where widening or some other change in construction has taken place and has reworked sensitive chalk material, and/or water has leaked into the chalk. • Because of the rapid failure in the weak concrete (lean mix) base layers and sensitivity of chalk substrate to water ingress, it is important to consider preventative maintenance (e.g. crack sealing) in composite constructions to prevent or delay pavement reconstruction. 999

• Considerations for pavement investigations to identify the cause of pavement distress should concentrate on the following: a. Identify representative pavement areas that are distressed and in good condition. b. Carry out deflection testing using the Deflectograph or FWD on both test areas. c. Compare material quality by taking cores in both areas to: i. Test bound layers for stiffness, strength and grading analysis. ii. Test unbound materials by DCP testing, sampling and moisture content. d. Check whether utilities works, haunching repairs or widening has been carried out. e. The possibility of a change in drainage conditions needs to be checked. REFERENCES Croney, D. 1949. Some cases of frost damage to roads. Road Note 8, Department of Scientific and Industrial Research, Road Research Laboratory (Unpublished Report). Department of Scientific and Industrial Research (DSIR) 1949. Chalk Subgrades. Road Research Laboratory, RN/1093/DC (Unpublished Report). Higginbottom, I.E. 1965. The Engineering Geology of Chalk. Chalk in Earthworks and Foundations, Institution of Civil Engineers, London. Highways Agency, Scottish Office Industry Department, Welsh Office & Department of Environment for Northern Ireland 1995. HD 25/94: maintenance of bituminous roads. Design Manual for Roads and Bridges, Volume 7, Pavement design and maintenance, Section 1. London, HMSO. Ingoldby, H.C. & Parsons, A.W. 1977. The classification of chalk for use as a fill material. TRRL Laboratory Report LR 806, Transport and Road Research Laboratory, Crowthorne, UK. Lord, J.A., Clayton, C.R.I. & Mortimore, R.N. 2002. Engineering in Chalk. CIRIA Publication C574. Construction Industry Research and Information Association, London. Parsons, A.W. 1967. Earthworks in sift chalk. A study of the factors affecting construction. Road Research Laboratory, RRL Report LR112, Crowthorne, UK. RRL 1971. Earthwork Construction in Chalk, Road Research Laboratory Leaflet LF 25, Crowthorne, UK. Sherwood, P.T. & Roe, P.G. 1986. Winter air temperatures in relation to frost damage in roads. TRRL RR45, Transport and Road Research Laboratory, Crowthorne, UK. Sherwood, P.T. & Salt, G.F. 1966. Proposals for a full-scale experiment into the use of a stabilised chalk sub-base. Road Research Laboratory Technical Note No. 109 (Unpublished Report), Crowthorne, UK. Transport for London 2002. A2 Blackheath Hill—Causes of Collapse. Transport for London, Report Ref: 1000110/R/9. Walsh, I.D. 1989. An investigation into effective treatment of reflective cracking. 10th National Workshop on Engineering a better pavement, Institution of Highways and Transportation (IHT). West, G. & Dumbleton, M.J. 1972. Some Observations on swallow holes and mines in the chalk, The Quarterly Journal of Engineering Geology, vol. 5, nos. 1 & 2. Young, A.E. & Currer, E.W.H. 1964. An investigation into frost damage on M20 (Maidstone By-Pass). Department of Scientific and Industrial Research, Road Research Laboratory, LN/482/AEY, EWHC, February 1963 (Unpublished Report).

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Design methodology based on strength and its application to full weathering granite used in highway subgrade Z. Li & C. Dong Hunan Communications Research Institute, Changsha, P.R. China

ABSTRACT: Subgrade yields plastic deformation under dynamic traffic loads cyclic in nature. The plastic deformation increases with the load repetitions and it may lead to failure. In this paper, the distributions dynamic stresses and strains in the pavement and subgrade t were analyzed through an established vehicle-pavement-coupling model. By using strength properties and introducing dynamic failure criteria, a restricted vertical strain of subgrade was established as a failure criterion on the basis of subgrade-pavement failure mechanism emphasizing rutting resistance. The corresponding dynamic stress was considered for establishing strength failure criteria. The design method based on the theory of applied dynamic stress in relation to strength was applied to a pavement having full weathering granite subgrade. The feasibility and application scope of the full weathering granite in highway subgrade was assessed using the design norm. 1

INTRODUCTION

Traffic loads exhibit dynamic and cyclic loading and unloading characteristics within a pavement’s life time. The subgrade shows failure characteristics under the cyclic load. The subgrade deformation is divided into two parts, one is the resilient deformation, and the other is the residual plastic deformation. The resilient deformation is determined by the stiffness of subgrade, and the residual plastic deformation is mainly linked to the strength of subgrade and the applied stress level. The residual plastic deformation accumulates with the repeated load applications. When the applied dynamic stress is less than a certain level, the rate of change of the residual plastic deformation decreases with the number of load cycles, and the subgrade deformation is finally stabilized. When the stress level is greater than a certain level, the residual plastic deformation increases. In this case, the growing subgrade deformation will cause pavement cracks due to the uneven settlement or bending, and then lead damage to the pavement structures. When fully weathered granite is used as highway subgrade fill material, its application becomes restricted because of its high mica content, negligent construction, bad water stability, and small cohesion. For these reasons, according to the features of pavement structures constructed under typical traffic loads in China, using dynamic stresses and adopting subgrade dynamic failure criterion in pavement design methodology was considered in this paper as a viable application in subgrade when the fully weathered granite residual soil are utilized. 2

THE SUBGRADE DYNAMIC DESIGN METHODOLOGY

With dynamic wheel load magnitudes gradually increasing, the deformation and strength of subgrade soils will experience three development stages: slight changes, significant changes and rapid changes. According to the characteristics of these three stages, they were called compaction stage, shear stage and destruction stage, respectively. The three stages were

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divided by two threshold strengths known as the critical strength (σc or Nc ) and the ultimate strength (σu or Nu). When the intensity of load is small or the loading time is short, the subgrade soil will appear with no damage or only slight structural damage. In this case, the subgrade soil mainly shows vertical deformation caused by the vibration compaction effect. When the dynamic load is larger than the critical strength, it may lead to significant increased deformation and decreased strength. During such high deformations, the effect of shear deformation is also gradually increased. At last, when the load applied reaches the limit strength, the phenomenon of rapid increase of the deformation and sudden decrease of the strength will appear as the obvious indications of the complete failure conditions. The damage criteria of the soil under the dynamic load have the following three aspects: limit equilibrium criterion, liquefaction criterion, and strain failure criterion. Under the dynamic traffic loads, the subgrade will yield plastic strain, with the increase of loading time the deformation will increase to lead to failure. Therefore, from a design aspect, in order to control rut, the restricted vertical strain, that is the compressive strain on top of subgrade, should be adopted as a failure criterion in the subgrade design limiting dynamic stress in relation to the strength. Therefore, the subgrade should be designed to meet both the strength and the compressive strain requirements. 2.1 Dynamic strain design As for the un-liquefied subgrade soil, the dynamic stress will gradually decrease and tend to be a stable value with the load repetitions, but the deformation will continue to develop with the ongoing vibration. In order to meet the compressive strain requirement, a restricted vertical strain εzp as the failure criterion is proposed as follows:

ε z , p ≤ [ε zp ]

(1)

Research studies on the compressive strain on top of subgrade is relatively scarce, let alone the common consensus on the value of [εzp]. As for the different projects, the values of [εzp] are different, meanwhile there are no experimental data on the use of [εzp] in the asphalt pavement structural design. So how to determine [εzp] is a problem worthy of study. According to the dynamic fatigue failure characteristics of the subgrade fill materials, under the effect of cyclic dynamic traffic loads, the permanent deformation of the subgrade fill materials will accumulate with the load repetitions, while the deformation rate is determined by the ratio between the dynamic stress and the critical dynamic stress of the subgrade. According to the effect analysis about the road using character, the strain failure criteria of the subgrade under the dynamic loads have the following two aspects: on the one hand is the destruction of subgrade itself, on the other hand is the destruction of the pavement due to excessive subgrade strain. According to the study of Raymond (1979), under the repeated train loads, the Ledy clay subgrade was unlikely to undergo significant damage unless there was spurt slurry in subgrade caused by liquefaction. Therefore, the criterion of failure strain under certain cyclic loads was proposed. A relatively larger strain could be allowed in the railway subgrade to only increase maintenance costs. Makiuchi and Shackel (1976) pointed out that on the road pavement surface vertical strains more than 4 percent was not allowed, therefore, in order to determine failure strain, the differential factor of strain and stress curve was used after 104 load cycles. 2.2 Dynamic stress design When subgrade dynamic stress σd is less than the critical strength, the subgrade residual deformation rate will decrease with loading cycles, and the cumulative residual deformation will gradually tend to be stable. When the subgrade dynamic stress is larger than the strength, the subgrade residual deformation rate will increase with the load cycles, and the subgrade 1002

accumulated permanent deformation will increase as well. Therefore, the applied dynamic stress should meet the strength requirements:

σ d max ≤ [σ cr ]

(2)

The basic idea of soil strength can be described as follows: the greatest stress in need of meeting the requirement that the caused strain is no more than a certain amount of strain under a given number of load applications. Therefore, the dynamic stress and the dynamic strain design are consistent after using the same deformation and damage standard of the subgrade. When the strain level can meet requirement, the corresponding strength value also needs to meet the requirement. 3

STRESS AND STRAIN ANALYSIS UNDER TRAFFIC LOADS

In combination with the actual traffic and road situation, and also considering the nonlinear characteristics of the materials, the plane strain elements were used to simulate the pavement structure. The vehicle-pavement-coupling model was analyzed by the ANSYS finite element (FE) software. The FE model constructed is shown in Figures 1 and 2. In order to consider coupling vibration between the road and the wheels, the contact analysis in ANSYS was undertaken using the elements of TARGE169 and CONTA172. In order to consider plastic behavior of the subgrade, material model used utilized the Druker-Prager yield criteria. The destruction of semi-rigid base pavement structure under the concentrated force was studied and the effect of subgrade modulus on the limited loads was investigated through FE analyses. The results are shown in Figure 3 through 6. Under the traffic loads, the road base got damaged first, and pavement cracking and plastic deformation of the subgrade followed. To avoid this damage, the design must ensure

Figure 1.

Plane strain pavement model.

Figure 2.

Mesh constructed for the vehicle-pavement-coupling model.

1003

Figure 3. Contour plot showing local amplification of plastic deformation.

Figure 4. Plastic strain of the subgrade and pavement graphed with the loading times.

Figure 5. Vertical strain changes with the loads on top of the subgrade.

Figure 6. Vertical strain changes along the cross direction on top of the subgrade.

Table 1. Stress and strain responses of the subgrade and pavement changing with loads (strain × 10–4). Subgrade

Pavement

Load (kN)

Stress (kPa)

Elastic strain

Plastic strain

Stress (kPa)

Elastic strain

Plastic strain

61.068 67.068 73.068 79.068 91.068 97.068 300.0

50.86 57.436 63.423 61.337 60.909 62.247 114.76

0.6358 0.7180 0.7928 0.7667 0.7614 0.7781 1.435

0 0 0.1651 0.7686 2.296 3.195 43.99

123.012 117.616 118.362 119.153 118.687 120.127 220.901

2.050 1.960 1.973 1.986 1.978 2.002 3.682

0 0.1872 0.5494 0.9273 2.145 2.624 2.213

that the maximum vertical strain on top of the subgrade cannot exceed the allowable strain. When the pavement has begun to enter the plastic zone, the elastic strains still increase, and the increase in the plastic strain is relatively moderate. When the maximum elastic strain was reached, the plastic strain increased dramatically. Therefore, the design of the subgrade should meet the requirement that the maximum allowable strain cannot exceed this total strain just when the maximum elastic strain occurred. 1004

Figure 7. The change of vertical stress from pavement to subgrade.

Figure 9. Stress time history diagram of the subgrade and pavement.

Figure 8. The change of transverse stress from pavement to subgrade.

Figure 10. Strain time history diagram of the subgrade and pavement.

From Table 1 and Figures 7 and 8, when the load levels increase, the strains of the subgrade and pavement both increase, and the subgrade first exhibits plastic behavior, then, the whole does. With the load further increasing, the plastic strains in the pavement are changed much more significantly than that in the subgrade. Under the dynamic vehicle loads, the time history of stress at midpoint of the subgrade and pavement is shown in Figures 9 and 10 at the speed of 90 km/h. The maximum stress and strain occurred beneath the centerline of the vehicle wheel loads. The peak strain is about 1.8 × 10–4, and the peak stress is 100 kPa. The points far away from the position of centerline reflect an obvious strain lag effect under the effect of dynamic traffic loads. 4

LARGE-SCALE DYNAMIC MODEL TEST

The size of the test model is designed as follows: vertical length is 2.3 m, horizontal bottom width is 3.6 m, horizontal top width is 2.0 m, and the slope ratio is 1:1. The bicircular loading plates were used to simulate the double rings of the vehicle, and the equivalent circle diameter denoted by d is 21.3 cm. The center distance between the bicircular loading plates is 1.5 d. The single axis load is 100 kN, and the static tire pressure is 0.7 MPa. A dynamic impact coefficient introduced as well ranges from 1.3 to 1.5. In the test, the frequency of load was used to reflect the speed effect on the dynamic characteristics of the structure, and the largest load test frequency is 8 Hz. Soil pressure and deformation and stress and strain of the subgrade and pavement were tested at each separate layer. 1005

4.1 Dynamic stress The dynamic stresses measured at different locations for the loads ranging from 5~75 kN and 5~135 kN are given in Table 2. In the table, 75 represents the load 75 kN. When the loads take value of 75 kN and 135 kN, the corresponding dynamic stresses on top of the subgrade are 0.044 MPa and 0.077 MPa, respectively. 4.2 Dynamic strain The change of permanent deformation of each structural layer with loading cycles can be given by the following formula (3): S pd = Sd 0 N δ

(3)

where, Spd = accumulated residual deformation; N = loading cycles; and Sd0 and δ are experimental constants. Sd0 is an initial deformation, δ reflects the increasing speed of deformation with loading cycles. The regression parameters of Sd0 and of δ are shown in Table 3. 5

DYNAMIC DESIGN INDICES OF GRANITE RESIDUAL SOIL

Using the results of finite element analysis and large-scale dynamic model tests, one can determine dynamic stress and deformation values of an asphalt pavement. Deformation means the permanent deformation of each layer of the pavement after repeated loading. 5.1 Dynamic stress indices From the results of finite element analyses, the dynamic stresses at different locations of the subgrade under the load of 50 kN are shown in Figure 11. In the three full-scale dynamic model tests (the results shown in Table 1), under the load of 75 kN and 135 kN, the maximum dynamic stresses on top of the subgrade were 44 kPa and 77 kPa, respectively. It is noteworthy that the dynamic effect caused by irregularity of the road has been taken into account under the load of 75 kN, which is equivalent to the designed standard static load 100 kN. The corresponding dynamic stress on top of the subgrade is equivalent to the dynamic stress value in the actual subgrade under the standard static load 100 kN. Therefore, the results of finite element analyses and the model tests are identical. Considering the influence of various factors, it is desirable to use the 50 kPa as the top of the subgrade design dynamic stress value. When considering the current larger proportion of overweight vehicles, then, this value should be appropriately raised to 70 kPa. Table 2. The dynamic stresses measured in the pavement and subgrade under dynamic loads (MPa). Depth/m Load/kN

0.0

0.18

0.48

0.78

1.08

1.38

1.68

75 75 135

1.041 1.040 1.879

0.871 0.722 1.456

0.292 0.271 0.468

0.044 0.044 0.077

0.023 0.023 0.041

0.009 0.008 0.015

0.004 0.004 0.006

Table 3. Regression parameters of Sd0 (×10–2) and δ (×10–1).

Sd0 δ

Pavement

Base Subbase

Subgrade Subgrade 0~30 cm 30 cm~60 cm

2.77 2.00

2.42 1.84

1.52 2.15

2.10 1.75

1006

1.05 1.82

–167321 –132576

Figure 11.

Profile showing dynamic stress σy.

5.2 Permanent deformation design indices According to the test results presented in Table 3, after 108 loading cycles, the total permanent deformation is 13.8 mm with 3.52 mm of it occurred in the subgrade (0~30 cm). Such permanent deformation wouldn’t cause failure to the structure, and the produced rut is also allowable. At this time, the permanent deformation corresponding to the subgrade (0~30 cm) is about 1.17%. Therefore, the choice of [εzp] = 1% as the permanent deformation control standard for the top of subgrade is suitable. If the permanent deformation is larger, it may cause destruction to the pavement structure. 6

DYNAMIC DESIGN OF THE FULL WEATHERING GRANITE SUBGRADE

6.1 Dynamic stress analysis of the full weathering granite According to the full weathering granite static loading test, when the static strain comes to 1%, the stress is already more than 50% of the static strength. So, one can use 1% strain as control standard for the full weathering granite. Under this strain control standard, the corresponding strength curves of different experiments were available. The compressive strength curve is shown in Figure 12 and the shear strength curve is shown in Figure 13. Incidentally, the strength curve also called the fatigue curve. And the power function was used to describe it.

σ d , f = kN θ

(4)

where: k and θ are experimental parameters, which are related to the compactness and confining pressure of the sample; σdf – the greatest dynamic stress amplitude in need of meeting the requirement that the caused strain is no more than failure strain under the given loading times of the corresponding curve. In group S148-2, σdf = 216.32 N–0.0643. In pavement’s life time, the axle loads which are converted to the standard axle loads will be more than 108. In this paper, 108 was used as the load number which the subgrade fill materials can bear during the life time. Under this given loading number, the strength values in each group are shown in Table 4. 6.2 Strength design In the design of subgrade, each part of the subgrade and pavement should meet the requirements of dynamic stress and deformation requirements. According to the influence factor analysis of strength, the shear strength of granite residual soil is much smaller than static shear strength, and it is greatly influenced by the moisture content, compactness, confining pressure and the number of traffic loads. When the water content is increased from the optimum water content to nearly saturated water content, the strength will decrease 1007

200

Dynamic strength/kpa

180 160 140 120 100 80 60 40 20

40

60

80

100

120

140

160

180

200

220

confining pressure/kpa

Figure 12. The correlation of strength and confining pressure at K148 + 220. Table 4.

Figure 13. The curve of shear strength at K148 + 220.

Dynamic strength value with allowable strain 0.5% and 1%, and 108 loading times (kPa).

Test group k155-0 k155-5 k155-4 k155-7 k155-9 s148-2 s148-3 s148-4 s148-5 s148-6 s148-7

σd0 (1%) 63.48 σd0 (0.5%) 23.51

56.16 27.14

49.74 16.20

41.67 20.24

31.48 21.99

66.08 27.36

92.45 79.98

136.49 193.01 34.86 77.04 142.73 17.05

57.06 25.04

Table 5. The dynamic strength value with allowable strain 1% and 108 loading times (kPa). K155 + 020 Test groups

0

5

K148 + 220 4

7

9

2

3

4

5

6

7

Compressive strength 63.5 56.2 49.7 41.7 31.5 66.1 92.5 136.5 193.0 34.9 57.1

about 50 percent. With the increase of confining pressure and compactness, the strength increased. The relationship between permanent deformation and loading cycles for the full weathering granite under certain dynamic stress can be given by the following equation (5):

ε p =α N β

1 1+ N

(5)

The soil strength formula is as follows:

σ d , f = kN θ

(6)

The initial compressive strength of the full weathering granite at k155-0 and s148-2 are 206.61 kPa and 216.32 kPa. The initial strength means direct loading until failure at one time. On the condition of the allowable strain of 1% and 108 loading times, the strength values shown in Table 5 are 63.48 kPa and 66.08 kPa, which are basically 1/3rd of the initial strength. Clearly, the strength of granite residual soil significantly decreased under the traffic loads, and cannot meet the requirements of heavy vehicles. The dynamic stress of the subgrade is less than the strength of subgrade fill material during the early stage of loading. But after 108 axle load cycles, the strength of subgrade fill material substantially decreases. When the strain is over 1%, then the damage of subgrade occurred. This is precisely one of the major failures occurred in the existing full weathering granite subgrade. Therefore, in order to meet the strength of 50 kPa and strain of 1% requirements, the full weathering granite should be improved, e.g., treated through cement stabilization. 1008

7

CONCLUSIONS

1. The use of full weathering granite subgrades can cause stability problems on highways. This paper showed that strength design methodology considering dynamic wheel load stresses can be applied to designing the full weathering granite and the cement stabilized soil. 2. After a comprehensive consideration of various factors, 50 kPa can be taken as the limiting dynamic design stress on top of the subgrade. If the present overload is considered, the dynamic design stress can be increased to 70 kPa. 3. The choice of using a limiting vertical strain of [εzp] = 1% for the permanent deformation control on top of subgrade is suitable. REFERENCES Brown, S.F. Repeated load testing of a granular material [J]. J. Geotech. Engrg. Div. ASCE, 2001, 100(7): 825–841. Li, D.Q. Cumulative plastic deformation for fine-grained subgrade soils [J ]. J.of Geo.Engrg, 1996, 122 (12): 1241–1249. Makiuchi, K. and Shackel, B. 1976. Soil characterization using a repeated loading cubical triaxial apparatus. Proceedings, 8th Australian Road Research Board Conference, Vol. 8 (7), pp. 22–29. Raymond, G.P. Gaskin, P.N. and Addo-Abedi, F.Y. Repeated compressive loading of Leda clay, Canadian Geotechnical Journal, Vol. 16(1), Feb, 1979. Raymond, G.P. Repeated compressive loading of Leda clay [J ]. Canadian Geotechnical Journal, 1979, 16(1): 201–207. Toshikazu, et al. Three-Dimensional Analysis of Traffic-Induce Ground Vibration. J. Geo. Eng. ASCE. 1991, 117(8). Trollope, E.H., Lee, I.K. and Morris, J., “Stresses and deformation in two-layer pavement structures under slow repeated loading.” Proc. ARRB, 1962, Vol. 1, Part 2, pp. 693–718.

1009

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Sustainable reconstruction of highways with in-situ reclamation of materials stabilized for heavier loads H. Wen Washington State University, Pullman, WA, USA

T.B. Edil Recycled Materials Resource Center, University of Wisconsin, Madison, WI, USA

ABSTRACT: Development of freight transportation infrastructure, whether it is highway or rail, will need to address several issues to be sustainable and economic. The new infrastructure should sustain higher loads but also last longer, be economic to build, and minimize energy consumption and generation of green house gases for materials production and construction. Upgrading the existing infrastructure to meet the increased load requirements and satisfy these requirements of sustainability is a challenging prospect. To investigate the feasibility of this approach, a field experiment is undertaken at MnROAD facility. Three identical highway sections were constructed except each had a different base course: conventional crushed aggregate, recycled pavement material (RPM), and RPM stabilized with high-carbon fly ash (typically not suitable for concrete production but self-cementitious). A variety of field tests during construction (soil stiffness gauge, dynamic cone penetrometer, nuclear density, light weight deflectometer) and post-construction (falling weight deflectometer) were performed on the instrumented road segments (temperature, moisture content, pavement strain, and stress). Additionally, laboratory material characterization tests (aggregate tests, compaction, permeability, CBR, and resilient modulus) were performed on all three base materials. Comparative behavior and benefits of using recycled materials are investigated. 1

INTRODUCTION

Development of freight transportation infrastructure, whether it is highway or rail, will need to address several issues to be sustainable and economic. The new infrastructure should sustain higher loads but also last longer, be economic to build, and minimize energy consumption and generation of green house gases for materials production and construction. Upgrading the existing infrastructure to meet the increased load requirements and satisfy these requirements of sustainability is a challenging prospect. The reconstruction and upgrade can be made using conventional construction materials and methods. However, conventional construction materials are becoming increasingly expensive as demands on resources intensify. In addition, concerns regarding energy use and greenhouse gas (GHG) emissions associated with generating and delivering conventional construction materials have led to significant interest in exploring alternative materials, such as recycled materials (e.g., recycled pavement materials and industrial byproducts) that can be obtained with minimal energy input and GHG emissions, as well as low cost. With the increasing awareness of building sustainable transportation system, recycled materials and industrial byproducts are increasingly being used for highway construction, especially in pavement base course. The physical properties of recycled materials and industrial byproducts have to be characterized for the purpose of pavement design. For instance, the deteriorated asphalt pavements could be reclaimed full depth and used for base course for the new pavement. The full-depth reclaimed pavement materials (RPM) could also be mixed with industrial byproducts, such as fly ash and cement kiln dust, to increase the stiffness (Li 2008; Wen 2004). When compared to traditional base materials, such as crushed aggregates, the recycled materials 1011

and industrial byproduct often have unique characteristics. For instance, it was found RPM has higher modulus, but also higher permanent deformation than certain crushed aggregate (Wen 2008). When these materials are used for pavement construction, the properties, such as resilient modulus and flexural strength (for bound materials only) have to be characterized as specified in the Mechanistic-Empirical Pavement Design Guide (MEPDG). In addition, the MEPDG does not include the use of many recycled materials and industrial byproducts, such as fly stabilized base materials for which the properties have to be determined. To investigate the feasibility of this approach, a field experiment is undertaken at MnROAD facility. Three identical highway sections were constructed except each had a different base course: conventional crushed aggregate, recycled pavement material (RPM), and RPM stabilized with high-carbon fly ash (typically not suitable for concrete production but self-cementitious). A variety of field tests during construction (soil stiffness gauge, dynamic cone, nuclear density, light weight falling weight deflectometer) and post-construction (falling weight deflectometer) were performed on the instrumented road segments (temperature, moisture content, pavement strain, and stress). Additionally, laboratory material characterization tests (aggregate tests, compaction, permeability, CBR, and resilient modulus) were performed on all three base materials. Comparative behavior and benefits of using recycled materials are investigated. 2

MATERIALS

2.1 RPM and Class 6 aggregate The RPM was produced by pulverizing the in-situ asphalt pavement at MnROAD, a fullscale accelerated pavement testing facility, located in Minnesota. The RPM consisted of 50% of hot mix asphalt and 50% of existing crushed aggregate base course. The Class 6 aggregate is a granite base course material used by MnDOT. The gradations of the RPM and Class 6 are shown in Table 1. 2.2 Fly ash Fly ash obtained from Unit 8 of the Riverside Power Plant in Minneapolis, MN (operated by Xcel Energy) was used to stabilize the RPM. This fly ash has a calcium oxide (CaO) content of 22.37% and a carbon content of 16.35%. Riverside Unit 8 fly ash is a cementitious high-carbon fly ash. A fly ash application rate of 14% by weight of dry mix was used to stabilize RPM as base course. Table 1. Gradation of RPM and class 6. Percent finer Sieve opening (mm)

RPM (%)

Class 6 (%)

37.5

100

100

25

99

100

19

96

98

12.7

86

73

9.5

77

55

4.75

60

32

2

39

11

0.425

13

4

0.075

6

2

1012

3

TEST METHODS

3.1 California bearing ratio CBR tests were conducted on all specimens in accordance with ASTM D 1883. CBR tests on specimens without fly ash were performed immediately after compaction, whereas specimens with fly ash were tested after 7-day and 28-day curing. A surcharge (4.54 kg) was used during CBR testing. 3.2 Resilient modulus Resilient modulus tests were performed on the subgrade soil, Class 6sp, RPM, and RPMfly ash mixtures in accordance with the National Cooperative Highway Research Program (NCHRP) 1-28A test protocol. Three replicates were used for each material. Mr specimens were instrumented with both internal and external linear variable displacement transducers (LVDTs). 3.3 Unconfined compressive strength Unconfined compression tests were conducted on SRPM resilient modulus specimens after the completion of the Mr test, in accordance with ASTM D 5102. All stabilized specimens were loaded at a strain rate of 0.21% per minute. These samples were cured for 7 and 28 days and tested for unconfined compression strength to determine the effect of curing length on unconfined compression strength. 3.4 Dynamic Cone Penetrometer (DCP) DCP is an instrument designed to provide a measure of the in-situ strength of subgrade, subbase, and base materials. A 7.9-kg weight is raised to a height of 57.4 cm and then dropped, driving the 60-degree 20-mm-diameter cone into the soil or aggregate base. The penetration depth per blow is used to estimate the strength or stiffness of the subject materials (DeBeer 1991). 3.5 Light Weight Deflectomer (LWD) LWD device is hand-operated and takes measurements of the deflection of compacted soil that is impacted by a falling weight. The LWD has one sensor directly below the falling weight. The device measures the resulting deflection and estimates a modulus value based on the force required to generate a given deflection for that soil type. 3.6 Falling Weight Deflectometer (FWD) FWD tests were conducted directly on the base courses during the construction. Prior to the placement of HMA, the base course had one month of curing. FWD tests were also conducted on several curing days to monitor the change of the properties of fly ash stabilized RPM. After the placement of HMA surface, FWD tests were conducted on HMA to backcalculate the modulus of base materials. 3.7 Soil Stiffness Gauge (SSG) A Humboldt H-4140 SSG was used in this study. The soil stiffness gauge (SSG) is a nondestructive testing device, which measures the stiffness (and or modulus) of surficial materials in place. The SSG directly measures in-situ stiffness of materials in a zone lying 125 mm ~ 380 mm below the surface. The SSG stiffness measurements were made in accordance with ASTM D6758. 1013

4

RESULTS

Table 2 summarizes the laboratory test results. It is found that RPM has higher modulus than Class 6sp but also higher plastic strain, indicating higher potential for rutting. The CBR of RPM was significantly lower than Class 6sp. Stabilizing RPM with a high carbon/high calcium fly ash significantly increased CBR, Mr, and lowered plastic strain. The strength of field mixed RPM with fly ash was found to be significantly lower than that of laboratory mixed, in terms of CBR, Mr, and Qu. It is suggested that the test results based on laboratory mixed specimens should be corrected as MEPDG input. Table 3 shows the direct measurements on the base layers. It can be seen that for any of Mr and field test methods, fly ash stabilized RPM had higher modulus than RPM, followed by crushed aggregate, as shown in Figure 1 in which the number after the test method indicates the days after the construction of base courses. The resilient modulus was always higher than moduli from field tests. The Mr of RPM was 257 MPa, while the highest modulus for RPM from field tests, DCP in this case, was 105 MPa. The difference between Mr and back-calculated moduli for stabilized materials is even larger. The Mr of 28-day stabilized RPM was 4334 MPa, while the highest modulus from field tests was 364. The Mr is more than ten times higher than moduli form field the tests. In the field tests, DCP tests resulted in higher modulus than LWD, SSG, and FWD. The moduli from SSG were higher than those from LWD and FWD tests, except for stabilized RPM. Between LWD and FWD tests, LWD generated higher moduli. This might be related to the stress/ Table 2.

Summary of field and laboratory test results. SRM, (MPa)

Material Class 6sp RPM L-SRPM F-SRPM

Curing time, (d)

CBR, (%)

Ext

Int

Plastic strain, (%)

Qu, (kPa)

R, (kPa)

0 0 7 28 7 28

133 19 129 176 62 94

154 201 513 561 – –

220 257 2984 4334 – –

0.71 2.8 0.58 0.56 – –

– – 1160 1380 350 480

– – 150 320 – –

Note. CBR = california bearing ratio, SRM = summary resilient modulus, Qu = unconfined compressive strength, R = flexural strength, Ext = based on external LVDT, and Int = based on internal LVDT measurement of deformation.

Table 3. Comparison between laboratory Mr and field measured moduli. Fly ash + RPM Curing days

RPM

Class 6

Test method

Average moduli (MPa)

7

Mr

2984

28

Mr

4334

257

220

8

DCP

3634

105

67

8

LWD

182

42

15

22

DCP

328

83

63

22

FWD

134

36

22

22

SSG

159

70

59

26

FWD

112

–

–

1014

10000 FA+RPM RPM Class 6 Moduli, MPa

1000

100

10 Mr_28

DCP_8

DCP_22

SSG_22

LWD_8

FWD_22

Test Methods

Figure 1.

Comparison of material modulus as measured by different methods.

Construction Costs

$30,000.00 Re-work Due to Weather

$25,000.00

Original Construction

$20,000.00 $15,000.00 $10,000.00 $5,000.00 $0.00 RPM

Crushed Aggregate

RPM+FA

Base Mateirials

Figure 2.

Comparison of initial construction costs.

strain-dependence of these materials. Each of these test methods applies different load levels to the materials and induces different strain levels. Further research is needed to determine how to use the lab results for pavement design. In addition, it was found that the test configuration affects the results, which should be considered carefully when selecting a test protocol. 5

COMPARISON OF INITIAL CONSTRUCTION COSTS, ENERGY CONSUMPTION, AND GREENHOUSE GAS EMISSION

Upon the completion of construction at MnROAD, the initial construction costs are available for comparison between different technologies. As seen from the Figure 2, crushed aggregate has the highest construction costs. Some of the costs for crushed aggregate and untreated RPM are associated with the second base work, due to the rainfall during the construction. At the end, fly ash treated RPM base course had the lowest construction costs. 1015

The initial energy consumption and greenhouse gas emission are also compared, using the PaLATE program, as shown in Figures 3 and 4. Again, the high carbon fly ash treated RPM has the lowest energy consumption and greenhouse gas emission. However, it should be noted that these comparisons are based on initial construction data. Life cycle costs, energy consumption, and greenhouse gas emission are needed, as the pavement performance affects maintenance and rehabilitation activities. It should also be noted that, due to the wet weather during construction, the RPM and crushed aggregate bases had to be removed and replaced, while the fly ash stabilized RPM base was not affected by the weather.

Initial Energy Consumption [MJ]

200,000

2nd Base Work

180,000

Processes (Equipment) Materials Transportation Materials Production

160,000

Energy [MJ]

140,000 120,000 100,000 80,000 60,000 40,000 20,000 0 RPM

Figure 3.

Crushed Aggregate

RPM+FA

Comparison of initial energy consumption.

16.00

Initial CO2 Emissions [Mg] and Global Warming Potential 2nd Base Work

14.00 Processes (Equipment)

10.00

Materials Transportation

CO2 [Mg]

12.00

Materials Production

8.00 6.00 4.00 2.00 0.00 RPM

Figure 4.

Crushed Aggregate

Comparison of initial greenhouse gas emission.

1016

RPM+FA

6

CONCLUSIONS

This paper presents the results of characterization of recycled pavement material (RPM) with and without fly ash stabilization as a base material in comparison to a traditional base material, Class 6sp crushed aggregate. The feasibility of using high carbon fly ash to stabilize RPM was demonstrated. The RPM and fly ash stabilized RPM have higher Mr than conventional aggregate. However, the CBR of RPM is significantly lower than that of conventional aggregate. The unconfined compressive strength of field-sample fly ash/RPM materials is significantly lower than that of lab-mixed materials, indicating that the design of stabilized base needs to take the construction quality into account. Different field test methods produced different modulus, indicating that these materials, including the stabilized RPM, are nonlinear materials. The behaviors of these materials depend on the stress/ strain levels induced by different test methods. Further research is needed to address the use of lab results for pavement design. In addition, using RPM and fly ash has potential to generate an enhanced stiffness base to support heavy freight loads, save construction costs, energy consumption, and reduce greenhouse gas emission. Life cycle analysis is warranted for future study. REFERENCES DeBeer, M. 1991, “Use of the Dynamic Cone Penetrometer (DCP) in the Design of Road Structures,” Proceedings of the tenth regional conference for Africa on Soil Mechanics & Foundation Engineering and the third International Conference on Tropical & Residual Soils. Maseru. 23–27 September 1991. Ham, M.E, 1966, Foundations of Theoretical Soil Mechanics, McGraw-Hill, p. 81 Li, L., C.H. Benson, T.B. Edil, and B. Hatipoglu. Sustainable Construction Case History: Fly Ash Stabilization of Recycled Asphalt Pavement Material. Geotechnical and Geological Engineering, Vol. 26, No. 2, 2008, pp. 177–188. Wen, H., M. Tharaniyil, B. Ramme, and U. Krebs. Field Performance Evaluation of Class C Fly Ash in Full-Depth Reclamation: Case History Study. In Transportation Research Record: Journal of the Transportation Research Board, No. 1869, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 41–46. Wen, H., J. Warner, and T. Edil. Laboratory Comparison of Crushed Aggregate and Recycled Pavement Material with and without High-Carbon Fly Ash (DVD). Presented at 87th Annual Meeting of the Transportation Research Board, Washington, D.C., 2008.

1017

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Estimating bearing capacity for opportune landing sites R. Affleck, L. Barna, S. Shoop & C. Ryerson ERDC, Cold Regions Research and Engineering Laboratory, Hanover, NH, USA

ABSTRACT: In today’s modern warfare, a military force requires the ability to conduct air transport operations in remote locations without making engineering preparations to the landing sites. Once a geometrically acceptable area is located from satellite imagery, adequate bearing capacity for aircraft operations needs to be assessed. Currently, there is no standard method of evaluating an Opportune Landing Site (OLS). The field techniques used on OLS were adapted from existing Air Force procedures. The capacity is analyzed based on California Bearing Ratio (CBR) criterion and number of passes for C-130 and C-17 using the PavementTransportation Computer Aided Structural Engineering (PCASE). The OLSs were unacceptable for heavy aircraft such as the C-17, but can support a C-130 operation, primarily during the dry season. The results may not be valid at low pass levels. However, the results provide an estimation of the OLS capability for aircraft operations based on soil strength. 1

INTRODUCTION

Air transport operations sometimes are necessary where no runways exist, and where engineers cannot be pre-positioned owing to time constraints. An Opportune Landing Site (OLS) is then required. The concept behind OLS selection is to remotely select a large strip of land suitable for aircraft operations without making engineering preparations to the landing sites. Unlike semi-prepared or contingency runways, OLSs use natural land surfaces in austere environments that are relatively smooth, flat, and obstruction-free areas (i.e. pastures, fields, etc.). The capability of rapidly locating OLSs has been developed using satellite imagery (Manley 2001, Vincent & Jennings 2004, Ryerson & McDowell 2007, Ryerson et al. 2008a, b). The Boeing OLS software uses a method developed by Dr. Robert Vincent, in which each pixel on a Landsat image is assigned indices related to site flatness (gradient), absence of standing water, and freedom from heavy vegetation. An OLS is composed of adjacent pixels with gradient and vegetation numbers below a threshold value, forming a continuous area of specified length and width. The thresholds are based on field observation and verification for the selected pixels (Vincent & Jennings 2004). The recent version of Boeing OLS software requires a vegetation index of 1.8 and flatness (gradient) index of 0.02. The software also requires input for minimum OLS dimensions for length and width, but a longer OLS can also be generated. Some of the OLSs that we assessed in this study were not long enough to land a C-130 and C-17. However, we were primarily interested in geographic areas that represent the terrain and soil characteristics to support landing zones. Current practice requires boots on the ground to evaluate the structural capability and suitability of existing semi-prepared or engineered runways. Similarly, the OLSs identified by the Boeing software need to be assessed on the ground to determine whether the geometric characteristics and strength requirements are suitable to land an aircraft. Currently, there is no standard method for evaluating an OLS. Procedures for evaluating OLSs were based on, and in some cases modified from, Air Force Civil Engineering Support Agency (AFCESA) standards (AFCESA 2002). Other sources drawn on to provide field measurements for evaluating an OLS came from vehicle mobility, pavement engineering, and standard testing methods. Soil strength was assessed using the dynamic cone penetrometer (DCP), which 1019

was the primary component for determining the loading capacity of the OLS. Other soil properties were assessed, including type, density, and moisture content, which are relevant to soil strength. The OLSs described in this paper were found to possess acceptable lateral and longitudinal gradients as required by AFCESA design criteria (AFCESA 2004). This paper discusses the landing sites’ bearing capacity and the variability of the soil strength measurements from the following: a. Data collected at the OLS assessment sites to examine the capability of Boeing OLS software for reliably locating suitable OLSs and determining the ability of the software to locate smooth, flat, and obstruction-free landing sites seasonally (Affleck et al. 2008a, b, c, Barna et al. 2008a, b). b. Data collected at the OLSs for a blind test of the capabilities of current technology in a semi-integrated functional demonstration (Shoop et al. 2008). The criterion used for soil strength is based on California Bearing Ratio (CBR). The focus of this paper is to provide a preliminary assessment of the bearing capacity of the OLSs, using existing tools or models. The bearing capacity is analyzed in terms of number of passes for C-130 and C-17 operations using the Pavement-Transportation Computer Aided Structural Engineering software (PCASE version 2.08). 2

LOCATIONS AND SITE DESCRIPTION

The OLSs described in this paper all are located in the continental United States with varying climatic and soil conditions. The objective of assessing OLSs was to evaluate the quality of the entire area of a runway selected by the Boeing OLS software, and determine whether the area is suitable to land an aircraft. 2.1 El Centro (EC) OLS The OLS selected at EC in southern California was located on US Naval Reservation land in the southwest desert of the Imperial Valley. The Imperial Valley is relatively flat desert terrain bordered by mountains to the north, west, and southwest. The climate of the Imperial Valley area is arid, with hot summers and mild winters. The transition periods between summer and winter seasons are very short. The land is on a Naval Reservation where air maneuver and air target live-fire training occur daily. The ground-truth at EC examined the capability of Boeing OLS software to reliably locate suitable OLSs, and to determine the ability of the software to locate smooth, flat, and obstruction-free landing sites seasonally (Affleck et al. 2008a, b). This OLS was identified by the Boeing software from Landsat imagery taken on 9 May 2005. It has runway dimensions of 60 by 914 m (200 by 3000 ft) and runs in an eastwest direction. The OLS at EC was assessed during summer, fall, and spring to examine the effects of the seasons on soil strength and surface characteristics. The vegetation type and cover changed little between assessment times. 2.2 Vandenberg Air Force Base (VAFB) OLS The OLS at VAFB was located using a Landsat image from 8 October 2006. Runway dimensions are 30 by 190 m (90 by 635 ft); the runway is oriented in a 120- and 300-degree (clockwise from the north) direction. The OLS at VAFB was relatively flat, with thick vegetation cover, mainly tall grasses and short bushes. The data collection at VAFB was conducted only once in the summer of 2007 as a demonstration site (Shoop et al. 2008). 2.3 Fort Bliss (FB) OLS The OLS at FB was selected from Boeing software run on Landsat imagery taken on 18 May 2003. The 60- by 914-m (200- by 3000-ft) site is oriented east-west, on the Otero Mesa in 1020

southern New Mexico. The area is generally flat and is leased by ranchers for cattle grazing. Otero Mesa is a rock-controlled upland dissected by many drainage ways. The Sacramento Mountains are to the north. The climate is arid to semi-arid continental. Precipitation varies greatly from year to year and from month to month. Affleck et al. (2008a, c) described the OLS assessment at FB to examine the capability of Boeing OLS software for reliably locating suitable OLSs and to determine the ability of the software to locate smooth, flat, and obstruction-free landing sites seasonally. 2.4 Holloman Air Force Base (HAFB) OLS HAFB in south central New Mexico (Shoop et al. 2008) hosted another OLS demonstration site. The OLS was based on a Landsat image from 19 June 2006 with runway dimensions of 30 by 215 m (90 by 700 ft) running in a north-south direction. Soil properties, including soil strength measurements, were conducted by AFCESA (Shoop et al. 2008). The site was relatively flat with short bush vegetation. 2.5 Dean Ford Farm (DFF) and North Vernon Airport (NVA) OLS Both OLSs assessed in southeastern Indiana were actively farmed fields. The DFF OLS was oriented in a northeast-southwesterly direction, with runway dimensions of 20 by 600 m (65 by 2000 ft). The surface condition at DFF changed with season as would be expected; after the corn was harvested, the ground was harrowed and the soil was in a loose state. The other OLS assessed in southeastern Indiana was among a cluster of OLSs near the North Vernon Airport (NVA). This area is in an actively farmed field, the primary crop being either corn or soybeans. In general, the field was flat and free of obstructions; however, for OLSs oriented in a north-south direction, there was a drainage ditch, approximately 3-m (10-ft) wide and 1-m (3-ft) deep, cutting across the field in an east-west direction. At southern Indiana OLSs, the capability of Boeing OLS software to reliably locate suitable OLSs and to locate smooth, flat, and obstruction-free landing sites seasonally was evaluated. Their dimensions were limited to 20 by 600 m (65 by 2000 ft) because of natural or manmade boundaries, such as tree lines or roads, typically demarcating property lines. Both OLSs were identified by the Boeing software using a March 2005 Landsat image and were assessed at four different times—spring, summer, fall, and winter—to examine the seasonal effects on soil strength and surface characteristics. Papers by Barna et al. (2008a, b) give detailed descriptions of the assessment on both OLSs. 3

PROCEDURE

3.1 Soil type, moisture, and density The soil bearing capacity or strength is directly related to soil type. Soil type was determined at various depths by collecting samples for laboratory analysis to determine the soil classification. The soil samples were collected at several locations to represent the soil type of the entire OLS. The resulting soil classification is reported per the Unified Soil Classification System (USCS) (ASTM 2006). Soil moisture content was measured at various depths using several methods, such as moisture sensors (ML2 and PR2 probes in percent volume) and gravimetric methods by taking soil samples. At some OLSs, in-situ density profiles were conducted using the nuclear density gage. 3.2 Soil strength Soil strength profiles were taken using a DCP to a maximum depth of 1 m (3 ft) at each location, but in some cases to only shallower depths because of resisting hard subsurface layers (i.e. cemented and caliche layers). A sampling layout was established using a regular grid spacing at EC, FB, DFF, and NVA to allow sampling of the entire OLS area. The number 1021

of DCP profiles varied from one landing site assessment to another primarily because of assessment purposes and runway dimensions. Between 60 and 80 DCP profiles were conducted on FB and EC OLSs. The DCP profiles collected on the DFF and NVA OLSs in southeastern Indiana ranged from 17 to 31. Soil strength was sampled at 20 locations within a 30- × 30-m (100- × 100-ft) square area at the VAFB and HAFB OLSs. The DCP profiles are translated into soil strength in terms of “estimated” CBR values ranging from 1 to 100% (where the 100% value represents the CBR of crushed limestone gravel). The DCP index is based on penetration per number of hammer blows and the hammer weight used. For most soil types, estimated CBR values are calculated using the relationships developed for use in pavement design or evaluation (Webster et al. 1992) CBR % =

292 DCPindex1.12

(1)

and for clay soil (CL material) the relationship to determine the soil strength is CBR % =

1 (0.017019( DCPindex ))2

(2)

where CBR = soil strength; and DCPindex = average penetration caused by one hammer blow. Both equations have data boundaries. Equation 1 caps the value of CBR at 100 and the minimum value is 1. Equation 2 is limited to CBR values between 1 (DCPindex is greater than or equal to 59 mm (2.3 in.) per blow) and 10 (DCPindex equal to 19 mm (0.75 in.) per blow). 3.3 Estimates of allowable gross loads/allowable passes The structural capacity (aircraft load and number of passes) of the OLSs was determined in layers of 0.15-m (6-in.) increments from the surface down to 1 m (3 ft). For airfield design, a CBR value for the specific soil tested should be selected near the lower part of the range generated during testing (US Army Corps of Engineers 2001, UFC 3-260-02). Variation in the measurements on CBR profiles occur normally, and especially for natural soils. For example,

CBR % 1

10

100

0 0 (0) 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020

0.15 (6) 6

Depth, m (in.)

0.30 (12) 12 0.46 (18) 18 0.61 (24) 24 0.76 (30) 30 0.91 (36) 36 1.06 (42) 42

Figure 1. CBR profiles at 20 locations taken within a 30-m × 30-m (100- × 100-ft) square area at the HAFB OLS. The shade of gray shows the ranges from 2 to 65 of CBR distribution.

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large variations occurred at the HAFB OLS from 20 DCP profiles on a 30- by 30-m (100- by 100-ft) square area (Fig. 1). For this reason, the 15th percentile of the minimum CBR value is often calculated for layers within the soil to better indicate strength at the weaker end of the range of measured values (US Army Corps of Engineers 2001). In this analysis, the 15th percentile of the CBR values was determined for each layer in 0.15-m (6-in.) increments. PCASE is one of the methods for evaluating the suitability of OLS for aircraft loading capacity (http://www.pcase.com). The OLS loading capacity was estimated using the PCASE evaluation module for unsurfaced runways. The module contains unsurfaced layer and natural subgrade materials, which are appropriate conditions for natural soils. The software is run for specific aircraft (C130 and C-17), and because the OLSs are intended for a very limited number of passes (for quick in and out), a traffic design of 10 passes for structural capacity was used in the analysis. However, it is important to note that the results may not be valid at such low pass levels particularly for the C-17 aircraft. 4

RESULTS

4.1 Soil type and soil moisture The soil at the EC OLS was found to be a non-plastic silty sand (SM) in most places, with some well-graded sand with silt (SW-SM) at depths of 0.48 and 0.61 m (19 and 24 in.) at a few locations (Table 1). Discontinuous cemented layers at various depths were found while digging the soil pits. These could be broken through with effort using a pick axe, with some pieces of crumbled soil resulting. The soil moisture contents from the three field visits at EC indicate a very dry summer, significant moisture in the soil in the fall, and a dry spring. The soil moisture profiles during the summer field visit ranged between 2 and 15% by volume throughout the OLS. During the fall field visit, the soil moisture with depth was approximately five to six times wetter than in the summer because the field testing coincided with a rainfall event; the moisture content dramatically changed with depth, where some sections on the OLS were wetter than others. These pockets of wetter soil were related to surface runoff of water onto low-lying areas of the OLS topography. The surface moisture content during the spring assessment ranged from 3 to 6% by volume. The dry density ranged from 1440 to 1744 kg/m3 (from 89.9 to 108.8 pcf) at the EC OLS. The measured soil type at VAFB was identified as silty sand (SM) with the moisture content profile ranging from 1 to 3% by weight (Table 1). No soil density measurements were collected. The upper layer on the entire FB OLS at varying depth is mainly non-plastic silty sand (SM). Then, a transition site of gravelly silt (caliche pieces with silt) material is typically found immediately above a caliche layer. The soil moisture contents from the three field visits

Table 1.

Summary of soils information, soil moisture ranges, and average density at all sites. Soil moisture, % Spring

Dry density kg/m3

3–27b

3–6b

1440–1744

6–18b

1–5b

1395–1530

Sites

Soil type

Summer

Fall

EC VAFB

SM, SW-SM SM

2–15b 1–3a

FB

SM

2–8b

Winter

a

HAFB

ML

15–24

DFF

CL, CL-ML

9–30b

16–37b

28–50b

22–40b

1329–1621

CL, CL-ML

b

b

b

b

1410–1586

NVA a b

7–31

23–38

Moisture content is reported in percent by weight. Moisture content is reported in percent by volume.

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29–42

28–41

showed a very dry summer, some moisture in the soil in the fall, and a dry spring. During the summer field assessment, the soil moisture near the surface was less than 4% by volume; depending on the location, the moisture gradually increased with depth, then slightly decreased below 0.3 m. In the fall, the soil moisture profiles ranged from 6 to 18%. During the spring field visit the surface moisture contents ranged from 1 to 5% by volume. The dry density of the FB OLS ranged from 1395 to 1530 kg/m3 (from 87 to 95.5 pcf ). The soil at HAFB was characterized as silt (ML) with the moisture content profile ranging from 15 to 24% during the blind test. Soil density measurements were not collected at this site. At the DFF OLS, seven soil pits were excavated, consisting of a silty clay with sand (CL-ML) in the upper 305 mm overlaying a lean clay (CL) below 305 mm. The soil at NVA is similar to those at DFF OLS (Table 1). The range of values for the plasticity index in the upper 305 mm is from 5 to 19, with a high percentage (greater than 70%) of material finer than 0.074 mm (#200 sieve). The physical properties are summarized in Table 1. Moisture content profiles at both NVA and DFF were found to be higher during fall, winter, and spring assessments. The dry density ranged from 1329 to 1621 kg/m3 (from 83 to 101.2 pcf), and from 1410 to 1586 kg/m3 (from 88 to 99 pcf ) at DFF and NVA, respectively. 4.2 Soil strength The ranges of calculated CBR values from the DCP measurements and 15th percentile value of the minimum CBR at each OLS site are summarized in Table 2. The CBR values varied from one season to another on OLSs primarily because of moisture content. The effects of the seasons on soil strength and surface characteristics were observed at EC, FB, DFF, and NVA. Several CBR profiles at the EC OLS showed low soil strength in the upper portion, with CBR values increasing with depth (Fig. 2). In general, the surface-layer CBR values were low and not reliable because of the lack of confinement in the soil. CBR values varied with depth and throughout the entire OLS, which was attributed to the irregular and discontinuous cemented soil layers. CBR values also differed with the topography of the OLS. The soil strength was lower in the fall due to higher soil moisture from a rain event before the assessment. Measured soil strengths at VAFB and HAFB varied widely. HAFB CBR values ranged from 2 to 65 (Fig. 1), and VAFB CBR values varied from 17 to 82, being stronger with depth. The range of 15th percentile CBR values lies between 4 and 11 at VAFB, and 8 and 11 at HAFB (Table 2). The 15th percentile CBR values at FB at depths above 0.30 m (12 in.) ranged between 5 and 8. However, the soil strength increased significantly in the 0.30- to 0.45-m (12- to 18-in.) depth range on most of the OLS (Fig. 3). A discontinuous caliche layer was found at varying depths on the entire OLS. The caliche layer was the main source of the soil strength increase at this depth. The soil structures at both the DFF and NVA OLSs were found to be very weak, except during the summer assessment, where the 15th percentile CBR values from 0.15 to 0.45 m were significantly higher (Figs. 4 and 5). The 15th percentile CBR values during the spring, fall, and winter were around 1. In this case, the high soil moisture contents affected the soil strength and resulted in low CBR values. This combined with a high water table, particularly at the NVA OLS, results in a weaker soil matrix. Three of the four seasons had high moisture content readings. The dryer soil structure at depths above 0.45 m resulted in higher CBR values in the summer. 4.3 Aircraft loading estimation Based on the calculated CBR values from the DCP measurements, we estimated the aircraft loading for a C-130 at 70 metric ton (155 × 103 lb) and for a C-17 at 195 metric ton 1024

Table 2.

Summary of the estimated CBR distributions in 0.15-m (6-in.) increments for all OLSs. Summer

Fall

Sites

Depth, m (in.)

A

B

EC

0−0.15 (0−6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

1−38 1−45 1−45 4−44 3−46 4−46

3 7 8 7 7 9

VAFB

0−0.15 (0−6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

5−17 4−30 4−82 4−82 4−70 4−67

7 5 4 7 11 11

HAFB

0−0.15 (0−6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

2−33 2−33 7−39 7−36 10−65 10−65

8 8 11 8 10 11

FB

0−0.15 (0−6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

5−37 3−92 1−100 5−100 4−100 4−91

DFF

0−0.15 (0−6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

NVA

0–0.15 (0–6) 0.15−0.30 (6−12) 0.30−0.45 (12−18) 0.45−0.60 (18−24) 0.60−0.75 (24−30) >0.75 (>30)

Winter

A

B

A

1−29 1−53 1−46 2−76 2−92 2−100

8 6 22 33 17 15

3−17 2−84 1−100 6−100 8−100 15−100

7−35 9−38 2−17 1−14 1−11

12 16 5 2 2

1−6 1−14 1−9 1−8 1−9 1−17

2 3 1 1 1 1

1−4 2−6 1−6 1−6 1−8 1−13

2−29 3−39 4−61 1−40 1−23

7 20 11 4 1

1− 7 3−20 2−28 1−18 1− 9 1−9

1 5 2 2 1 1

1−12 1−18 1−13 1−14 1−17 1−7

Spring B

A

B

1 4 8 8 9 9

2−32 2−44 3−44 3−39 1−38 4−44

3 6 9 10 10 9

5 6 12 13 17 16

4−49 1−48 3−100 6−100 8−65 7−36

8 7 21 15 9 12

1 2 1 1 1 1

1−4 1−7 1−5 1−6 1−15 1−12

1 1 1 1 1 1

1 1 1 1 1 1

1−3 1−9 1−14 1−5 1−6 1−8

1 1 1 1 1 1

A = CBR ranges (minimum−maximum values). B = 15th percentile of the minimum CBR values.

(430 × 103 lb.) using the PCASE model. The allowable loading capacity in terms of number of passes for each OLS is summarized in Table 3. The results suggest that the C-130 is capable of landing with several passes on all of the OLSs, especially in the summertime, except at DFF, where only four passes were possible. The OLS at FB can also support several passes in the fall and spring, based on the soil strength. The OLSs at DFF and NVA are possibly capable of only one pass in the fall, winter, and spring because the OLS contained low-strength layers with insufficient CBR value (Table 2). All of the OLSs were found to be inadequate or showed very limited numbers of passes for a C-17 aircraft. These OLSs were unacceptable for aircraft operations under these soil conditions. 1025

35 30

Summer Fall

CBR (%)

25

Spring

20 15 10 5 0 0-0.15

0.15-0.30

0.30-0.45

0.45-0.60

0.60-0.75

0.75-0.90

Depth Ranges (m)

Figure 3. Estimated CBR values at each depth range representing the 15th percentile of the CBR profiles used to determine the loading capacity for FB OLS. 18 16 14

Spring

CBR (%)

12

Summer Fall

10

Winter 8 6 4 2 0 0-0.15

0.15-0.30

0.30-0.45

0.45-0.60

0.60-0.75

0.75-0.90

Depth Ranges (m)

Figure 4. Estimated CBR values at each depth range representing the 15th percentile of the CBR profiles used to determine the loading capacity for DFF OLS. 20 18

Spring

16

Summer Fall

CBR (%)

14

Winter

12 10 8 6 4 2 0 0-0.15

0.15-0.30

0.30-0.45

0.45-0.60

0.60-0.75

0.75-0.90

Depth Ranges (m)

Figure 5. Estimated CBR values at each depth range representing the 15th percentile of the CBR profiles used to determine the loading capacity for NVA OLS.

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Table 3.

Summary of allowable number of passes at OLSs. C-130, AGL = 70 MT (155 × 103 lb.)

C-17, AGL = 195 MT (430 × 103 lb.)

Sites

Summer

Fall

Winter

Spring

Summer

Fall

Winter

Spring

El Centro Vandenberg Fort Bliss Holloman DFF NVA

44 13 19 65 4 48

2 – 19 – 1 1

– – – – 1 1

19 – 48 – 1 1

1 1 1 1 2 1

1 – 1 – 0 0

– – – – 0 0

1 – 1 – 0 0

MT = metric ton.

5

SUMMARY AND CONCLUSIONS

The concept of locating Opportune Landing Sites on a piece of land that is smooth, flat, level, and relatively free of obstruction using Boeing software was found to be acceptable based on the geometric requirements of AFCESA design criteria. However, estimating the loading capacity on an OLS requires thorough analysis of soil strength measurements. PCASE was used to estimate the capability of the OLSs using the evaluation module for unsurfaced runways using unsurfaced layer and natural subgrade materials. The results suggest that the OLSs can support aircraft operations, primarily the C-130, as long as the soil structure provides adequate strength. The OLSs that were assessed were unacceptable for heavy aircraft such as the C-17. PCASE was developed primarily for evaluation of conventional runways, including unsurfaced or semi-prepared landing zones. It is likely that the evaluation module for unsurfaced runways in PCASE may not provide reasonable values in terms of number of passes for C-130 and C-17 operations at low pass levels. However, the bearing capacity analysis using PCASE provided thresholds or limits for OLSs. This certainly needs further examination to use for OLS assessment. One of the primary factors influencing the soil strength to the OLSs was moisture content. At certain OLSs (i.e. DFF and NVA), the moisture combined with the presence of poorly draining soils and a shallow water table will impact the bearing capacity of the OLS. This study indicates that an OLS may have the capacity for aircraft operations during one season but the same area may not be suitable in another season. Even if the OLSs are capable of aircraft operations (in this case, the C-130 during the summer), it is important to point out that soil failure in the form of rutting, depression, and irregular compaction is likely to occur because of aircraft dynamic loading on areas with soft soil layers. On natural soils, these soil failures can substantially affect aircraft landing and take-off, causing significant tire sinkage and soil resistance. REFERENCES AFCESA. 2002. Criteria and guidance for C-17 contingency and training operations on semi-prepared airfields. Engineering Technical Letter 97–09. Tyndall AFB: Air Force Civil Engineer Support Agency. AFCESA. 2004. C-130 and C-17 landing zone (LZ) dimensional, marking, and lighting criteria. Engineering Technical Letter 04–7. Tyndall AFB: Air Force Civil Engineer Support Agency. Affleck, R.T., Barna, L. & Ryerson, C. 2008a. Assessment of Opportune Landing Sites at El Centro NAF and Fort Bliss OLS. In Proceedings Transportation Systems Workshop, April 2008. Phoenix, AZ. Affleck, R.T., Ryerson, C.C., Barna, L. & Claffey, K. 2008b. Opportune Landing Site (OLS) program: suitability measurement and analysis for Fort Bliss OLS. US Army ERDC/CRREL Technical Report TR-08–16. Hanover, NH: Cold Regions Research and Engineering Laboratory. Affleck, R.T., Ryerson, C.C., Barna, L. & Claffey, K. 2008c. Opportune Landing Site (OLS) program: suitability measurement and analysis for El Centro NAF OLS. US Army ERDC/CRREL Technical Report TR-08-18. Hanover, NH: Cold Regions Research and Engineering Laboratory.

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ASTM. 2006. Standard practice for classification of soils for engineering purposes (Unified Soil Classification System). D 2487. West Conshohocken, PA: ASTM International. Barna, L., Affleck, R. & Ryerson, C. 2008a. Assessment of Opportune Landing Sites in Southeastern Indiana. In Proceedings Transportation Systems Workshop, April 2008. Phoenix, AZ. Barna, L.A., Ryerson, C.C., Affleck, R.T., Claffey, K. & Tracy, B. 2008b. Opportune Landing Site (OLS) program: Southeastern Indiana field data collection and assessment. US Army ERDC/CRREL Technical Report TR-08-22. Hanover, NH: Cold Regions Research and Engineering Laboratory. Manley, D. 2001. Identifying unprepared landing sites for advanced theater transport aircraft (and terrain trafficability for military vehicles). Long Beach, CA: Phantom Works, The Boeing Company. PCASE. Pavement Design Evaluation Software. http://www.pcase.com Ryerson, C. & McDowell, J. 2007. Anywhere-anytime: enhancing battlespace vertical mobility. In AIAA 2007-1103, 45th Aerospace Sciences Meeting and Exhibit, 8–11 January. Reno, NV: American Institute of Aeronautics and Astronautics. Ryerson, C., McDowell, J., Almassy, R. & Eizenga, K. 2008a. The Opportune Landing Site Program. In Transportation Systems Workshop, April 2008. Phoenix, AZ. Ryerson, C., Shoop, S. & Koenig, G. 2008b. Opportune Landing Site program: final report. US Army ERDC/CRREL Technical Report TR-08-13 (limited distribution). Hanover, NH: Cold Regions Research and Engineering Laboratory. Shoop, S.A., Ryerson, C., Affleck, R., Buska, J., Frankenstein, S. & Kost, J. 2008. Predicting soil strength for Opportune Landing Sites. In Transportation Systems Workshop, April 2008. Phoenix, AZ. US Army Corps of Engineers. 2001. Pavement design for airfields (Chapter 6). Unified Facilities Criteria (UFC) 3-260-02. Washington, DC: US Army Corps of Engineers. Vincent, R.K. & Jennings, D.L. 2004. A four-state evaluation of the Boeing Landing Suitability Index (BLSI) for automatically mapping candidate aircraft operating sites in natural terrain from LANDSAT TM Data. Journal of Terramechanics 41: 151–162. Webster, S.L., Grau, R.H. & Williams, T.P. 1992. Description and application of dual mass dynamic cone penetrometer. Instruction Report GL-92-3. Vicksburg, MS: USACE Waterways Experiment Station.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Shear strength properties of naturally occurring bituminous sands J. Anochie-Boateng CSIR Built Environment, Pretoria, South Africa

E. Tutumluer University of Illinois at Urbana-Champaign, Urbana, USA

ABSTRACT: Shear strength properties of three oil sand materials were determined in the laboratory by simulating field loading conditions of large capacity mining trucks and shovels. Both monotonic triaxial compression and direct shear tests were performed on the oil sand materials with bitumen contents of 8.5%, 13.3% and 14.5% at 20oC and 30oC test temperatures. Results from the two tests could not be effectively compared since the triaxial tests produced zero friction angles for all the oil sand materials because of the cohesive nature of bitumen contents. However, results from the direct shear tests were comparable to properties of oil sands reported earlier from various other laboratory tests. Based on the direct shear test results, Mohr-Coulomb failure envelopes were determined to establish shear strength properties of the three oil sand samples. The results presented in this paper may be used to estimate friction angles and cohesion intercepts of oil sand materials with similar characteristics in the field. 1

INTRODUCTION

Shear strength of any geomaterial, i.e., fine-grained soil or granular material, is generally mobilized either due to a cementing action or cohesion and/or grain-to-grain interlock, i.e., angle of friction or repose, under applied loading. Commonly referred to as shear strength properties, cohesion and friction angle are determined from laboratory and field tests performed on constituted specimens and undisturbed in-situ samples, respectively. For several decades, the triaxial compression and direct shear tests have been recognized as some of the standard laboratory tests for determining shear strength properties of soils and granular materials. The results from these tests are often used for analyzing the bearing capacity and stability of slopes and foundations of structures and pavements. Oil sands, or tar sands are natural deposits of bituminous sand materials that are mined for crude oil production. The world’s largest oil sand deposits are found in the Alberta Province in Canada. The typical 8% to 15% by weight of bitumen or asphalt content in the oil sand composition makes these naturally occurring sands low load-bearing materials for haul trucks, shovels and other mining equipment. During the past decade, monotonic triaxial compression and direct shear tests have been performed with certain success to determine oil sand shear strength properties using the traditional shear strength test procedures (ASTM D 2166, 2850, 3080, 4767). In this study, both triaxial compression and direct shear tests were used to determine shear strength properties three oil sand materials in the laboratory. The test procedure was based on field loading conditions of the oil sand materials under large capacity mining trucks and shovels. The laboratory test program focused on conducting shear strength tests on the oil sand samples at two test temperatures at 20oC and 30oC representing typical spring and summer conditions in Saskatchewan, Canada. Based on the laboratory test data, this paper presents the cohesion intercepts and friction angles determined for the individual oil sand samples to establish Mohr-Coulomb failure envelopes. 1029

2

LABORATORY TESTING PROGRAM

2.1 Materials tested and properties Three types of oil sand materials, designated herein as SE-09, SE-14 and AU-14, were initially tested for bitumen and water contents using AASHTO T 308 and AASHTO T 265 test procedures, respectively. The bitumen contents were found to be 8.5%, 13.3% and 14.5% for the SE-09, SE-14 and AU-14, respectively; and the water contents were 1.4%, 3.2% and 2.2%, respectively. After separating bitumen from the oil sands through burning in the oven, washed sieve analysis tests were conducted on the sand ingredients to determine particle size distributions of the three oil sands following AASHTO T 27 procedure. Figure 1 shows the sieve analysis test results. All the three oil sands are uniformly graded fine to medium sands with the smallest to largest size particles ranging from 0.6 mm to 2.36 mm. The fines contents, i.e. passing No. 200 sieve or 0.075 mm, range from 7% to 15%. Similar grain size distributions for oil sand materials were reported by Cameron and Lord (1985). 2.2 Specimen preparation The amount of oil sand material required to achieve a predetermined field density was computed to prepare specimens for shear strength testing. For monotonic triaxial compression tests, oil sand specimens were mechanically compacted in a split aluminum compaction mold using a standard Proctor compaction hammer in three lifts to achieve the target density. Approximately 71-mm diameter cylindrical specimens were prepared for testing. Specimen density was controlled by measuring the weight of material and compacted thickness of each lift, referenced to the top of the mold. The surface of each lift was scarified down to a depth of approximately 10 mm to achieve uniform compaction in 3 lifts. The direct shear test specimens were prepared from gyratory compacted specimens. An Industrial Process Controls (IPC), Ltd. Servopac gyratory compactor available at the University of Illinois was used to produce 150 mm in diameter by 150 mm high cylindrical specimens. Using a masonry saw, the gyratory compacted specimens were cut into square prismatic specimens of size 100 mm and approximately 30 mm high. Following compaction and direct shear specimen cutting and trimming, the oil sand test specimens were conditioned for a minimum of six hours in an environmental temperature chamber before testing.

100 90

Percent Passing, %

80 70 60 50 40 30

SE-09

20

SE-14 AU-14

10 0 0.01

0.1

1

Grain Size - Millimeters Figure 1.

Particle size distributions of oil the sand samples.

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10

(a)

Cylindrical triaxial test specimens

Figure 2.

(b) Square prismatic direct shear test specimens

Compacted oil sand sample specimens for shear strength tests.

Figure 3 shows compacted specimens of one of the oil sand samples prepared for conducting monotonic triaxial compression and direct shear tests. 2.3 Test procedure and laboratory testing A new shear strength test procedure proposed for oil sand testing was used to determine the shear strength properties of the three types of oil sand materials. The proposed test procedure, which is based on the field loading characteristics of the haul trucks and mining equipment for oil sands, considers confining or normal stresses as high as 552 kPa. In addition, the test procedure is based on testing at temperatures of 20oC and 30oC, which represent warmer months in spring and summer, respectively, as observed in oil sand fields (Joseph, 2005). Shear strength tests were conducted on the three samples with bitumen contents of 8.5%, 13.3% and 14.5% using both triaxial and direct shear test procedures. The triaxial tests were performed on the cylindrical specimens, 71 mm in diameter and 142 mm high, by applying five confining stress levels, i.e., 20.7, 41.4, 69, 138 and 276 kPa. Specimens were conditioned and tested at temperatures of 20oC and 30oC to obtain the friction angle φ, and cohesion c properties. The test specimens were monotonically loaded at a strain rate of 1% strain/minute using an IPC UTM-5P pneumatic testing system, and pressurized in a triaxial chamber with air pressure. The load was measured through the load cell, whereas, the deformations were measured using the actuator linear variable displacement transducer (LVDT). Direct shear tests were also performed on the oil sand samples to compare test results with the triaxial compression tests. The same test conditions for the triaxial compression tests were repeated during direct shear testing except that the applied confining or normal stresses were increased up to 552 kPa in the Humboldt pneumatic direct shear test setup at the University of Illinois Advanced Transportation Research and Engineering Laboratory (ATREL). The shear stress was measured through the load cell, whereas, the horizontal and vertical deformations were measured using horizontal and vertical LVDTs. 3

ANALYSIS OF TRIAXIAL COMPRESSION TEST DATA

Tables 1 and 2 show the results for all the three oil sand samples tested at 20oC and at 30oC, and Figures 3 and 4 present the shear strength test results in Mohr’s circles to indicate that the oil sand samples were found to give essentially similar shear strength properties regardless of the applied confining pressure. Apparently, the oil sand materials did not densify as confining 1031

Triaxial shear strength test results for oil sand samples at 20oC.

Table 1.

Peak shear stress @ confining stress in kPa

Strength properties

Sample ID

20.7

41.4

69

138

276

φ (degrees)

c (kPa)

SE-09 SE-14 AU-14

32.5 40.6 62.7

26.7 43.9 51.1

35.5 43.9 69.0

33.9 41.6 41.3

27.0 50.9 41.9

0 0 0

15.7 22.3 24.8

Triaxial shear strength test results for oil sand samples at 30oC.

Table 2.

Peak shear stress @ confining stress in kPa

Strength properties

Sample ID

20.7

41.4

69

138

276

φ (degrees)

c (kPa)

SE-09 SE-14 AU-14

24.5 22.2 28.7

33.3 20.7 22.9

34.0 24.5 22.9

31.3 25.9 28.7

21.5 21.4 30.2

0 0 0

15.0 13.0 15.4

120 Shear Stress τ, kPa

(a) SE-09

100 80 60 40 Test #1 Test #2 Test #3

20

Test #4

Test #5

c = 15.7 kPa, φ = 0

0 0

Shear Stress τ, kPa

120

50

100

150 200 250 Normal Stress σ n , kPa

300

350

400

(b) SE-14

100 80 60 40

Test #1 Test #2

Test #3

Test #4

Test #5 c = 22.3 kPa, φ = 0

20 0 0

Shear Stress τ, kPa

120

50

100

150 200 250 Normal Stress σ n , kPa

300

350

400

(c) AU-14

100 80 60 40

Test #2

Test #1

Test #3

Test #4

Test #5 c = 24.8 kPa, φ = 0

20 0 0

Figure 3.

50

100

150 200 250 Normal Stress σ n, kPa

300

Mohr circles for the three oil sand samples tested at 20oC.

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350

400

120 Shear Stress τ, kPa

(a) SE-09

100 80 60 40 Test #1 Test #2 Test #3

20

Test #4

Test #5

c = 15 kPa, φ = 0

0 0

50

100

150

200

250

300

350

400

Normal Stress σ n , kPa

Shear Stress τ, kPa

120

(b) SE-14

100 80 60 40 Test #1 Test #2 Test #3

20

Test #4

Test #5 c = 13.0 kPa, φ = 0

0 0

Shear Stress τ, kPa

120

50

100

150 200 250 Normal Stress σ n , kPa

300

350

400

(c) AU-14

100 80 60 40 Test #1

20

Test #2 Test #3

Test #5

Test #4

c = 15.4 kPa, φ = 0

0 0

Figure 4.

50

100

150 200 250 Normal Stress σ n, kPa

300

350

400

Mohr circles for the three oil sand samples tested at 30oC.

pressure increased, hence the shear strength did not increase. It is worth mentioning that none of the specimens tested failed in shear; rather, all the test specimens bulged when the applied shear stress reached the peak value. This failure mode resulted in zero friction angles for all the oil sand samples, i.e., there is no or negligible interlock between the sand grains of the materials and the oil sands are primarily cohesive in nature. The zero friction angles obviously are not reflective of the dense nature of the tested oil sand materials. Dusseault & Morgenstern (1978b) and Agar et al. (1983) report that oil sand derives its strength from the dense interlocking grain structure it exhibits. Therefore, the test results can be interpreted as there was no significant contact between the grains of the oil sands tested, which resulted in zero friction angle. In a related case, Dusseault & Morgenstern (1978b) abandoned triaxial tests in favor of direct shear testing for Athabasca oil sands. One of the reasons was that sample uniformity and the required number of similar specimens to describe Mohr-Coulomb envelopes could not be obtained from triaxial testing. Similarly, in this study, direct shear tests were also performed, however, the small cohesion values obtained for all the samples appear to reasonably agree with findings by Round (1960), Dusseault & Morgenstern (1978b), and Agar et al. (1987). Generally, no significant difference was found between cohesion of the three oil sand samples at 20oC and at 30oC. Cohesion was found to be relatively higher at 20oC than at 30oC for all the oil sands with the AU-14 sample giving the highest cohesion value of 24.8 kPa at 20oC. Note that in Figure 3c, the Mohr circles lying above the failure 1033

envelope (test #1 and test #3) were not considered for determining the cohesion property of the AU-14 sample. 4

ANALYSIS OF DIRECT SHEAR TEST DATA

The results for the direct shear tests for all three oil sand samples are reported in Tables 3 and 4 which list the maximum deviator stress at failure, the applied normal stresses, and the shear strength properties determined at test temperatures 20oC and 30oC. Note that only 4 direct shear tests were performed for the oil sand samples at 30oC. There were insufficient oil sand samples to conduct the tests at all the six confining stresses. Comparisons among the test results indicate that the oil sand materials exhibit higher friction angles at 20oC than at 30oC. On the other hand, the cohesion parameter was found to be higher at 30oC than at 20oC. Overall, the SE-09 sample has the highest friction angle and the lowest cohesion, whereas AU-14 has the lowest friction angle and highest cohesion. There is apparently no significant difference between friction angle and cohesion values of SE-14 and AU-14 samples. Both AU-14 and SE-14 samples have higher cohesion intercepts compared to SE-09 sample. The high φ values imply ability of the oil sand materials to develop strength under confinement and resist permanent deformation, and high c values relate to high resistance of the oil sand materials to shearing stresses. Although, the differences between the test parameters are not large, the SE-09 sample is expected to have greater potential to resist permanent deformation when compared to SE-14 and AU-14 samples, which behaved somewhat similar. This could be expected since the difference between their bitumen contents is not significant. It appears that bitumen content has an effect on the shear strength properties of oil sand materials. This effect could be explained in more detail if the characteristics of the bitumen were better known. Generally, the high friction angles and low cohesion values exhibited by the three oil sand samples are in agreement with research findings of Round (1960) and Dusseault & Morgenstern (1978b). All these studies reported low or negligible cohesion and high friction angles for oil sand materials in direct shear tests. Typical “c” values for oil sand materials from direct shear tests under different test conditions are less than 20 kPa; whereas typical “φ” values range mostly between 30 and 60o (Round 1960, Dusseault & Morgenstern 1978b). These researchers also noted that oil sand with high quartz content or highly coarse-grained in nature had high shear strength properties. Table 3.

Direct shear test results for oil sand samples at 20oC. Peak shear stress @ normal stress in kPa

Strength properties

Sample ID

20.7

41.4

69.0

138.0

276.0

552.0

φ (degrees)

c (kPa)

SE-09 SE-14 AU-14

27.3 26.2 32.2

45.7 52.1 41.8

59.8 77.6 61.2

126.3 94.1 123.0

218.3 223.1 210.2

473.4 417.9 365.9

39.4 35.7 32.1

6.2 15.2 22.9

Table 4.

Direct shear test results for oil sand samples at 30oC. Peak shear stress @ normal stress in kPa Strength properties

Sample ID

69.0

138.0

276.0

552.0

φ (degrees)

c (kPa)

SE-09 SE-14 AU-14

63.8 56.6 65.0

113.5 120.4 98.8

190.6 209.7 210.1

384.4 355.2 332.4

33.0 30.7 29.0

17.6 29.5 31.4

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Based on the direct shear test results, Mohr-Coulomb failure envelopes were developed for each oil sand sample. The Mohr-Coulomb failure envelope is expressed by Equation 1. Generally, the Mohr-Coulomb failure criterion is the most widely known strength definition used to characterize shear strength behavior of geomaterials within limited stress ranges. The results from such characterization provide parameters, which are employed in analyzing the stability of the tested materials. In this study, linear Mohr-Coulomb envelopes were used to analyze the direct shear test data of the oil sand samples at the different bitumen contents and test temperatures of 20oC and 30oC.

600 SE-09: τ max = 0.82 σn + 6.2

Shear Stress, kPa

500

400

SE-14: τ max = 0.72 σn + 15.2

300

200 AU-14: τ max = 0.63 σn + 22.9 100

0 0

100

200

300

400

500

600

Normal Stress, kPa

Figure 5.

Mohr-Coulomb failure envelopes for oil sand samples tested at 20oC.

600

Shear Stress, kPa

500

SE-09: τmax = 0.65 σn + 17.6

400

SE-14: τmax = 0.59 σn + 29.5

300

200 AU-14: τmax = 0.55 σn + 31.3 100

0 0

100

200

300

400

500

Normal Stress, kPa

Figure 6.

Mohr-Coulomb failure envelopes for oil sand samples tested at 30oC.

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600

τ max = c + σ n tan φ

(1)

where, τmax = shear strength; σn = normal stress at failure; c = cohesion intercept, tan φ = slope of the failure envelope (φ is friction angle). Figures 5 and 6 show the Mohr-Coulomb failure envelopes developed from the cohesion c and angle of internal friction φ values for the three oil sand materials. It can be observed that at normal stresses below 200 kPa, no significant difference can be ascertained with respect to the mobilized shear strength in the three oil sand materials. However, at normal stresses higher than 200 kPa, the SE-09 sample with lower bitumen content (8.5%) mobilized higher shear strength than the SE-14 and AU-14 with bitumen contents of 13.3% and 14.5%, respectively. Similarly, the SE-14 sample had higher shear strength than the AU-14 sample at high normal stress levels. This trend suggests that the ability of oil sand materials to mobilize shear strength in direct shear testing depends to a large extent on the amount of bitumen content present in the material. Therefore, the applied normal stress has a significant influence on the shear strength properties of the oil sand samples. The results may be used to estimate friction angles and cohesion intercepts of oil sand materials with similar characteristics in the field. In addition, the shear strength properties obtained may be used as inputs into finite element analyses to model permanent deformation behavior of oil sands in order to account for mobility and trafficability of large capacity haul trucks and shovels in oil sand mine fields. 5

SUMMARY AND CONCLUSIONS

The typical 8% to 15% by weight of bitumen or asphalt content in the oil sand composition makes these naturally occurring sands low load-bearing materials for haul trucks, shovels and other mining equipment. A newly proposed shear strength test procedure allowed application of somewhat high confining or normal stresses during testing to adequately determine strength properties of three types of oil sand materials. Both monotonic triaxial compression and direct shear tests were performed on the oil sand materials with bitumen contents of 8.5%, 13.3% and 14.5% at test temperatures of 20oC and 30oC. The triaxial compression tests performed on the three oil sand materials gave zero friction angles and all specimens failed by specimen mid-height bulging, which suggests that the samples behaved cohesive in nature and there were apparently no interparticle contacts between the sand grains in the oil sand samples. The results obtained for cohesion intercept was rather reasonable and agreed with results reported in the literature for similar oil sand samples. Direct shear tests results indicated that the oil sand samples had higher friction angles at 20oC than at 30oC, and lower cohesion values were obtained at 20oC. Generally, SE-09 sample had the highest friction angle and lowest cohesion, whereas AU-14 had the lowest friction angle and highest cohesion at the two test temperatures. Thus, the oil sand sample with lowest bitumen content would have greater ability to resist potential rutting in the field. This observation was evident from high friction angles obtained for the oil sand sample with less bitumen content. Based on the direct shear test results, Mohr-Coulomb failure envelopes were established for the three oil sand samples at the two test temperatures. The shear strength data provided will be useful for engineers and equipment manufacturers to estimate load bearing capacities of oil sand materials under operating haul trucks and shovels in the field. ACKNOWLEDGEMENTS The authors would like to acknowledge Drs. Liqun Chi and Kaiming Xia of Caterpillar, Inc. of Peoria, Illinois for their collaborative efforts in funding this research and providing the oil sand samples and valuable insights in this study. 1036

REFERENCES AASHTO T 265. Standard method of test for laboratory determination of moisture content of soils. AASHTO T 27. Standard method of test for sieve analysis of fine and coarse aggregates. AASHTO T 308. Determining the asphalt binder content of hot mix asphalt by the ignition method. Agar, J.G. Morgenstern, N.R. & Scott, J.D. 1983. Geotechnical testing of Alberta oil sands at elevated temperatures and pressures. Proc., 24th U.S. Symposium on rock mechanics. 795–806. Agar, J.G., Morgenstern, N.R. & Scott, J.D. 1987. Shear strength and stress-strain behavior of Athabasca oil sand at elevated temperatures and pressures. Canadian geotechnical journal Vol. 24: 1–10. American Association of Highway and Transportation Officials. (20th ed.). 2000. Standard specifications for transportation materials and methods of sampling and testing. Washington D.C. American Society for Testing and Materials. 2004. Annual Book of ASTM Standards. Vol. 4 (3). ASTM D 2850. Standard test method for unconsolidated-undrained triaxial compression test on cohesive soils. ASTM D 3080. Standard test method for direct shear test of soils under consolidated drained conditions. ASTM D 4767. Standard test method for consolidated undrained triaxial compression test for cohesive soils. ASTM D 2166. Standard test method for unconfined compressive strength of cohesive soil. Dusseault, M.B. & Morgenstern, N.R. 1978b. Shear strength of Athabasca oil sands. Canadian geotechnical journal Vol. 15: 216–238. Joseph, T.G. 2005. Physical, static and inferred dynamic loaded properties of oil sand. Final progress report, phases I, II, & III, submitted to Caterpillar, Inc. Kosar, K.M. Scott J.D. & Morgenstern, N.R. 1987. Testing to determine the geotechnical properties of oil sands. Proc., 38th annual technical meeting of petroleum society of CIM, Innovation and optimization: everyone’s challenge. Lord, E.R.F. & Cameron, R. 1985. Compaction characteristics of Athabasca tar sand. 38th Canadian geotechnical conference, Edmonton, Alberta. 359–368. Scott, J.D. & Kosar, K.M. 1984. Geotechnical properties of Athabasca oil sands. Proc. WRI-DOE tar sand symposium, Vail, Colorado.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Effects of bearing capacity and load transfer efficiency of jointed concrete pavements on reflective cracking in hot-mix asphalt overlays J. Baek & I.L. Al-Qadi University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

ABSTRACT: Reflective cracking is a major distress in hot-mix asphalt (HMA) overlays and is induced in the vicinity of discontinuities beneath the overlay due to environmental and vehicular loading. This study investigated the mixed-mode fracture mechanism of loadassociated reflective cracking in HMA overlay placed on jointed concrete pavement (JCP). Using a three-dimensional finite element model, the joint response to loading was evaluated using virtual falling weight deflectometer (FWD) testing. In addition, a transient moving vehicular load was applied on the HMA overlay surface. The behavior of reflective cracking was investigated with respect to bearing capacity as well as load transfer efficiency (LTE) of the JCP. Reflective cracking potential was investigated using FWD average deflection, δave, and deflection ratio, δu/δl. This study concluded that 1) critical tensile and shear stresses at the joint primarily depend on pavement subgrade bearing capacity and 2) bearing capacity highly affects mode I reflective cracking initiation. 1

INTRODUCTION

Hot-mix asphalt (HMA) overlays have been used to rehabilitate flexible, Portland cement concrete (PCC) and composite pavements. The first step in HMA overlay design is to evaluate the existing pavement condition. According to the Mechanical-Empirical Pavement Design Guide (MEPDG), the number of distressed and repaired slabs of existing PCC pavement is used as input for the HMA overlay design. Depending on the existing pavement condition, pre-overlay treatments such as full-depth repair, slab replacement, crack-and-seat, and rubblization may be conducted prior to placing the overlay. In the design procedure, HMA overlays are also expected to address several distresses in existing pavement, including reflective cracking. Reflective cracking is a major distress, which is caused by vertical and horizontal movements at the joints and cracks in underlying pavements. The vertical movements are mainly associated with traffic loading and depend on overlay thickness, the existing pavement’s structural capacity, and joint transfer efficiency at joints and/or cracks. It is recommended that joints with a poor rating be replaced or improved prior to HMA overlay. According to the Asphalt Institute (1993), existing concrete pavements need specific treatments depending on their load transfer efficiency (LTE): Saw-cut/seal or interlayer systems when LTE is greater than 75%; crack relief layer or fractured slab when LTE is between 60% and 75%; and fractured slab when LTE is less than 60%. The performance of HMA overlays is dependent on existing pavement conditions. Button and Lytton (2007) suggest that LTE of JCP should be equal or greater than 80% to ensure the effectiveness of a geosynthetic interlayer system. The bearing capacity of PCC pavements can influence deflections at joints. Because LTE values are insufficient to describe the deflection characteristics at the joint, it is the opinion of the authors that the effect of bearing capacity on reflective cracking will be used to provide better information on reflective cracking development.

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2

RESEARCH OBJECTIVES AND APPROACHES

This study investigates the effect of bearing capacity and LTE of an existing JCP on reflective cracking potential in a new HMA overlay using a three-dimensional finite element (FE) model. Deflection parameters obtained through modeling of FWD test were used to represent the bearing capacity and LTE of existing JCP. Then, reflective cracking potential due to traffic loading was analyzed with respect to deflection parameters. To accomplish the objectives of this study, two FE analyses were conducted as follows: First, FWD testing was simulated to obtain vertical deflections of a loaded and unloaded slab (δl and δu, respectively) of a JCP having various bearing capacity and joint conditions. Using sensitivity analysis, proper deflection parameters were determined to represent the bearing capacity and LTE. Second, a moving vehicular loading was applied on the overlay across a transverse joint to develop reflective cracking. This allows the effect of bearing capacity and LTE on tensile and shear stresses at critical locations for reflective cracking to be examined. The modeling results were used to develop a preliminary HMA overlay design approach to control reflective cracking that considers bearing capacity and LTE of existing JCP. 3

NUMERICAL MODELING FOR HMA OVERLAYS

3.1 Geometry and boundary conditions The HMA overlaid pavement modeled in this study is composed of four layers: a 57 mm thick HMA overlay, 200 mm thick PCC slabs, a 150 mm thick base, and a subgrade (Baek & Al-Qadi 2008). Figure 1 illustrates the geometry of the pavement model. The JCP has a 6.8 mm width contraction joint. Since the pavement is geometrically symmetric with respect to the center of an underlying concrete slab, only an area corresponding to a quarter of the slab, 3.05 m long and 3.60 m wide, was modeled. X-axis (longitudinal direction) and Y-axis (transverse direction) symmetric conditions are imposed to three faces of the pavement model accordingly. These symmetric conditions may not be applicable when moving

57 mm HMA overlay 200 mm PCC

6.8 mm joint

5.0 m Finite domain 150 mm base 10.0 m

(a)

3.5 m

6.1 m 1.8 m

Infinite domain Z 7.0 m

Symmetric condition

6.1 m by 3.6 m slab

Y

(b)

X

6.1 m (c )

Figure 1. Geometry of HMA overlay on JCP: (a) Cross section; (b) Pavement joint schematic; and (c) Overall pavement model.

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traffic loading is applied; but because the main area of interest in this study is close to a joint, which is usually affected less by boundary conditions, the symmetric conditions were held to execute this model efficiently. It is also important to use appropriately sized elements and domain to obtain accurate responses. A 5.0 m by 3.5 m finite domain is surrounded by infinite elements as a “quiet” boundary condition, which sets zero deformation and minimizes stress wave reflection in dynamic analysis. Hence, the total domain size is 10.0 m deep, 6.1 m long, and 7.0 m wide. In these two domains, various element sizes were used: the smallest elements (1.0 mm in vertical direction) were located in HMA overlay in the vicinity of a joint. Thus, a total of 103,277 8-node linear brick, reduced integration elements and 2,385 8-node cohesive elements are used in the finite domain and 400 8-node infinite elements are used for the subgrade layer in a far-field zone. 3.2 Material characteristics 3.2.1 Bulk material properties Bulk HMA properties are listed in Table 1. The HMA is assumed as a linear viscoelastic material at low temperature. The Prony series based on the generalized Maxwell model were used to model time-and-temperature dependent behavior of HMA. An inter-conversion procedure was used to obtain the Prony series parameters from complex modulus measured in a laboratory test (Baek & Al-Qadi 2008). Aside from the HMA, the other materials are assumed linear elastic. In lieu of the modulus of subgrade reaction, subgrade modulus, Esg, and base modulus, Eba, were used to represent a variety of bearing capacities for the JCP. Three levels of bearing capacity were specified by combining Esb and Eba. For poor foundation, Esg is 40 MPa and Eba is 200 MPa; for good foundation, Esg is 80 MPa and Eba is 400 MPa; and for excellent foundation, Esg is 120 MPa and Eba is 600 MPa. 3.2.2 Fracture material properties In addition to the bulk property, fracture properties of HMA overlay were used to define cohesive elements for reflective cracking. According to earlier work by Baek and Al-Qadi (2008), fracture properties in mode I were determined with field cored HMA by a disk-shaped compact tension test at a crack-mouth opening displacement (CMOD) rate of 1.0 mm/s. Fracture energy and tensile strength areas 274 J/m2 and 3.4 MPa at –10ºC, respectively. Fracture property in mode II was assumed to be the same as mode I due to a lack of equipment to measure. In addition, reduced fracture energy and tensile strength were assumed to consider the effect of damage due to repetitive loading on HMA. A detailed procedure to determine the reduced fracture property will be published elsewhere (Baek et al., 2010). In this study, it was hypothesized that the damaged HMA had experienced a high number of load repetitions, i.e. a certain degree of damage had been accumulated so that the damaged HMA had only a half of its original fracture energy and tensile strength. 3.2.3 Joint properties It was necessary to model the behavior of a joint due to the existence of dowel bars and aggregate interlocking. A series of spring elements were simply added between concrete slabs to Table 1.

Material properties of the composite pavement.

Layer

Elastic modulus (MPa)

Poisson’s ratio

Density (T/m3)

HMA PCC Base Subgrade Joint

N/A* 27,600 200, 400, 600** 40, 80, 120** k = 1.0 ~ 106 kN/m

0.25 0.15 0.35 0.40

2.3 2.4 1.9 1.9

* Instantaneous modulus and linear viscoelastic property used with the Prony series expansion is referred in a previous work (Baek & Al-Qadi 2008). ** Corresponding CBR of 45 to 260 for base and 4 to 20 for subgrade.

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Approach slab

HMA overlay

Leave slab

Traffic direction Joint FWD loading area

Dualassembly tire-imprint

304 mm

600 mm

(a)

(b)

Figure 2. Schematic of two loading cases: (a) FWD loading on one JCP slab; and (b) a moving load on the HMA overlay.

constrain vertical movements of the joint (Kim et al., 2007). The spring elements were assumed to have no horizontal degree of freedom in a transverse and axial direction. A wide range of spring stiffness, ksp, was imposed into the spring elements to represent various joint conditions: ksp of 1.0 × 106 kN/m for in-tact or retrofitted dowel bars with excellent aggregate interlocking and ksp of 1.0 kN/m for fully loosened dowel bars with very poor aggregate interlocking. 3.3 Implicit dynamic analysis for two loading models Two distinct loading schemes, FWD test loading and traffic loading, were used in this study. In order to obtain time-dependent responses of the pavement system due to the dynamic loading, implicit dynamic analysis was conducted for both loading cases. 3.3.1 FWD loading FWD loading was simulated with a 40 kN impulsive loading which has a sinusoidal shape with a period of 0.030 s. The loading area of the FWD loading is discretized equivalent to a circle area with a 304 mm diameter. A uniform contact pressure of 0.55 MPa is applied on the edge of an approach slab (Fig. 2a). Loaded deflection, δl, is acquired at the center of the loading area while unloaded deflection, δu, is obtained at the leave slab, 152 mm apart across the joint. 3.3.2 Traffic loading A 42 kN of dual-tire assembly loading, which moves 600 mm across the joint, was progressively applied on an HMA overlay surface (Fig. 2b). Each tire imprint consists of five ribs and four groves and has a constant contact area of 33,880 mm2 (Yoo et al., 2006). Vertical non-uniform contact stresses that average 0.7 MPa and have a maximum of 1.2 MPa are employed on the tire contact area. A set of the tire imprint area was shifted 20 mm in a longitudinal direction for one step; at a speed of 8.0 km/h, 30 steps were applied. The loading amplitudes vary linearly in each step (0.009 s); but have a sinusoidal shape globally and total loading period corresponding to 30 steps becomes 0.027 s. 4

EVALUATION OF EXISTING PAVEMENTS USING FWD DEFLECTION PARAMETERS

4.1 Selection of deflection parameters for bearing capacity and joint deflection conditions A sensitivity analysis was conducted to select the proper deflection parameters to indicate the bearing capacity and joint deflection conditions. A total of five deflection parameters were examined: two single deflections, δl and δu, and three combined ones of average deflection, 1042

Table 2. Summary of sensitivity analysis of deflection parameters on subgrade modulus, Esg, and spring stiffness, ksp. Subgrade modulus, Esg

Spring stiffness, ksp

CC*

R2

P-value

CC*

R2

P-value

δl δu δave

–0.939 –0.841 –0.966

0.881 0.707 0.932

6.17E-06 6.10E-04 3.58E-07

–0.187 0.313 0.040

0.035 0.098 0.002

0.560 0.322 0.902

δl–δu

–0.366

0.132

0.245

–0.624

0.389

0.030

δu/δl

–0.075

0.006

0.818

0.745

0.554

0.005

Deflection parameters

* Correlation coefficient.

0.20

Average deflection, δave (mm)

Esg = 40 MPa

Esg = 80 MPa

Esg = 120 MPa

0.15

High LTE & large δave (HL-LD)

Low LTE & large δave (LL-LD)

0.10

0.05

ksp increases High LTE & small δave (HL-SD)

Low LTE & small δave (LL-SD)

0.00 0

20

40

60

80

100

Load transfer efficiency, LTE (%) Figure 3.

Load transfer efficiency versus loaded deflection at three subgrade elastic modulus levels.

δave, deflection difference, δl–δu, and deflection ratio, δu/δl. Since subgrade modulus, Esg, is strongly related to bearing capacity, and spring stiffness, ksp, can indirectly represent joint deflection conditions, the sensitivity analysis was conducted with respect to Esg and ksp. Table 2 shows the sensitivity analysis results for those deflection parameters. Based on three statistic quantities of correlation coefficient (CC), R2, and P-value, the first three deflection parameters were found to best represent Esg, while the other two deflection parameters were good enough to be replaced by ksp. Especially, δave and δu/δl (or LTE) are the best parameters to reflect the contribution of Esg and ksp, respectively. For δave, CC = –0.966, R2 = 0.932, and P-value = 3.58E-07, which is much less than a significant level of 0.05. For δu/δl, CC = 0.745, R2 = 0.554, and P-value = 0.005. Hence, the deflection parameters δave and LTE are used as a bearing capacity and joint deflection condition indicators, respectively. 4.2 Bearing capacity and joint deflection condition classification The joint deflection condition of JCP is classified into four categories using the bearing capacity and LTE. They are grouped with respect to their subgrade modulus levels (Figure 3): Case 1 (LL-LD): a JCP has LTE = 50% and δave = 130 μm; Case 2 (LL-SD): a JCP has LTE = 50% and = δave = 60 μm; 1043

Case 3 (HL-LD): a JCP has high LTE = 90% and = δave = 130 μm; and Case 4 (HL-SD): a JCP has high LTE = 90% and = δave = 60 μm. In each group, as the ksp increases, LTE is enhanced; but δave is found to be insensitive to ksp. It is expected that more reflective cracking occurs in Case 1; less reflective cracking could be developed in Case 4. For Case 3, bending mode failure can be induced; while shear-dominant reflective cracking could be developed in Case 2. Hence, it is unclear which condition is more critical to reflective cracking. Therefore, the effects of the aforementioned joint conditions on reflective cracking development are investigated herein. 5

REFLECTIVE CRACKING ANALYSIS

5.1 Effect of bearing capacity and LTE on tensile and shear stresses at a critical location The effect of bearing capacity and joint stiffness on reflective cracking potential was investigated during one passage of traffic loading for the four JCP cases. Two reflective cracking potentials are tensile and shear stresses at a critical reflective cracking location within the HMA overlay. A stress in a bulk element is equivalent to a traction force per unit cross area of a cohesive element (cohesive strength), which is unable to exceed a material’s tensile or shear strengths. The behavior of reflective cracking was examined for undamaged and damaged HMA. 5.1.1 For undamaged HMA Three stress components in a cohesive element are shown in time domain for the three cases in Figure 4. Those stresses were obtained in the middle of the leveling binder under the center of the two tires where critical stress occurs. The tensile stress, σ33, governs mode I (opening) failure in a longitudinal (or traffic) direction while vertical shear stress, σ23, governs mode II (shear) failure in a vertical (or perpendicular to pavement surface) direction. No mode III (tearing) failure in a transverse direction was expected since horizontal shear stress, σ23, is

4.0

σ23

Stress (MPa)

3.0

σ33

σ13 S13 S13 σ13 S13 σ13

HL-SD HL-LD LL-LD

σ33 S33 S33 σ33 S33 σ33

S23 σ23 S23 σ23 S23 σ23

2.0

σ33

as bearing capacity

1.0

σ23

as LTE

0.0

σ13 ≈ 0.0 –1.0 0.00

0.05

0.10

0.15 0.20 Time (sec)

0.25

0.30

Figure 4. Comparison of tensile and shear stress variations in time domain for undamaged HMA of (a) HL-LD and HL-SD cases and (b) HL-LD and LL-LD cases.

1044

relatively very small. Generally, tensile stress monotonically increases, reaches its peak when the moving load is located right over the joint, and decreases gradually after that. On the other hand, the shear stress variation curve has a positive peak when moving loads are applied on an approach slab edge and a negative peak on a leave slab edge. Compared to the vertical stress, higher tensile stress occurs in most of the loading sequences regardless of underlying JCP conditions. Hence, the main driving force of reflective cracking due to the applied moving traffic loading is tensile stress in the HMA. Comparing two JCP cases (HL-LD and HL-SD) having different bearing capacities but the same level of high LTE, a 0.85 MPa higher critical tensile occurs in the JCP with weaker foundation: 1.35 MPa in HL-SD and 2.21 MPa in HM-LD. As the bearing capacity becomes weaker, higher deflections occur in the underlying JCP and consequently greater tensile stress due to bending occurs at the bottom of the HMA overlay, particularly at the vicinity of the joint. However, vertical shear stresses in both cases are relatively less than tensile stresses due to high LTE; no significant difference could be found between the two cases. Therefore, even though a JCP has good LTE, if bearing capacity of the JCP is not enough to support HMA overlay, critical tensile stress becomes relatively higher at the bottom of leveling binder and the JCP has higher reflective cracking potential. On the other hand, the critical vertical shear stress is magnified by a factor of 6.4 in the JCP case of LL-LD with lower LTE and poor bearing capacity over that of HL-LD with higher LTE and poor bearing capacity. Nonetheless, tensile stress is still much higher than the vertical shear stress; the critical vertical stress is only 37% of the critical tensile stress. Therefore, it is clear that tensile stress is the main driving force for reflective cracking for a JCP with poor bearing capacity while the effect of vertical shear stress importance increases as LTE becomes worse. 5.1.2 For damaged HMA Under the assumption that HMA is damaged due to repetitive loading applications, the effects of bearing capacity and joint stiffness on the critical tensile and shear stress were investigated. A tensile stress peak in damaged HMA for HL-LD appears earlier and 21% less than that in the undamaged HMA (Figure 5a). This shift happens because a traction force in a cohesive element starts to decrease once the tensile stress reaches its tensile strength, and consequently, more damages are accumulated. This means a certain degree of micro-cracks arise at the critical location by tensile stress. Moreover, when bearing capacity of a JCP is enhanced, critical tensile stress is reduced and does not reach its tensile strength as shown in Figure 5b. Thus, no further damage is induced by the traffic loading. However, since vertical shear stress does not reach its strength level, the effect of vertical stress is not significantly more important than that of tensile stress. This phenomenon can be explained by the fact that a joint deflection condition is improved after the JCP received HMA overlay. In other words, relative displacement at a joint is lessened due to stress distribution in the HMA overlay so that the effect of LTE of underlying JCP becomes less significant. As a result, a JCP with weaker foundation has a high potential for reflective cracking regardless of its LTE. Therefore, it can be concluded that the bearing capacity of a JCP has a greater effect on reflective cracking due to traffic loading. The relationship between bearing capacity and reflective cracking potential was evaluated by means of average deflection, δave, and a scalar of degradation, D. The degradation represents a degree of damage of a cohesive element, ranging from 0.0 for no damage and 1.0 for fully damaged (macro-crack) as follows (Abaqus 2007): D=

(

δ mc δ mmax − δ m0 δ mmax

(

δ mc

) )

− δ m0

(1)

where, δc is a critical separation; δ0 is a separation corresponding to maximum traction; δmax is a current maximum separation which experienced by a cohesive element; and subscript m denotes a mixed mode. Regarding the three levels of LTE, the degradation variation at a 1045

3.0

σ23, HL-LD σ23, LL-LD

σ33, HL-LD σ33, LL-LD

σ (undamaged HMA)

Stress (MPa)

2.0

σ (damaged HMA) 1.0

σ23

as LTE

0.0

–1.0 0.00

τ (undamaged HMA) 0.05

0.10

0.15

0.20

0.25

0.30

Time (sec) (a) 3.0

Tensile stress, HL-LD Tensile stress, HL-SD

Shear stress, HL-LD Shear stress, HL-SD

Stress (MPa)

2.0

σ33

as bearing capacity

1.0

0.0

–1.0 0.00

0.05

0.10

0.15

0.20

0.25

0.30

Time (sec) (b) Figure 5. Comparison of tensile and shear stress variations in time domain for damaged HMA of (a) HL-LD and HL-SD cases; and (b) HL-LD and LL-LD cases.

potential reflective cracking critical location is shown with respect to δave in Figure 6. A clearly linear trend between D and δave is found; degradation starts to increase at δave of 70 μm and keeps increasing up to 0.89 at δave of 140 μm. Though those deflections are only valid for the given overlay structure and materials, generally speaking, the reflective cracking potential can be evaluated by means of not only LTE, but also bearing capacity or average deflection obtained from FWD testing. Further research is needed to build a deflection criterion for reflective cracking through bearing capacity evaluation. For the entire in-plane cross-section 1046

Figure 6.

Degradation variation with respect to average deflection for various LTE conditions.

of the HMA overlay, fractured area differences at different supporting conditions are compared elsewhere (Baek and Al-Qadi 2009) and further evaluation is needed. The relationship between bearing capacity and reflective cracking potential was evaluated by means of average deflection, δave, and a scalar of degradation, D. The degradation represents a degree of damage of a cohesive element, ranging from 0.0 for no damage and 1.0 for fully damaged (macro-crack). Regarding the three levels of LTE, the degradation variation is shown with respect to δave in Figure 6. A clearly linear trend between D and δave is found; degradation starts to increase at δave of 70 μm and keeps increasing up to 0.89 at δave of 140 μm. Though those deflections are only valid for the given overlay structure and materials, generally speaking, the reflective cracking potential can be evaluated by means of not only LTE, but also bearing capacity or average deflection obtained from FWD testing. Further research is needed to build a deflection criterion for reflective cracking through bearing capacity evaluation. 5.2 HMA overlay design concept to consider bearing capacity and load transfer efficiency Under traffic loading, reflective cracking is initiated in a mixed mode. The main driving force in the mode I and mode II is tensile stress and shear stress, respectively, induced in a vicinity of joint. The fracture property of HMA overlay is also related to the failure criterion of reflective cracking. Figure 7 illustrates the mixed mode fracture criteria and typical stress statuses of reflective cracking. A quadratic-form failure criterion was used in this study, which has three components of normalized tensile stress and normalized shear stresses in vertical and horizontal directions. Since the horizontal shear stress is relatively very small, only vertical shear stress is considered in the failure criterion. Under the failure criterion envelope, i.e. sum of square of each stress component is less than 1.0, no failure occurs. As shown in Figure 7, four stress statuses of A, B, C, and D are specified to compare their failure modes: low tensile stress and low shear stress at A; high tensile stress and low shear stress at B; low tensile stress and high shear stress at C; and high tensile stress and high shear stress at D. For the same overlay structure, lower LTE induces higher shear stress while high δave induces greater tensile stress as mentioned earlier. For the given tensile strength, σ10 and shear strength, τ10 for an HMA overlay, reflective cracking occurs only at D. There are two approaches to control the failure at D: decreasing δave and/or increasing LTE, i.e. enhancing bearing capacity and/or restoring dowel bars of the JCP. For damaged HMA overlay with lower strength (σ20 < σ10, τ20 < τ10), reflective cracking occurs at B and D under the same loading application due to a lack of HMA tensile strength. For this case, foundation improvements 1047

τ / τo Undamaged HMA (σ1o, τ1o)

1.0

Microcrack (damage) initiation criterion Damaged HMA (σ2o < σ1o, τ2o < τ1o) C

δave

A

D

2

LTE

B 1.0

Figure 7.

2

⎛ σ ⎞ ⎛ τ ⎞ ⎜ o⎟ +⎜ o⎟ =1 ⎝σ ⎠ ⎝τ ⎠

σ / σo

Schematic of the effect of LTE and δave on mixed-mode fracture.

of the JCP, such as under seal grouting, can be an efficient method of controlling reflective cracking rather than dowel bar restoration because it can reduce more tensile stress. 6

SUMMARY

The effect of bearing capacity and joint deflection conditions on reflective cracking initiation was investigated using a three-dimensional finite element method for a hot-mix asphalt (HMA) overlay on a jointed concrete pavement (JCP). Two deflection parameters were used and obtained from falling weight deflectometer testing on existing JCP: Average deflection, δave, in a loaded and unloaded slab and load transfer efficiency (LTE). These parameters indicate the bearing capacity and joint deflection conditions of the JCP, respectively. One passage of moving traffic loading was applied to develop reflective cracking in a potential critical area where cohesive elements were inserted. Based upon the numerical analysis, higher tensile stress occurs at a JCP with weaker bearing capacity while higher vertical shear stress is induced at a JCP with poor LTE. With regards to reflective crack initiation, the effect of bearing capacity is more important than LTE. Since the effectiveness of reflective cracking control depends on HMA characteristics, the authors recommend that pavement designers consider bearing capacity as well as LTE in developing the structural and material HMA overlay design. ACKNOWLEDGEMENT This research was supported in part by the National Science Foundation through TeraGrid resources provided by an Abe machine in NCSA under an awarded project of TGDMS070014T. TeraGrid systems are hosted by Indiana University, LONI, NCAR, NCSA, NICS, ORNL, PSC, Purdue University, SDSC, TACC and UC/ANL. REFERENCES Abaqus. 2007. Abaqus/Standard User’s Manual Version 6.7, Abaqus, Inc., Palo Alto, California. Applied Research Associates (ARA). 2004. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures, NCHRP 1-37A, Final report, Transportation Research Board, Washington, D.C.

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Asphalt Institute (AI). 1993. Asphalt overlays for Highway and Street Rehabilitation, Manual Series No. 17 (MS-17), College Park, MD. Button, J.W. & Lytton, R.L. 2007. Guidelines for Using Geosynthetics with Hot Mix Asphalt Overlays to Reduce Reflective Cracking. Presented at the 86th Annual Meeting of the Transportation Research Board, CD-ROM, Transportation Research Board, Washington, D.C. Baek, J. & Al-Qadi, I.L. 2008. Finite Element Modeling of Reflective Cracking under Moving Vehicular Loading: Investigation of the Mechanism of Reflective Cracking in Hot-Mix Asphalt Overlays Reinforced with Interlayer Systems, Presented at the 2008 ASCE T & DI Highway and Airfield Pavements Conference, Bellevue, Washington. Baek, J. & Al-Qadi, I.L. 2009. Application of a Steel Netting Interlayer System Application on a HotMix Asphalt Overlay with a Poorly Supported Jointed Concrete Pavement, MairePav6 Conference, Torino, Italy. Baek, J. & Al-Qadi, I.L. 2010, Determination of Fracture Energy of Hot-Mix Asphalt under Fatigue Loading. Journal of Engineering Mechanics, (To be submitted). Kim, H., Chou, K.F. & Buttlar, W.G. 2007. Finite Element Fracture Analysis of Airport Overlay System Using J-Contour Integral Approach, Presented at the 86th Annual Meeting of the Transportation Research Board, CD-ROM, Transportation Research Board, Washington, D.C. Yoo, P.J., Al-Qadi, I.L., Elseifi, M. & Janajreh, I. 2006. Flexible Pavement Responses to Different Loading Amplitudes Considering Layer Interface Conditions and Lateral Shear Forces, International Journal of Pavement Engineering, 7(1), 73–86.

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Bearing capacity designs for climatic conditions

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Use of Ground Penetrating Radar for detection of salt concentration on Norwegian winter roads A. Lalagüe & I. Hoff SINTEF, Road and railway Engineering, Trondheim, Norway

E. Eide 3d-radar AS, Trondheim, Norway

A. Svanekil Norwegian Public Roads Administration, Trondheim, Norway

ABSTRACT: The use of salt for ice and snow prevention and removal is practised in many countries in order to maintain a high level of mobility and safety during the wintertime. Today winter serviceability comes within a new scope where environmental considerations are very important. Due to lack of calibration of spreading methods, quantity of salt applied is usually not accurately determined. The Ground Penetrating Radar can be a useful tool in salting operations. It records the electric echoes induced by the dielectric properties differences between two materials. GPR can detect salted/non salted surfaces, especially when spread with brine. The amplitude of a single reflected signal is dependent on the brine concentration. This pilot study verifies this effect. However, the equipment and software used for the pilot need modifications to become a practical tool. 1

INTRODUCTION

1.1 The context Because of snow and ice deposit, the adherence between tires and pavement is considerably reduced, which leads to an increase of traffic accidents. Snow can also disrupt the local economic activity when it impedes the road-users mobility. Optimization of salt use and better control of spreading are possible improvements. Targeted concentrations are often more effective, more economic and more eco-friendly than spreading on the entire section. This project work is related to the “bare pavement strategy” during winter, conducted by the Norwegian Public Roads Administration (NPRA), which consists to develop new tools and methods to keep the road snow- and ice-free. 1.2 Background on road salt use De-icing is the process of removing ice from the pavement, while anti-icing consists in preventing ice deposit. De-icing can be done with chemicals. Snow removal is done by winter service vehicles and will not be discussed in this paper. Abrasives like sand increase friction. Sand does not have any chemical potential, and therefore does not affect the environment in the same way. On the other hand it is less efficient in many cases than salt. Chemicals are sodium chloride (NaCl), magnesium chloride (MgCl2) or calcium chloride (CaCl2). NaCl is by far the most used. MgCl2 and CaCl2 are sometimes combined with NaCl, they reduce the reaction time and can be spread at very low temperatures (Vaa T., 2004), but they are expensive, less easy and less safe to handle. MgCl2 and CaCl2 are not discussed in this paper. 1053

1.3 Research objectives Due to lack of calibration of spreading methods, quantity of salt applied is not normally accurately determined. Thus 140 000 tons of road salt are used each year in Norway; this amount is probably unnecessary high. The purpose of this project was to determine if the Ground Penetrating Radar (GPR) technique could be a relevant way to control the salt amount on roads. Laboratory tests were conducted at NTNU/SINTEF Road technology laboratory, in Trondheim. Tests have been carried with dry salt, brine and pre-wetted salt, all used by winter maintenance services.

2

THE MELTING ACTION OF SALT (VAA & SAKSHAUG, 2007)

2.1 The eutectic point Salt is a “freezing point depressant”: it lowers the freezing point of water (Environnement Canada, 2004). The freezing point varies in relation to the NaCl concentration. The lowest freezing point is called the “eutectic point”. For a brine solution, it is reached at −21°C, for a salt percentage of 23.3%. In theory NaCl can be used for very low temperatures – down to −21°C. In practice, it is not recommended below −11°C. Even if NaCl is still able to melt ice at lower temperatures, it becomes less efficient. 2.2 The role of salt in ice removal The melting action of salt is due to its hygroscopic property. It can absorb water from the pavement (rain, ice, snow) or humidity from the air if this is higher than 76%. Salt in contact with water will form brine that seeps in the ice/snow layer until it reaches the surface of the road. The bonds between pavement and ice are broken as brine flows along the crossfall. Remaining ice/snow is reduced to slush with traffic (Transportation Association of Canada, 1999). 2.3 Dry salt applications Dry salt can be used on a bare pavement only in special occasions, in contemplation of a snowstorm for instance. It needs to be carefully spread, avoiding wheel path, because traffic sweeps it away from the road. Spread on ice/frost, dry salt is almost always efficient, but with a reaction time which can be high (>30 min). This delay corresponds to the necessary time for solid particles to absorb water and turn into brine. Below −7°/−8°, the water content in air is too low to initiate the melting process. 2.4 Salt brine applications Liquid binds better than dry salt to the pavement, spreading can therefore be done at higher speeds. In addition to that, there is no delayed reaction time because there is no dry salt dissolution required. The treatment can be considered instantaneous, which is a real advantage. However, when ice starts melting, the brine is diluted. The salt concentration is getting lower as melting goes along and the solution becomes less efficient. It can even refreeze at low temperatures. The brine effectiveness is time limited. 2.5 Pre-wetted salt applications The pre-wetting technique uses salt brine to wet dry salt. Thus it reduces the time needed for particles to dissolve and become active, and there is less dilution problem. Dry salt turns into brine as ice melting goes along, and salt concentration remains the same until all of the dry salt is dissolved.

1054

Table 1.

Guiding salt quantity in grams/m2 (NPRA, 2003). Brine solution

Pre-wetted salt (dry + brine)

Dry salt

Pavement

[0°; −5°]

[0°; −5°]

[−5°; −10°]

[0°; −5°]

Dry Humid Wet White frost Thin ice Thick ice Before rainfall Supercooled rain Snow

10 15

4+2 8+3 14 + 6 8+3 14 + 6 18 + 8 14 + 6 21 + 9 20 + 0

4+3 9+4 18 + 4 11 + 5 18 + 8 21 + 9 18 + 8 28 + 14 25 + 0

15 30

[−5°; −10°]

15 20 inefficient 20 40 inefficient inefficient inefficient inefficient

10

20

[−5°; −0°]

inefficient inefficient 15 inefficient inefficient inefficient inefficient inefficient 25

2.6 Amount of salt to be applied according to pavement conditions The following guideline recommendations (see Table 1) are issued by the Norwegian Public Roads Administration and used by the Norwegian winter maintenance services. The de-icing actions depend on the climatic conditions and state of the pavement. As indicated, dry salt can be applied only in case of high moisture content on the pavement surface so that it can turn into brine. Conversely, brine should not be applied when rainfalls occur to prevent a salt concentration lowering.

3

ENVIRONMENTAL IMPACTS OF ROAD SALT USE

3.1 Corrosion and infrastructure damage 3.1.1 Roads and bridges Salt can affect most structures by damaging concrete. Chlorides penetrate through concrete voids and corrode steel reinforcements. They dilate, which create cracks in the concrete. Today, new technologies and changes in construction practices have improved the corrosionresistance of concrete, but old structures remains predisposed (Salt Institute, 2004). 3.1.2 Vehicles Few years ago, vehicles corrosion was the costly consequence of road salt use. Today, even if some parts are still exposed to corrosion, automobile manufacturers have improved vehicle life span by using non-corrosive materials such as plastic and zinccoated steel. As a consequence of ongoing improvements, vehicles corrosion has never been so low. But obviously, older vehicles still remain susceptible to salt damage (Salt Institute, 2004). 3.2 Roadside vegetation Roadsides are often dry, man-made, harsh environments, and use of salt makes this situation worse. High chloride concentrations stop the absorption of soil humidity by the plants and make the leaves becoming brown. High sodium concentrations may affect plants growth, by modifying structure, permeability and aeration of the soil. The extent of the damages depends on several factors: amount of salt, type of soil, precipitation, distance from the road, wind direction and plant species. In a word, impacts are local and change from one site to another. Sensible salting can reduce the quantity of salt transported to side terrain (Transportation Association of Canada, 2003).

1055

3.3 Groundwater impacts The damages caused to vegetation are connected to impacts on groundwater. It depends on several factors such as the frequency of salt applications, size of the waterbody and distance from the road. During the snow melt, road runoffs are collected through waterpipes and mixed with sewage. At that time, the salt content can rise to more than 100 mg/l. If the runoffs are not previously diluted and directly discharged into the lake or river, the salt concentration can reach 5000 mg/l at the opening. However salted water is quickly diluted. Even if it can have a very high concentration of pollutants coming from the roadside in winter, the volume is generally very low. For these reasons roads are normally not considered an ecological hazard (Transportation Association of Canada, 2003). 3.4 Fish tolerance towards salt High salt concentration in spring time may affect the aquatic life. To a certain extent, most fish types have a good tolerance to salt content, even if they are sensitive to long lasting impacts. Tolerated limit values range from 1000 mg Cl−/l (plankton, larva) to 6000 mg Cl−/l (trout). Obviously, the impact of salt on fishes depends on site characteristics and the turnover rate of water. If the flow rate is high, salt will be faster diluted (Salt Institute, 2004). 4

THE GROUND PENETRATING RADAR (GPR)

4.1 Principle The GPR is a nondestructive method used to image the subsurface. It can detect all kinds of objects, cables, pipes, drains, waterways, groundwork, iron framework, anchorage etc. In geology and geotechnics, it determines the layout and the thickness of the different layers. If appropriately used, it is time-saving and improves the safety during construction works. The georadar transmits electromagnetic waves in the studied structure and records the electric echoes induced by the dielectric properties differences between two materials. It takes into account the round-trip time and the amplitude of the signal. An image is created when moving on the surface. Depth range and resolution depend on the several factors (Neal, 2004). If the electrical conductivity of the ground increases, the energy is likely to dissipate, then the penetration depth decreases. Likewise, high

Emitted signal

Reflected signal

θ1

θ2 θ 1 = θ2

ε1 ε1

θ3 Refracted signal Figure 1.

GPR principle.

1056

frequencies penetrate less into the soil than lower frequencies but give a better resolution. Sands, gravels, ballasts and rocks are easily penetrated. Concretes, due to their homogeneity, give goods images of their intern structure as well. On the contrary, clays and saline soils can constitute obstacles (Saarenketo, 2006). 4.2 Functions The Ground Penetrating Radar has many applications in numerous areas. Contrary to others systems which are limited to metal detection, it can locate all kinds of materials including synthetics such as PVC or polyethylene. It is therefore perfectly suitable for detection of piping and wiring systems in urban environment. It is also possible to determine the thickness of a material with the propagation speed. Surveys showed an error less than 10% when estimating ballasts thickness. As for roads, the GPR can be used in phase of excavation to estimate the quality of the subgrade and thus limit core drilling. In tunneling it enables the detection on voids and weakness zones. Stratigraphy, visualization of groundwater table or river bottoms, examination of polluted sites, seeking of voids, faults or cavities are others possible uses.

5

LABORATORY EXPERIMENT

5.1 Equipment and materials − Ground Penetrating Radar • • • • •

GeoScopeTM GPR from 3d-radar AS Frequency from 100 MHz to 2 GHz Dwell time 2 μs Frequency step size 2 MHz 31 elements (6 active for the tests)

− Materials • • • •

Sea salt, min. 99.9% NaCl, water content max. 3%, grain size max. 8 mm Brine, nearly saturated with 23.3% salt by weight Asphalt Concrete maximum grain size 11 mm, samples 30 cm × 30 cm × 5 cm Foam microwave absorber, AN-79 by ECCOSORB®

5.2 Test procedure The test consisted in: − Placing the asphalt sample on top of the absorbent foam. The foam reflects less than −20 dB of normal incident energy above 600 MHz. It is thus easier to locate the asphalt layer on vertical pattern when analyzing data. − Adding salt on top of asphalt, in the form of dry particles, brine or pre-wetted grains. Salt was spread as uniformly as possible, in ascending quantity order. It was not possible to follow the salt quantity guiding provided by NPRA. For practical reasons, it was difficult to use the low amount of salt. It sometimes even does not correspond to one salt grain. The salt quantity has therefore been exaggerated to fit the experience. Accurate salt concentrations can only be spread by using winter service vehicles (gritters, spreaders), for in-situ measurements. − Pulling slowly the set board/foam/asphalt with the rope. It should be in motion to simulate the speed of the radar and to create the 3D-image. Movement is also necessary to avoid the static signal filter. Data are recorded with the GeoScopeTM GPR and analysed with Road Doctor®. 1057

Figure 2.

General setting.

Figure 3.

Single scans at different salt concentrations. Table 2.

Correspondence between pulse peaks and interfaces.

Peak number

Interface

1, 2 3, 4 5, 6

Asphalt surface Asphalt bottom/Top of the board Board bottom

1058

3000 2500 2000

R2 = 0.825

Amplitude

1500 R2 = 0.735

1000 500

R2 = 0.895

0 −500 0

5

10

15

20

25

30

35

−1000

−2000

Salt amount (g) Peak 1

Table 3.

45 50 R2 = 0.922 R2 = 0.849 R2 = 0.001

−1500

Figure 4.

40

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Evolution of the reflection amplitudes according to brine quantity.

Data analysis: brine. Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Descriptive statistics Mean Standard deviation Relative standard deviation

−534 90 17%

1199 141 12%

−1304 108 8%

915 172 19%

−1280 280 22%

2335 147 6%

Regression statistics R R2 Standard error

−0.92 0.85 79.96

0.86 0.74 112.07

0.04 0.00 83.85

−0.95 0.90 125.12

0.96 0.92 121.19

−0.91 0.83 79.96

5.3 Results The single scan views reveal pulses coming from the different interfaces (air/asphalt, asphalt/ board and board/ground). For each quantity of salt (dry, diluted or pre-wetted), the pulse amplitudes were measured and listed in a table. Figures 4, 5 and 6 give the evolution of the amplitude in function of the salt amount spread on the asphalt surface. Legend refers to peaks as shown in Figure 3. Statistical analysis of the data showed no correlation between the peak amplitude and the amount of dry salt. As expected, the signal amplitude seems to not be dependent on the dry salt quantity: correlation coefficients on figure 6 are close to 0. Dry salt is indeed not conductive and reflects the electromagnetic wave very slightly. It cannot be detected by the GPR in such small proportions. In pre-wetted salt case (Figure 5), the correlation is moderate (|R| between 0.15 and 0.81). It comes from the fact that the salt is partly diluted. Figure 4 indicates a strong linear relationship between brine concentration and amplitude (|R| between 0.86 and 0.96). The series 3 is an exception because it has an R-value close to 0: the correlation coefficient 1059

4000 R2 = 0.442

3000 2000 Amplitude

R2 = 0.659 1000

R2 = 0.149

0 −1000

0

10

20

50 60 R2 = 0.021 R2 = 0.655

−2000

R2 = 0.203

−3000

Table 4.

40

Salt amount (g) Peak 1

Figure 5.

30

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Evolution of the reflection amplitudes according to pre-wetted salt quantity.

Data analysis: pre-wetted salt. Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Descriptive statistics Mean Standard deviation Relative standard deviation

−502 23 5%

1122 47 4%

−1347 65 5%

1015 50 5%

−1687 90 −5%

2647 135 5%

Regression statistics R R2 Standard error

0.15 0.02 24.62

0.81 0.66 30.33

−0.81 0.66 41.63

0.39 0.15 50.84

−0.45 0.20 87.57

0.67 0.44 110.19

can be strongly attenuated by measurements errors. Even if the salt brine is only a thin film on the surface, it obviously also influences on the reflections from deeper interfaces. An increase in reflected signal strength (peaks 1 and 2) leads to energy loss of following waves (peaks 3, 4, 5 and 6). Reflection/transmission losses occur by absorption and each time the radio waves pass through a boundary (Reynolds, 1997). 6

FIELD TESTING

In situ measurements have been carried out in order to corroborate results obtained in laboratory. Testing consisted in scanning a short road section – 500 m – at regular time interval – 45 min, after passage of the salt spreader. At the same time quantity of salt was directly measured by use of a so-called saltstick SOBO-20 (Nygaard, 2003). This first trial was not conclusive by reason of unfavorable weather conditions. A number of factors should be considered in field testing such as width and pattern of salt spread, residual salt on the road surface, wind, humidity and temperature effect. 1060

3000 2500

R2 = 0.000

2000

Amplitude

1500 R2 = 0.019

1000 500

R2 = 0.003

0 –500 0

5

10

15

20

25

30

35

40

R2 = 0.016

–1000

R2 = 0.001

–1500 –2000

Salt amount (g) Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Figure 6.

Evolution of the reflection amplitudes according to the dry salt quantity.

Figure 7.

Dampening of a road section before use of the SOBO-20.

7

R2 = 0.045 45 50

Peak 6

CONCLUSION

The single pulse analysis comes to the following conclusion: salt is detectable by the Ground Penetrating Radar in presence of water (brine). Salted solution is highly conductive (100 mS/cm for brine); the conductivity is proportional to the salt concentration and since we get high R-values, the assumption of linear dependency between the salt concentration and the amplitude seems to be correct. These positive results concerning brine—the main point of interest— encourage us to continue research: they have yet to be substantiated with data from road trials. Field testing is currently in progress. To utilize the GPR as a practical tool, it would be necessary to develop a specialized equipment and software as well as calibrating GPR-measurement with other type of measurements. 1061

REFERENCES Environnement Canada. 2004. Principe d’utilisation des sels. Retrieved from http://www.ec.gc.ca/ Neal, A. 2004. Ground Penetrating Radar and its use in sedimentology: principles, problems and progress. NPRA. 2003. Håndbok 111 – Standard for drift og vedlikehold. In norwegian. NPRA. 2006. Salt befuktet med varmt vann. Forsøk sesongen 2005/2006 og videre anbefalinger. In norwegian. Nygaard, H. 2003. Rapport om restsaltsmåleren SOBO 20. In norwegian. Reynolds, J.M. 1997. An introduction to applied and environmental geophysics. Wiley. Saarenketo, T. 2006. Electrical properties of road materials and subgrade soils and the use of Ground Penetrating Radar in traffic infrastructures surveys. Salt Institute. 2004. Le sel de voirie et notre environnement. In french. Transportation Association of Canada. 1999. Road salt and snow and ice control. Transportation Association of Canada. 2003. Gestion de la végétation. In french. Transportation Association of Canada. 2003. Gestion du drainage et des eaux de ruissellement. In French. Vaa, T. 2004. Norwegian experience with use of Magnesium Chloride. Vaa, T. & Sakshaug, K. 2007. Salting av veger—En kunnskapoversikt. In norwegian.

ADDITIONAL RESOURCES Eide, E. 2000. Radar Imaging of Small Objects Closely Below the Earth Surface. Mangold, T. 2000. Road salt use for winter maintenance. Sensors & Software Inc. Notes on Ground Penetrating Radar principles, procedures & applications. Stidger, R.W. 2003. The basics of salting and sanding. Better Roads magazine. Svanekil, A. 2007. Forsøk med varmbefuktet salt for å bedre friksjonen på vinteren. In norwegian.

1062

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Seasonal coefficients for the pavement roads in Polish climate conditions M. Graczyk Instytut Badawczy Dróg i Mostów—IBDiM, Warsaw, Poland

ABSTRACT: The paper presents the results of research into seasonal coefficients in testing bearing capacity of pavements in Poland with the use of a FWD—Falling Weight Deflectometer and a BB—Benkelman Beam. The deflection measurement method is one of the methods adopted in designing structural pavement in Poland, in accordance with the standard designs in “Flexible and Semi-Rigid Pavement Maintenance and Rehabilitation Catalogue.” Calculation of the real value of deflection of pavement surface involves accurate measuring or assuming coefficients as in a standard measurement. Therefore, it is very important to measure deflection value independently of the season, in the same standard conditions. This is possible to achieve by adopting seasonal coefficients. 1

CHARACTERISTICS OF CLIMATE CONDITIONS IN POLAND

Poland is situated in a temperate climate zone but its climate can be affected by marine or continental climate influences. This results from humid Atlantic air masses clashing with dry air masses from the interior of Eurasia. Therefore, Polish climate is characterised by significant changeability of weather and considerable differences in the lengths of seasons following one another in consecutive years. It is particularly noticeable as far as winters are concerned—they can either be humid, marine type or fair-weather, continental winters. A visible effect of the clash of the two mentioned masses of air is cloudiness. An average number of cloudy days in a year varies from 60 to 70%, which is a fairly large divergence. Cloudiness often leads to rainfall. Polish sky is the cloudiest in November and the sunniest in August and September. Total yearly rainfall in years 2003–2005 was similar to the maximum in years 1971–2000 (namely 700–1000 mm, with the average yearly 1000 mm) and slightly lower as far as the minimum rainfall is considered (300–500 mm, with the average 550 mm). The total monthly average rainfall in the period between June 2004 and October 2006 was similar to the average monthly maximum in years 1971–2000 and slightly lower when the minimum rainfall figure is concerned. The average monthly temperature distribution in the period of research, namely June 2004 to October 2006, generally did not exceed the average yearly band. Yet, some extreme temperatures were observed, e.g. in January and February 2006 (–8, –6 degrees Celsius) or in July or September (24, 17 degrees Celsius). The analysis of rainfall and air temperature in Poland between June 2004 and October 2006 as well as the average yearly figure in years 1971–2000 shows a considerable variability of temperatures and rainfall in a yearly cycle. Marked fluctuations of average monthly temperatures (ranging from 8 degrees Celsius in January 2006 to 24 degrees in July 2006) as well as rainfall (ranging from 5 mm in October 2005 to 250 mm in September 2006) are typical both of various areas of Poland and of various periods of a given year. The total monthly average rainfall in the period between June 2004 and October 2006 was similar to the average monthly maximum in years 1971–2000 and slightly lower when the minimum rainfall figure is concerned. 1063

2

CHOICE OF RESEARCH SEGMENTS

Pavements, soil and subterranean water conditions and climate regions representative of the country were chosen for an analysis. It was found that the value of deflection depends mainly on the structure, its kind and condition, as well as the thickness of the pavement and the soil type. The temperature of the pavement, the soil moisture and the period of data acquisition are also of a significant importance. A period with similar average weather conditions is termed a season. Spring was the main period to measure deflection and for other periods deflection was extrapolated using seasonal coefficients. The value of seasonal coefficients for weather conditions in Poland was assessed in the course of three-year research into bearing capacity in different areas of the country. The observed climate changeability affects the conditions of operation of the whole pavement construction, particularly upper asphalt layers and earthen foundation of road pavement. The variability of results of research into pavement deflection results mainly from these conditions and therefore it is seasonal. Climatic coefficients affecting seasonal variability: • • • •

air temperature and pavement temperature amount of rainfall as well as pavement construction and soil foundation humidity depth of soil layer that freezes in winter insulation (a humid, wooden area or a dry, open area)

The above mentioned climatic conditions were taken into account while choosing research segments of roads. The segments are situated in various parts of Poland and their situation is shown in Figure 1. Field research on the chosen segments was carried out continuously between September 2004 and September 2006. 3

SEASONAL COEFFICIENTS MEASUREMENT MODELS

The choice of seasonal models of pavement deflection was made on grounds of deflection values obtained as results of field research on the chosen segments as well as deflections calculated for theoretical systems. Basing on available papers, an analysis of research models was carried out in seasonal nature of pavement deflection research in various countries.

.

– deflection research segments

Figure 1.

Research segments situation.

1064

3.1 Statistical model The statistical model of seasonal nature of deflection coefficient was assumed as follows: Umax = Urzecz * fs

(1)

fs = Umax/Urzecz

(2)

where: Umax = stands for the maximum value of pavement deflection in the early spring period; Urzecz = stands for values of deflection in research in varied periods; and fs—stands for seasonal nature coefficient determined for periods of early spring, summer and autumn. The statistical model of seasonal nature of deflection, together with a detailed analysis of research resulting in determining generalized values of fs for different periods of deflection research is presented in the further section of the article. 3.2 Theoretical—experimental model The theoretical model is constructed basing on a general description provided by laws of reaction in continuous medium deformation process, which determines among others values of deflection of the load-bearing surface. The parameters used in the description are as follows: mass density, elasticity modulus, Poisson coefficient, viscosity coefficient of asphalt layer materials, etc. The above parameters change seasonally as a function of temperature and moisture. Average values of these parameters and their statistical deviation can be determined drawing conclusions from the results of field research on the chosen road segments in various areas of the country, using mathematical statistics methods (e.g. optimization with the use on the smallest squares method as well as methods of regression). Putting the above in formal terms, one can use the following equations: ⎡ ∂u u( ρ , E ,ν ,η ) = u( ρ0 , E0 ,ν 0 ) + ⎢ ⎢⎣ ∂ρ

⎤ ⎡ ∂u ⎤ ⎥ * ( E − E0 ) ⎥ * ( ρ − ρ0 ) ⎥ + ⎢ ∂E ⎥⎦ ( ρ0 , E0 ,ν 0 ,η0 ) ( ρ0 , E0 ,ν 0 ,η0 ) ⎦ ⎢⎣ ⎤ ⎤ ⎡ ∂u ⎡ ∂u (η − η0 ) ⎥ (ν −ν 0 ) ⎥ + ⎢ +⎢ * * ⎥⎦ ⎢⎣ ∂ν ( ρ0 ,E0 ,ν 0 ,η0 ) ⎥⎦ ⎢⎣ ∂η ( ρ0 ,E0 ,ν 0 ,η0 )

(3)

In turn, parameters ρ, ν, E can be determined as follows:

ρ = ρ0 + a1 * (T − T0 ) + b1 * (w − w0 )

(4)

ν = ν 0 + a2 * (T − T0 ) + b2 * (w − w0 )

(5)

E = E0 + a3 * (T − T0 ) + b3 * (w − w0 )

(6)

η = η0 + a4 * (T − T0 ) + b4 * (w − w0 )

(7)

where the parameter values for varied pavement layer materials and soil foundation are as follows: u = pavement deflection; ρ0 = standard value of mass density under normal conditions; ν0 = standard value of Poisson coefficient under normal conditions; E0 = standard value of elasticity modulus under normal conditions; η0 = standard value of viscosity coefficient under normal conditions; T = temperature; w = moisture; and ai, bi = correction coefficients determined with the use of statistical methods. 3.3 Theoretical model A theoretical analysis was carried out for a two-layer medium of a pavement—soil foundation type, as described by Burmister (1945). 1065

Solutions for two-layer media, in contrast to the commonly used in numerous models of pavement design and diagnostics medium such as elastic half space, allows for better estimation of real pavement deflection as there is a clear layer structure of the model (pavement layers versus soil foundation). Burmister (1945) determined stress pattern in a two-layer medium with the following assumptions and boundary conditions: • • • • • •

the upper layer has a limited thickness—h the lower layer is infinite vertically and horizontally the upper layer rests on the lower layer each layer material is homogeneous, elastic and isotropic the value of Poisson coefficient is assumed as follows: ν1 = ν2 = 0,5 in the upper layer outside the load-bearing area there is no additional shearing or axial stress

A theoretical analysis of the range of seasonal nature coefficient values for local conditions. The theoretical deflection examined with the use of a Benkelman Beam can be determined with the followig formula: q a u = 1,5 * * ωz E2

(8)

where u = deflection of pavement bearing a vehicle wheel load measured in m; 1,5 = coefficient for a vehicle wheel load bearing on the pavement; q = pavement load in MPa; a = track radius of a vehicle wheel load in m; E2 = elasticity modulus of soil foundation in MPa; and ωz = coefficient depending on the ratio E1/E2 and h/a. The theoretical pavement deflection measured with the use of a FWD can be determined with the followig formula: q a u = 1,18 * * ωz E2

(9)

where u = deflection of pavement bearing a vehicle wheel load measured in m; 1,18 = coefficient for a rigid plate load bearing on the pavement; q = pavement load in MPa; a = track radius of a rigid plate load in [m]; E2—elasticity modulus of soil foundation in MPa; and ωz = coefficient depending on the ratio E1/E2 and h/a. The following pavement construction characteristics, in accordance with the Catalogue of Typical Flexible and Semi-rigid Pavement Constructions were used in the calculations (BB and FWD). i. flexible construction for KR1, 15 cm thick altogether, on subsoil G1 (e.g. gravel and clay mix), [E1—flexible pavement construction elasticity modulus: spring–autumn = 10000 MPa, dry period = 3000 MPa], [E2—subsoil elasticity modulus; spring (with natural moisture w = 18)—12 MPa, dry period (with natural moisture w = 6) = 65 MPa]. ii. flexible construction for KR6, 36 cm thick altogether, on subsoil G1 (e.g. gravel and clay mix), [E1—flexible pavement construction elasticity modulus: spring–autumn = 10000 MPa, dry period =3000 MPa], [E2—subsoil elasticity modulus; spring (with natural moisture w = 18) = 12 MPa, dry period (with natural moisture w = 6) = 65 MPa]. Tables 1 and 2 show the results of the calculations of theoretical pavement deflections for the maximum and minimum values achieved in measurements with the use of a Benkelman Beam as well as a FWD. 1066

Table 1. Theoretical pavement construction deflections in accordance with Burmister model with the use of a Benkelman Beam and the coefficient of deflection variability. Deflection [mm]

Variability coefficient (spring/ dry period) Average values

No

Construction type

Spring

Dry period

Variability coefficient (spring/dry period) Maximum values

1

Flexible construction I (KR1) Flexible construction II (KR6)

1.70

0.87

1.95

1.475

0.71

0.49

1.45

1.225

Season

2

Table 2. Theoretical pavement construction deflections in accordance with Burmister model with the use of a FWD and the coefficient of deflection variability. Deflection [mm]

No

Construction type

Spring

Dry period

Variability coefficient (spring/dry period) Maximum values

1

Flexible construction I (KR1) Flexible construction II (KR6)

1.24

0.59

2.10

1.55

0.475

0.343

1.38

1.19

Season

2

Variability coefficient (spring/dry period) Average values

The variability of the results of the theoretical pavement deflection analysis for the two-layer Burmister (1945) model was as follows: – for Benkelman Beam, the maximum values ranged from 1.45 for flexible pavement construction of type I, corresponding to KR6 to 1.95 for flexible pavement of type I, corresponding to KR1. The average values were at 1.225 to 1.475, respectively. – for FWD, the maximum values ranged from 1.38 for flexible pavement construction of type II, corresponding to KR6 to 2.10 for flexible pavement I, corresponding to KR1. The average values were at 1.19 to 1.55, respectively. – As results from the theoretical calculations, pavement deflection variability and, which follows, seasonal coefficient might be considerably high both for constructions of KR1 and KR6 type, independently of the device type used in tests. 4

SPECIFICATION OF SEASONAL PERIODS OF PAVEMENT DEFLECTION MEASUREMENT

Seasonal periods of pavement deflection measurement need to be described by climatic conditions, mainly by temperature and amount of rainfall. From the analysis of seasonal climate changes in a yearly cycle, both from long-standing observations and the ones from years 2004–2006, it results that four distinct seasons need to be differentiated, taking into account differences in temperature and rainfall: • season I—“winter” including January and February, with the monthly average maximum temperature 0–2 degrees Celsius, the monthly average minimum temperature –4 –3, the monthly average rainfall minimum 20–30 mm and the monthly average rainfall maximum 40–50 mm. 1067

• season II—“early spring” including March and April, with the monthly average maximum temperature 4–8, the monthly average minimum temperature 1–6, the monthly average rainfall minimum 30 mm and the monthly average rainfall maximum 50–80 mm. Pavement deflection measurements were mainly carried out in this period and their results are considered as the most reliable as pavement construction and subsoil, having thawed, have the lowest load-bearing capacity. • season III—“spring/summer” including May, June, July, August and September, with the monthly average maximum temperature 13, 5–18, the monthly average minimum temperature 11–16, the monthly average rainfall minimum 45–60 mm and the monthly average rainfall maximum 100–160 mm. In this period measurements were also carried out, but the results need to be corrected taking a seasonal coefficient into account. • season IV—“autumn” including October, November and, partly, December, with the monthly average maximum temperature 1, 5–9, the monthly average minimum temperature—2–7, the monthly average rainfall minimum 35–40 mm and the monthly average rainfall maximum 60–80 mm. In this period measurements were carried out until the first frost and its results need to be corrected taking a seasonal coefficient into account. 5

DETERMINATION OF SEASONAL COEFFICIENTS

Seasonal coefficients corresponding to given seasons were determined, both for measurements with the use of a Benkelman Beam and a FWD, in accordance with the following procedure: • Average values of deflection were determined after measurements carried out on particular research segments according to the folowing fomula: n

ui i =1 n

(10)

1 n 2 ∑ ( ui − usr ) n − 1 i =1

(11)

usr = ∑ s=

where: usr = average deflection for each measurement taken monthly on a research segment; ui = a single measurement on a given research segment; n = a number of single measurements on a given research segment; and s = standard deviation for measurement taken monthly on a research segment. Table 3.

Monthly average long-standing temperature, divided according to seasons. Monthly average temperature in years 1971–2000 in [ºC]

Month

Maximum temperature

Minimum temperature

Season

January February March April May June July August September October November December

0 0,5 4 8 13,5 16,5 18 18 13,5 9 4,5 1,5

–4 –3 1 6 11 14,5 16 16 11,5 7 2 –2

Winter—season I Winter—season I Early spring—season II Early spring—season II Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Autumn—season IV Autumn—season IV Autumn—season IV

1068

Table 4.

Monthly average long-standing rainfall, divided according to seasons. Monthly average rainfall in years 1971–2000 in [mm]

Month

Maximum rainfall

Minimum rainfall

Season

January February March April May June July August September October November December

50 40 50 80 100 150 160 130 100 80 80 60

25 20 30 30 50 60 60 55 45 40 40 35

Winter—season I Winter—season I Early spring—season II Early spring—season II Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Spring/Summer—season III Autumn—season IV Autumn—season IV Autumn—season IV

• Deflection values adjusted to temperature were determined for the average values of deflection calculated before. The following forula was used: usrT = usr * [1 + 0.02(20 − T )]

(12)

where usrT = adjusted average deflection for each measurement taken monthly on a research segment, taking into account asphalt layers temperature; T—asphalt layers temperature. • Next, standardized average values were calculated for each research segment in order to show deflection variability in different seasons as well as to compare different segments. The value of a standardized average was calculated accordig to the formula: U STp =

usrTk usrODC

(13)

where USTp = standardized average for a single research segment; usrODC = average deflection for each research segment; and usrTk = adjusted average deflection for each measurement taken monthly on a research segment. • Then, standardized average values were calculated for determined earlier seasons (early spring, spring/summer and autumn) in order to show deflection variability in different seasons. Also, global standardized average values were determined. Seasonal standardized average values were determined accordng to the formula: U STp U STc = ∑ season M t

(14)

where: USTc = standardized deflection average for a segment examined in a given season—t (early spring, spring/summer and autumn); USTp = standardized deflection average for a single measurement on a segment in a given season; and M—number of measurements on a research segment in a given season. Standardized average values for given segments in various seasons and global deflection values standardized for given seasons are shown in Tables 5 and 6. • Next, adjusted global seasonal coefficients values were determined according to the following rules: • the first step was to reject extreme values after an analysis of the determined average seasonal coefficients • next, global seasonal coefficients were determined again • the final step was to determine global seasonal coefficients 1069

Global seasonal coefficients were determined with the following formula: f skGLseas =

f GLseas′

(15)

f GLseas′III −IV

where f skGLseas = adjusted global seasonal coefficients for seasons—t: early spring, spring/ summer, autumn; f GLseas' = global seasonal coefficient determined with rejecting extreme values in seasons—t: early spring, spring/summer, autumn; and f GLseas' III–IV = global seasonal coefficient determined with rejecting extreme values in early spring season (base season). Global seasonal coefficient determined with rejecting extreme values—f and adjusted global seasonal coefficients for seasons are shown in Tables 7 and 8. Research confirmed dependence of deflection values on a research season, with an increasing trend, both for adjusted global seasonal coefficients for a Benkelman Beam and a FWD. 6

SEASONAL COEFFICIENTS FOR DEFLECTION MEASUREMENTS FOR POLAND

Seasonal coefficients determined according to the statistical model correspond to the results of theoretical calculations as far as the average adjusted values are concerned. For the average adjusted values, seasonal coefficients are given below. For the measurements with the use of BB: for theoretical calculations–1.225 and for the statistical model–1.204. For the measurements with the use of FWD: for theoretical calculations–1.190 and for the statistical model–1.210. From an analysis of similar research abroad, it results that seasonal coefficient values are in the range of 1.00 to 1.6, with a dominating range of 1.0 to 1.3. As a result of the measurements of pavement construction deflection on the research segments with the use of a Benkelman Beam and a FWD as well as theoretical calculations,

Table 5.

Seasonal standardized average values for given research segments (Benkelman Beam).

Seasonal standardized average for research segments USTc – BB Season Research segment

Early spring III–IV

Spring/summer V–IX

Autumn X–XII

1.00 0.08

0.94 0.22

Global standardized deflection (mm) Average value Standard deviation

Table 6.

1.06 0.16

Seasonal standardized average values for given research segments (FWD).

Standardized seasonal average for segments USTc – FWD Season Research segment

Early spring III–IV

Spring/summer V–IX

Autumn X–XII

1.03 0.16

0.87 0.13

Global standardized deflection (mm) Average value Standard deviation

1.08 0.15

1070

Table 7.

Global seasonal coefficients for BB. Seasonal coefficients – BB Seasons

No

Values

III–IV

V–IX

X–XII

1 2 3 4

Global seasonal coefficient (without extreme values) Standard deviation (without extreme values) f GLseas' III-IV f skGLsez

1.12 0.11 1.12 1.000

1.26 0.21 1.12 1.126

1.35 0.43 1.12 1.204

Table 8.

Global seasonal coefficients for FWD. Seasonal coefficients – FWD Sezony

No

Values

III–IV

V–IX

X–XII

1 2 3 4

Global seasonal coefficient (without extreme values) Standard deviation (without extreme values) f GLseas' III-IV f skGLseas

1.02 0.03 1.02 1.000

1.15 0.18 1.02 1.124

1.23 0.14 1.02 1.210

Table 9.

Seasonal values for deflection measurements in Poland. Seasonal coefficients fs Season

No

Measurement

III–IV

V–IX

X–XII

1 2

Beam/girder deflectometer BB FWD device

1.00 1.00

1.15 1.15

1.25 1.25

foreign research and a statistical analysis, seasonal values for deflection measurements in the area of Poland were adopted as shown in Table 9. In the course of this research, in years 2004–2006, altogether 587 deflection measurements were taken on the research segments. Among these were: • 377 with the use of a BB; in early spring season—72, in spring/summer season—228, in autumn season—77 • 210 with the use of a FWD; in early spring season—43, in spring/summer season—110, in autumn season—57. 7

CONCLUSIONS

1. The chosen research segments are typical of the whole Polish road network with respect to: • geographical situation (the whole country area) • frost penetration zones (all frost penetration zones from 0,8 to 1,4) • types of subsoil (coherent, loose) • types and thicknesses of construction (flexible, semi-rigid; 30–60 mm) 2. In comparison to longstanding observations from years 1971–2000, a slight climate-warming tendency and a decreasing rainfall tendency occurred. 1071

3. As a result of the analysis of a seasonal nature of climate in a yearly cycle, both for longstanding observations in years 1971–2000 and years 2004–2006, four seasons were differentiated: • • • •

season I—“winter” including January and February season II—“early spring” including March and April season III—“spring/summer” including May, June, July, August and September season IV—“autumn” including October, November and, partly, December

4. As a result of the analysis of theoretical pavement construction deflection in the two-layer Burmister’s model the following results were obtained: • for a BB: the maximum values from 1,45 (flexible construction pavement KR6) to 1,95 (flexible pavement KR1). The average values of deflection variability were: 1,225 to 1,475, respectively. • for a FWD: the maximum values from 1,38 (flexible construction pavement KR6) to 2,10 (flexible pavement KR1). The average values of deflection variability were: 1,19 to 1,55, respectively. Having taken into account the theoretical discussion of pavement construction deflection variability, it can be concluded that a seasonal coefficient might be considerably high both for constructions of KR1 and KR6 type, independently of the device type used in tests. 5. As a result of the measurements of pavement construction deflection on the research segments with the use of a BB and a FWD as well as theoretical calculations, foreign research and a statistical analysis, seasonal values for deflection measurements in Poland were adopted as follows: • for “early spring” season (March and April)—fs = 1,00 • for “spring/summer” season (May, June, July, August and September)—fs = 1,15 • for “autumn” season (October, November and, partly December)—fs = 1,25 REFERENCES Antunes M. & Pinelo A. & Correia A. 1998. “Seasonal variation of pavements response to falling weight deflectometer”. Fifth International Conference on the Bearing Capacity of Roads and Airfields. Norway, Trondheim. Burmister D.M. 1945. “The general theory of stresses and displacements in layered systems.” Journal of Applied Physics Vol. 16 No. 1 January 1945. Bayoumy F. & Richter Ch. & Lopez A. 1998. “Quantification of seasonal variation effects of subgrade soil moisture and pavement temperature on pavement performance using LTPP data.” Fifth International Conference on the Bearing Capacity of Roads and Airfields. Norway, Trondheim. GDDP. 1997. “Katalog Typowych Konstrukcji Nawierzchni Podatnych i Półsztywnych”, Warszawa: GDDP. GDDP. 2001. “Katalog Wzmocnień i Remontów Nawierzchni Podatnych i Półsztywnych” Warszawa: GDDP. Graczyk M. & Rafa J. 2002. “Modyfikacja metody wyznaczania nośności nawierzchni wielowarstwowych.” Warszawa: IBDiM. Graczyk M. & Rafa J. & Chomicki M. & Mechowski T. & Sudyka J. 2002. “Method of Estimation of Bearing Capacity of Multi-Layer Pavements with Application of Quasi-Static Tests.” 6th International Conference on the Bearing Capacity of Roads and Airfields, Lisbon, Portugal: Balkema. Lorenc H. 2005. “Atlas Klimatu Polski” Warszawa: IMiGW. Van Gurp Ch. 1995. “Characterisation of seasonal influences on asphalt pavements with the use of falling weight deflectometers Ph.D. Thesis.” Delft University of Technology. Transport Research COST 336—Falling Weight Deflectometr. Final Report of the Action. European Commission. Wistuba M. & Blab R. & Litzka J. 2004. OBERBAUVERSTARKUNG VON ASPHALTSTRASSEN. Methodenüberblick und Ableitung von Klimadaten für die analytische Bemessung. Wien: TU. Wiłun Z. 2001. “Zarys Geotechniki” Warszawa: WKŁ.

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Seal courses for a soft asphalt pavement with semi-rigid base in cold regions X. Wang, X. Zhang & Y. Tan Harbin Institute of Technology, Harbin, P.R. China

ABSTRACT: As a typical structure of roads, asphalt pavement with base course of cement stabilized aggregates, which is usually called semi-rigid base course can be found everywhere in China. Research experiences show that the semi-rigid base course is often more susceptible to moisture and frost or less sufficient for moisture and frost stability. Such designs more frequently lead to reflected cracks, with more extensive low temperature cracking. As more water is penetrating down into the base course through the cracks, the bearing capacity will decrease and deterioration of the road increase. To make an improvement, especially in developing a soft binder asphalt pavement with larger void content of the mix for low volume roads, the author tries to use seal coat as a functional course. This course, in between wearing and base courses, and around 10 mm thick of mixture of asphalt binder and fine aggregates, is specially designed for moisture separation and/or mitigation of reflected cracks. In recent years, test roads consisting of seal courses were constructed in north China’s Heilongjiang and Gansu Provinces, where environmental conditions differ largely in temperature, precipitation, geology and others. Some details of design, construction and performance of the seal course based on laboratory and in-situ experiments as well the test roads constructed are presented in this paper. 1

INTRODUCTION

Semi-rigid base course is the prevailing type of base course for both bituminous and cement concrete pavements, and for both trunk roads and rural roads in China, due to its resistance to rut, increasing heavy loads of axles, and others. It is usually composed of cement stabilized macadam, or cement stabilized sandy gravel, or lime and fly ash stabilized macadam. Two layers and one layer of such type of base course are quite often adopted for trunk roads and rural roads respectively. In its implementation, reflected cracks due to shrinkage are more easily found, with low temperature cracking worsen. And if not sealed in time and effectively, the cracks as the access of water may further endanger the moisture and frost stability of the base course and even the overall performance of the road as well, possibly decreasing the service life of roads, or contributing to the longitudinal cracking of roads the reasons of which are now uncertain. Early in situ investigations were carried out to study moisture and frost stability of typical semi-rigid base courses (Wang, 1998). From the strength variations in structural layers of cement stabilized materials at different periods, it can be seen that strength of material itself or strength at top of each layer realizes the highest value in the year of construction completion or in the first year after completion. After suffering from dry-moist cycles and frost-thaw cycles later in different seasons, strengths decrease considerably comparing with the initial values. Road structures with semi-rigid course are less adopted in western countries. Similar application can be found in England that lean concrete, or cement stabilized granular materials, or cement stabilized soils are used as materials for a base course or subbase course. And before being open to traffic temporarily, according to technical specifications in some countries, a seal course with emulsified asphalt surfacing should be applied on top of the base course (Hachiya & Sato, 1997). 1073

Soft asphalt pavements are effective in crack resistance, when combined with base course of unbound aggregates (Wang, 2005). Due to the fact that semi-rigid base course exists widely in new road construction and rehabilitation projects in China, soft asphalt pavements may need to be applied with the semi-rigid base. In this case, the seal course can be a good solution to unfavorable influences from large void content of soft binder mixture of the wearing course. In recent years, more researchers are striving for solutions to related problems with more attention to the base course itself (Wang & Wang, 2005). The intent has been to counteract its related weakness by applying a multifunctional course in the road structure, based on the state-of-art of the semi-rigid course and prior to no workable measures available. Two typical structures of bituminous pavements were selected for tests. One is for rural roads usually with low volume of traffic, newly developed for a soft asphalt pavement by the author, and the other for trunk roads, with larger volume of traffic. 2

SITES AND CLIMATES

2.1 Sites of the test roads Test road sites cover two different parts of northern China. Test Section NW1 is located in Min County, northwestern Gansu Province, Test Section NE1 in Fuyu County, northeastern Heilongjiang Province. Although the roads differ largely in locations, climatic conditions and even road structures, the problem to solve is identical, i.e., to improve the stability of semi-rigid base and to mitigate cracking, as described above. Test Section NW1 is tested for application in rural road, Test Section NE1 for trunk road. 2.2 Climates in study area Test Section NW1 is situated in western Mountain Qin, 1700–3000 m above sea level, with frequent geological disasters. Monthly average temperature varies from –6.9°C (January) to 16°C (July). Annual average air temperature is 5.7°C, annual average precipitation 596.5 mm, maximum frost penetration 1.23 m. Test Section NE1 is situated in Songnen Plain, in the vicinity to Nenjiang River, 200–250 m above sea level. Monthly average temperature varies from –25.7°C (January) to 22.8°C (July). Annual average air temperature is 3.2°C, annual average precipitation 415.7 mm, maximum frost penetration 2.20 m. 3

ABOUT DESIGN AND CONSTRUCTION

3.1 Structure of test roads Types of road structure are listed in Tables 1 and 2, for Test Section NW1 and NE1, respectively. Disregarding bearing of loads, seal course should not be listed as a structural layer, in real sense. It is done in the tables intentionally, just to highlight its importance. It would be helpful to improve road performance structurally. 3.2 Construction work Constructed in 2006, Test Section NW1 is in S210 Barenkou—Daimasi Highway, with station number from 8 + 100 to 8 + 900; in 2007, Test Section NE1 is in G111 Qiqihaer—Nehe Highway, Table 1.

Structure for test section NW1.

Structure

Depth, cm

Description

Wearing course Seal course Base course Filter course

4 0.6 20 20

OG-B16, soft binder asphalt Slurry seal Cement stabilized aggregates, 4% cement content Natural sandy gravel

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Table 2.

Structure for test section NE1.

Structure

Depth, cm

Description

Wearing course Binder course Seal course Base course Subbase

5 7 1 20 20

AC-16, SBS modified binder AC-25 Synchronized crushed stone seal coat Cement stabilized aggregates, 4% cement content Cement stabilized aggregates, 5% cement content

SC1, Min County Figure 1.

SC2, Fuyu County

Two different seal courses after completion of construction.

with station number from 40 + 610 to 40 + 810. Seal courses for Test Section NW1 and NE1 are designated with SC1 and SC2 respectively. For construction, special-purpose equipment for seal course is suggested to achieve anticipated quality. One should continue to the next course as soon as possible so as not to be polluted. The surface textures of the two types of seal courses may differ considerably from each other as shown in Figure 1. The important detail lies in preventing constructed layers from water permeation and pavement cracking. 4

EXPERIMENTS AND OBSERVATIONS

4.1 Technical specifications and tests According to Technical Specifications for Construction of Highway Asphalt Pavements (JTJ032-94), technical requirements for SC1 are shown in Table 3 and Table 4, which must be met during construction for quality control. As for SC2 seal course, based on construction experiences in the country, Tables 5, 6 and 7 show requirements and some test results. Table 3.

Grading requirements for SC1 seal course. Passing (%) to the following size (mm) of sieves

Type of grading

9.5

4.75

2.36

1.18

0.6

0.3

0.15

0.075

ES-2

100

90–100

65–90

45–70

30–50

18–30

10–21

5–15

1075

Table 4.

Specifications of SC1 mix. Requirements (For fast opening to traffic)

Items Mixing time (25°C), s Cohesion 30 min (for initial setting) tests 60 min (for opening to traffic) WTAT, 1h in water, g/m2 Workability, cm

Table 5.

>120 ≥1.2 ≥2.0 <80 2−3

Grading requirements for SC2 seal course. Passing (%) to the following size (mm) of sieves

Type of grading

6.3

8

12

6–12 mm Results

1–15 10

30–70 60

80–100 100

Table 6.

Specifications of modified asphalt for SC2.

Category

Technical requirements

Results

Penetration (25, 100 g, 5 s), 0.1 mm Ductility (5 cm/min, 5°C), cm Softening point (S.P), °C Flash point, °C R.T.F.O. Mass loss, % Pene. Ratio, % Ductility (5°C), cm

60–100 ≥60 ≥70 ≥260 ≤1 ≥65 ≥35

89 ≥65 80 335 0.02 80 40

Table 7.

Low temperature tests of SBS modified asphalt with additives.

Types of modified asphalt

Particles off, %

Temperature, °C

#

0 2 5

–25 –25 –25

110 asphalt + 2% additives + 5% SBS 110 asphalt + 10% additives + 5% SBS # 110 asphalt + 15% additives + 5% SBS #

Based on the laboratory tests, neither base asphalt nor asphalt of high grades can meet separately the requirements for low temperature adhesion. According to mixing tests (see Table 7), it is proposed to adopt the one with 5% SBS modifier and 15% of additives as the binder for SC2 seal course.

4.2 Pavement performances Seal courses of the kinds are known as being watertight or water-proofing. In-situ experiments of water permeability and the site experiences further confirm the same situation. Figure 2 shows a picture taken during construction of the wearing course of soft binder asphalt at the top of SC1 seal course, which was just finished days before. It can be clearly noted that the water down from the wearing course flows along the road crown via the surface of seal course, and off the road. As a measure to guarantee the base course, the seal course is able to improve water and frost stability of semi-rigid base, so as to prolong or ensure subsequently its service life. 1076

Figure 2.

Water seeping down from wearing course flowing away off SC1.

Table 8. Listing of crack observations to test section NE1 and section nearby for comparison. Test Section NE1

Section nearby for comparison

Station

Length, m

Width, mm

Station

Length, m

Width, mm

K40 + 610 K40 + 644 K40 + 684 K40 + 706 K40 + 728 K40 + 750 K40 + 786

9 9 9 9 9 9 9

5 7 3 4 2 6 9

K40 + 408 K40 + 430 K40 + 440 K40 + 470 K40 + 477 K40 + 492 K40 + 512 K40 + 540 K40 + 551 K40 + 570 K40 + 573 K40 + 585 K40 + 605

7 9 9 9 9 9 9 9 3 9 5 9 9

1 8.5 1 3 3 5 8 5 2 2 1 4 10

Pavement cracks of the test roads are observed regularly, especially when the winter season ends each year. Data of pavement cracks, from in-site observations to Test Section NE1 are given in Table 8, which lists the location in terms of station number, how long and how wide of each crack. The observations were taken on April 20, 2008. Test Section NE1 is 9 m wide, while the other in study is 7 m. It means the transverse crack goes across the entire pavement, if a piece of crack is 9 m long. No cracks have been found so far in Test Section NW1, mostly and largely due to the favorable combination of suitable materials and structure, and the mild weather there as well. From Table 8, in the section for comparison, which is in close vicinity to the test section and with no seal course applied, it cracks averagely at every 15.15 m, in longitudinal direction of the road. For Test Section NE1, it cracks at an interval of 25.14 m. And based upon the latest observation on February 23, 2009, it cracks averagely at every 15.00 m in the section for comparison, and 23.63 m in Test Section NE1. It can be seen that the measures taken relating to seal courses are preliminarily effective. Further verification will be continued. 5

CONCLUSIONS

Cracking and crack-induced issues of asphalt pavement with semi-rigid base course, which is typical and common in China, have long aroused pubic concerns. Improvements and new solutions are being strived for continuously. To improve water and frost stability and to mitigate reflected cracks, in connection with ongoing research projects, this paper attempted to employ an alternative way using the seal course as a multifunctional layer. It was a structural 1077

approach. Tentative effects were achieved and presented in this paper. Information of long term pavement performance is necessary to acquire, by means of FWD application to determine about variations of bearing capacities of roads, especially property changes of semi-rigid base course, in addition to regular observation of cracks. REFERENCES Hachiya, Y. & Sato, K. 1997. Effect of tack coat on bonding characteristics at interface between asphalt concrete layers. Asphalt Pavements; Proc. 8th intern. symp., Seattle, 10–14 August 1997. Seattle: International Society for Asphalt Pavements. Wang, X. 1998. Evaluation to the typical structures of cement concrete pavements in Heilongjiang. In Refsdal Nordal (ed.), Bearing capacity of roads and airfields; Proc. 5th intern. symp., Trondheim, 6–8 July 1998. Trondheim: Tapir Academic Press. Wang, X. 2005. Development of a Hi-soft asphalt pavement for cold regions. In Ivar Horvli (ed.), Bearing capacity of roads, railways and airfields; Proc. 7th intern. symp., Trondheim, 27–29 June 2005. Trondheim: Tapir Uttrykk. W,Z. & W,W. 2005. Analysis of raw materials of stabilized macadam—cement and standard. Journal of Liaoning Provincial College of Communications 7(4): 19–20.

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Thermal stress analysis in ultra-thin whitetopping pavement J.R. Roesler & D. Wang University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

ABSTRACT: The primary objective of this theoretical thermal stress calculation for ultra-thin whitetopping (UTW) was to determine if the initial crack spacing at early ages (e.g., 24 hours) can be estimated. Temperature profile data and laboratory elastic and fracture parameters are presented for several concrete mixtures at early ages. The analytical model coupled with the measured field data revealed that 4 by 4 ft UTW panels will not crack at every saw-cut joint for the concrete mixtures and climatic conditions evaluated. Larger joint spacing, such as 6 by 6 ft, is sufficient but still may not propagate cracks at every joint. Initiating more joint cracks at early ages may be attained by higher stresses in the concrete layer (e.g., more slab restraint or longer slab sizes), lower material fracture properties, or a deeper notch depth. 1

INTRODUCTION

Several challenges in ensuring an ultra-thin whitetopping (UTW) pavement meets the service life objective are preserving bond between the concrete and existing asphalt concrete layer, and maintaining adequate load transfer across the joints. Since no man-made load transfer devices exist across the contraction joints, the crack width or joint opening must be minimized to maintain aggregate interlock. Several ways to minimize joint opening include smaller slab sizes and selecting concrete mixtures with low heat of hydration, low drying shrinkage potential, or with the inclusion of fiber-reinforcement. Selection of a small slab size will only promote good load transfer if uniformly distributed working cracks exist at early ages. Several UTW projects completed at the University of Illinois in the summer of 2006 and 2007 (Roesler et al. 2008) indicated that many of the contraction joints did not crack initially. In fact, the initial joint cracks occurred at every 5 to 8 joints (for 4 × 4 ft panels). The result of this large crack spacing was wider openings at these initial crack locations and reduced load transfer. Cracks at other locations eventually propagated, but the load transfer efficiency (LTE) across these cracks were dramatically higher than the initial cracks. The primary objective of this analytical study was to determine if the initial crack spacing at early ages (e.g., 24 hours) can be approximately predicted for UTW sections, and if it is possible to promote additional cracks to propagate at early ages. One additional factor, which has made it more difficult to propagate cracks at early ages, is the addition of fibers, which increase the crack propagation resistance of the concrete. The nonlinear mechanical behavior of the fiber reinforcement was difficult to account for in conjunction with the selected nonlinear elastic fracture mechanics model presented in this study. There are two types of thermal stresses generated, namely axial thermal stress due to uniform temperature change in the slab, and curling stress, due to temperature differential through the slab thickness. For simplicity, only linear temperature differentials throughout the slab are considered. Field and laboratory data are presented for several concrete mixture designs at early ages. Finally, a discussion is presented to interpret the field observations and results of the analytical model.

1079

2

SOLUTION METHODS FOR AXIAL THERMAL STRESS

To calculate the axial thermal stress due to uniform temperature change in the slab, two mechanistic-based methods are used. The first one was developed using one-dimensional elasticity theory with a bilinear slab-base friction assumption (Zhang and Li, 2001). This one-dimensional model was modified to predict the time-dependent joint opening in jointed plain concrete pavement (JPCP) due to climatic loadings (Roesler and Wang, 2008). The solution method generates a spatially dependent axial thermal stress. The one-dimensional model takes slab geometries into consideration, such as slab thickness h and length L; in addition the model includes a few other material properties, such as the elastic modulus of the concrete E, the steady-state slab-base frictional stress τ0, and its corresponding slab slippage δ0, where τ0 and δ0 can be determined from a field test. This solution method is abbreviated as the “Bilinear Model” in this paper. Although UTW assumes the concrete is bonded to the underlying asphalt layer, there is field evidence that local debonding occurs under certain conditions and therefore at early ages a slab-base friction assumption is deemed valid. A second method was introduced by Westergaard in 1926 and is based on a two-dimensional elasticity theory. Only the maximum axial thermal stress in the interior area of a large slab can be calculated. As expected, the derived formula is independent of slab geometric conditions. To facilitate the introduction of the Bilinear Model, the underlying bilinear slab-base interfacial restraint model is presented first (Roesler and Wang, 2008). 2.1 Slab-subbase interfacial restraint Let x be the direction along the Portland cement concrete (PCC) slab length, z be the direction along the PCC slab thickness, where z is measured positive downward and z = 0 is at the mid-depth of slab. The ends of the slab are located at x = 0 and x = L. It is assumed that no displacement occurs at the mid-span of the slab x = L/2, thus only half of the slab (0 ≤ x ≤ L/2) is analyzed. The coordinate system is shown in Figure 1. The slab-base friction interaction serves as a restraint to slab movement, thus proper characterization of this friction is critical for accurately predicting the axial thermal stress in the concrete slab. Field push-off test results suggest that the stress-slippage behavior of a slabbase interface can be satisfactorily approximated by a bilinear function as presented in equation (1) below (Rasmussen and Rozycki, 2001; Wimsatt et al. 1987): ⎧ ⎪ τ 0 u( x ) if u( x ) ≤ δ 0 ⎪⎪ δ 0 τ (x ) = ⎨ if 0 < δ 0 < u( x ) ⎪τ 0 ⎪−τ 0 if u( x ) < −δ 0 < 0 ⎪⎩

(1)

where τ (x) is the slab-base Iinterfacial friction at x (MPa), and a stress sign convention is applied (Timoshenko and Goodier, 1970); τ0 is the steady-state friction (MPa); δ0 is the slippage (displacement) corresponding to the friction of τ0 (mm); u(x) is the average displacement through the PCC slab thickness (mm). In cases where u(x) > 0, the PCC slab contracts, and where u(x) < 0, the PCC slab expands for 0 ≤ x ≤ L/2. Equation (1) is plotted in Figure 2. 2.2 Maximum thermal stress based on bi-linear model Equation (1) and Figure 2 suggest that there are two cases for which axial thermal stress development should be studied. The maximum axial thermal stress σm for each case is listed below and the derivation can be found in Roesler and Wang (2008). 1080

h

x τ

L/2

0

0

z Figure 1. Coordinate system used in this model.

δ0

u(x)

Figure 2. Bilinear Slab-subbase restraint

model.

•

Case 1 occurs when u(0) ≤ δ0, thus ⎡ ⎤ 1 σ m = −Eα ⋅ ΔTave ⎢1 − ⎥ β L cosh( / 2 ) ⎣ ⎦

•

(2)

Case 2 occurs when u(0) ≥ δ0 and u(X0) = δ0 , thus ⎡ ⎤ 1 1 2 σ m = −Eα ⋅ ΔTave ⎢1 − ⎥ + E β δ 0 x0 cosh( β (0.5L − x0 )) ⎣ cosh( β (0.5L − x0 )) ⎦

(3)

Here, E and μ are the modulus of elasticity and Poisson’s ratio of concrete, respectively; ΔTave is the temperature difference between uniform (or average) temperature at time t in the slab and slab setting temperature, where the method for calculating average temperature in the slab is presented in Section 3; α is the coefficient of thermal expansion of concrete; h is the τ0 ; x0 is the coordinate value of x where the displacement u equals slab thickness; β = Ehδ 0 δ0 (x0 can be numerically determined using Equation 4 via a nonlinear equation solver, such as Newton-Raphson iterative method described by Burden and Faires, 2001).

δ0 = −

1 2 e − β x0 − e − β ( L − x0 ) ⎡ β δ 0 x0 + α ⋅ ΔTave ⎤ ⎦ e − β x0 + e − β ( L − x0 ) β⎣

(4)

2.3 Westergaard’s axial thermal stress formula Westergaard’s formula for calculating the maximum thermal stress, assuming an infinite slab length, is given in Equation 5 (Westergaard, 1926) as

σm =

Eα ⋅ ΔTave 1− μ

(5)

As mentioned above, the Westergaard solution is the maximum axial thermal stress induced in the central part of a large slab, where horizontal displacements due to uniform temperature changes are assumed to be fully resisted by the slab-base frictional restraint. Equation 5 always over-estimates the axial thermal stress value since finite slab sizes exist in reality. The Westergaard axial thermal stress serves as the upper bound for axial thermal stresses calculated using other mechanistic models and therefore, should be interpreted with caution. 1081

3

CURLING STRESS DUE TO LINEAR TEMPERATURE DIFFERENTIAL THROUGH SLAB THICKNESS

Westergaard’s curling stress formula for the case of a slab having infinite width and finite length L can be applied (Westergaard, 1926). The maximum tensile or compressive stress σ at the top of the slab in the middle of slab length is (derived from Westergaard, 1926) ⎡ 2(sin λ cosh λ + cos λ sinh λ ) ⎤ σ = σ 0 ⎢1 − ⎥ sin 2λ + sinh 2λ ⎣ ⎦

(6)

L Eh3 Eα ⋅ ΔTc ; λ= ;l = 4 ; and ΔTc is the temperature difference 2(1 − μ ) 12(1 − μ 2 )k l 8 between the top and the bottom of slab, under the assumption of a linear temperature difference through the thickness; and k is the modulus of subgrade reaction. The linear temperature difference between the top and the bottom of slab ΔTc(t), can be extracted from a measured nonlinear temperature profile using the concept of an equivalent linear temperature component (Ioannides and Khazanovich, 1998). Given the measured temperature profile through the thickness of slab, T(z, t), the average temperature through the thickness of slab, Tave(t), which is needed in the axial thermal stress calculation can be approximated in equation (7) using the mean-value theorem of integration in calculus. where σ 0 =

Tave (t ) =

1 h/2 T ( z,t )dz h ∫− h / 2

(7)

Also, ΔTc(t) is given in Equation (8) (Roesler an Wang 2008) 12 h / 2 ⎛ h ⎞ ⎛h ⎞ ΔTc (t ) = TL ⎜ − ,t ⎟ − TL ⎜ ,t ⎟ = − 2 ∫ ξT (ξ ,t )dξ h −h / 2 ⎝ 2 ⎠ ⎝2 ⎠

(8)

where TL is the equivalent linear temperature component. 4

THERMAL STRESS CALCULATIONS

The main inputs for the calculation of thermal stresses based on the above methods are listed as: temperature profile, setting temperature, elastic modulus, base parameters, and the soil k-value. 4.1 Temperature profile The temperature profile through the thickness of slab is critical in the thermal stress development at early ages, also the temperature profile in the slab during the first 24 hours plays an important role in selecting the appropriate saw-cutting for UTW (including sawcut timing, joint spacing, etc), slab temperature data measured at different depths for times t = 6, 8, 10, 12, and 24 hours after the slab was cast was used and listed in Table 1, where the slab thickness is 4.5 inch. Furthermore, the average temperature and equivalent linear temperature differential calculated using equations (7) and (8), respectively are listed in Table 2. 4.2 Setting temperature The setting temperature is assumed to be 50°C, and inferred to occur at t = 5 hours after the slab was cast, based on the observation of temperature profile measured at 15-minute intervals. 1082

4.3 Elastic modulus of concrete The elastic modulus of concrete E is an important material parameter used in any elasticity theory-based thermal stress formulation. Since no early concrete material data was available for this particular UTW project, elastic moduli of six different concrete mixtures tested in the laboratory were used. The elastic modulus values are given in Table 3. Note the concrete mixture nomenclature in Table 3 (e.g., 555.44) stands for the 555 lb/yd3 of cementitious materials, 0.44 water to cement ratio, and ‘st’ means a 25 mm maximum aggregate size was used instead of 38 mm. 4.4 Base parameters The parameters used in the bilinear slab-base restraint model for concrete placed on an asphalt layer are: τ0 = 0.052 MPa and δ0 = 0.38 mm. 4.5 K-value The k-value or modulus of subgrade reaction used in Westergaard’s curling stress formula is assumed to be 100 psi/in. 4.6 Maximum axial thermal stress The maximum axial thermal stress are given in Table 4 for different joint spacing calculated using the Bilinear Model for Mix_3 (Anna, IL), along with those based on Westergaard’s Table 1.

Measured concrete slab temperature at different depths (ºC).

Time after slab cast (hrs)

Surface

1 in.

2 in.

4.5 in.

6 8 10 12 24

47.73 44.68 39.41 35.50 31.32

48.39 45.18 40.97 36.99 31.33

48.41 45.56 42.10 38.22 31.36

45.06 44.56 42.72 39.69 31.44

Table 2. Calculated average temperature and linear temperature differential (ºC).

Table 3.

Time after slab cast (hrs)

Mean temperature

ΔT (Ttop–Tbottom)

6 8 10 12 24

47.03 44.99 41.79 38.22 31.38

4.87 0.72 –3.62 –5.07 –0.18

Elastic modulus of concrete at early ages (MPa).

Mixture

6 hours

8 hours

10 hours

12 hours

24 hours

Mix 3 (Anna, IL) Mix 11 (Dan Ryan) 555.44 555.44st 688.38 688.38st

7,331 3,360 1,635 1,196 1,180 1,368

9,468 4,480 4,542 3,322 3,277 3,800

11,452 5,601 7,766 5,679 5,603 6,496

13,283 6,721 11,820 8,643 8,528 9,888

21,049 13,441 16,843 12,316 12,152 14,090

1083

formula, which is independent of joint spacing. Table 4 demonstrates that the maximum axial thermal stress only varies slightly with large joint spacing from 120 ft to 240 ft. Thus, only the maximum axial thermal stress based on the Bilinear Model for L taken between 12 ft and 120 ft were considered for the rest of mixture analyses in this study. Thermal stresses for joint spacing less than 12 ft were not calculated since the tensile stresses were very small. In the first 24 hours after the whitetopping pavement is cast, the fully restrained (or bonded) condition between PCC slab and existing asphalt concrete (AC) layer may not be well develop. In this paper, equation (1) was adopted to describe the shear stress acted on PCC slab by AC layer. This slab-base friction assumption generates reasonable maximum axial thermal stress for Mix 3 (Anna). Furthermore, the full restraint assumption based on Westergaard’s formula serves as an upper bound of the maximum axial thermal stresses as seen in Table 4. Table 5 lists the curling stresses at the top of the slab for different joint spacing values for Mix_3. As expected, Table 5 shows that Westergaard’s curling stress values remain unchanged in the first three or four decimal places when L was greater than 40 ft (L/l → ∞). Therefore, only the curling stresses for L ranging from 12 ft to 40 ft for the other mixtures were considered. 5

ANALYSIS OF SAW-CUTTING PATTERN

The material fracture properties, KIC and cf , are required for calculation of the nominal strength of the concrete slab at early ages. Table 6 presents the experimental fracture properties for the six concrete mixtures at 6, 8, and 10 hours. Table 7 lists the nominal strength of concrete slab (σN) for the Mix_3 (Anna) mixture versus the notch depth-to-slab thickness ratio (a/d), where a is the notch depth and d is the slab thickness. σN is calculated using Bazant’s size effect model and measured concrete fracture properties (KIC and cf) at several ages. The detailed explanation of this model is contained in the paper by Gaedicke et al. (2007). Given the nominal strength of concrete slab (σN) and the combined maximum tensile thermal stress σ for a fixed joint spacing at a particular time (Tables 4 plus 5 stresses), the minimum saw-cut depth to slab thickness ratio (a/d) can be determined by setting σ equal to σN Table 4.

Maximum axial thermal stress based on bilinear model for mix 3 (Anna) (MPa). Time elapsed (hrs)

Joint spacing L (ft)

6

8

10

12

24

12 20 24 28 30 40 60 80 100 120 140 160 180 200 220 240 Westergaard’s Result

0.050 0.104 0.128 0.148 0.156 0.187 0.214 0.222 0.225 0.225 0.225 0.226 0.226 0.226 0.226 0.226 0.265

0.088 0.193 0.242 0.286 0.305 0.380 0.453 0.478 0.487 0.490 0.491 0.491 0.491 0.491 0.491 0.491 0.578

0.148 0.335 0.428 0.512 0.551 0.707 0.872 0.935 0.959 0.968 0.971 0.972 0.973 0.973 0.973 0.973 1.145

0.217 0.502 0.648 0.785 0.848 1.113 1.412 1.537 1.587 1.607 1.615 1.618 1.619 1.620 1.620 1.620 1.906

0.357 0.837 1.073 1.304 1.417 1.956 2.849 3.431 3.748 3.907 3.984 4.021 4.040 4.048 4.053 4.055 4.772

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from Table 7 for Mix_3 (Anna). A set of notch depth ratios required for equilibrating the nominal strength of the concrete to the maximum tensile stress for various joint spacing at different saw-cutting times are given in Table 8 for Mix_3 (Anna). The tensile stresses presented in Table 8 are the superposition of the axial thermal stress and maximum tensile curling stress; the tensile stress is calculated at the top of slab, except at t = 6 hours where it is greatest at the bottom of the slab due to daytime curling stresses. In the case of maximum tensile stresses at the bottom of the slab, no saw-cut depth suggestion is made since cracks will initiate at the bottom and propagate upward if tensile stresses are above the nominal strength of the concrete slab. However, these bottom tensile stresses assume that the material does not creep. The tensile creep at early ages has been reported to relax stresses as much as 50 percent (Grasley, 2006), which would reduce these bottom stresses below the material strength. The nominal strengths of concrete slab (σN) made by the other mixtures at different notch depth-to-slab thickness ratios (a/d ) are given in Tables 9, 11, 13, 15, and 17, and the corresponding saw-cut notch depth ratio (a/d ) based on critical tensile stress (thermal) are given in Tables 10, 12, 14, 16, and 18, respectively. Table 5.

Curling stress for Mix 3 (Anna) (MPa). Time elapsed (hrs)

Joint spacing L (ft)

6

8

10

12

24

12 20 24 28 30 40 to 240

–0.236 –0.219 –0.216 –0.217 –0.217 –0.217

–0.045 –0.043 –0.042 –0.042 –0.042 –0.042

0.268 0.259 0.253 0.251 0.251 0.252

0.429 0.424 0.412 0.408 0.408 0.410

0.022 0.025 0.023 0.023 0.023 0.023

Table 6. Critical stress intensity factors (KIC) and cf values at early age. Mixture Mix 11

Mix 3

555.44

555.44st

688.38

688.38st

0.16 0.22* 0.33

0.03 0.12 0.19

0.02 0.07 0.19

0.05 0.17 0.33

0.03 0.10 0.26

0.062 0.040* 0.016

0.069 0.037 0.026

0.027 0.031 0.018

0.0014 0.0030 0.0048

0.0014 0.0018 0.012

Age (hrs)

KIC (MPa-m0.5)

6 8 10

0.01 0.02 0.04 cf (m) 0.027 0.001 0.004

6 8 10

*Estimated values.

Table 7.

Nominal strength (σN) for Mix 3 (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.268 0.493 1.279

0.301 0.490 1.026

0.284 0.450 0.874

0.267 0.415 0.771

0.243 0.375 0.682

0.212 0.327 0.595

0.178 0.276 0.507

0.145 0.226 0.422

0.116 0.182 0.344

0.092 0.144 0.275

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Table 8.

Saw-cut depth to slab thickness ratio (a/d) for slab made by Mix 3 for different joint-spacing. Concrete ages (hrs) 6

8

Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.28 (Bottom) 0.323 (Bottom) 0.344 (Bottom) 0.365 (Bottom) 0.373 (Bottom) 0.404 (Bottom) 0.431 (Bottom)

Table 9.

a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.043 0.151 0.200 0.244 0.263 0.338 0.411

Too early Too early 0.75 0.65 0.60 0.50 0.30

0.416 0.594 0.681 0.763 0.802 0.959 1.124

0.7 0.5 0.4 0.3 0.25 0.15 0.05

Nominal strength (σN) for Mix 11 (Dan Ryan) (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.035 0.272 1.279

0.032 0.092 0.156

0.029 0.067 0.119

0.026 0.055 0.100

0.023 0.048 0.087

0.020 0.042 0.075

0.017 0.036 0.065

0.014 0.030 0.055

0.011 0.025 0.045

0.009 0.021 0.037

Table 10. Saw-cut depth to slab thickness ratio (a/d) for Mix 11 (Dan Ryan) for different joint-spacing. Concrete ages (hrs) 6

8

Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.148 (Bottom) 0.170 (Bottom) 0.180 (Bottom) 0.187 (Bottom) 0.190 (Bottom) 0.198 (Bottom) 0.203 (Bottom)

Table 11.

a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.0541 0.120 0.144 0.162 0.169 0.193 0.208

0.3 0.08 0.07 0.06 0.06 0.04 0.04

0.265 0.380 0.429 0.469 0.486 0.542 0.585

0.05 Too late Too late Too late Too late Too late Too late

Nominal strength (σN) for Mix 555.44 (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.058 0.314 0.594

0.053 0.275 0.498

0.051 0.252 0.443

0.048 0.231 0.401

0.044 0.209 0.358

0.038 0.182 0.313

0.032 0.154 0.265

0.026 0.126 0.219

0.021 0.102 0.177

0.016 0.081 0.141

6

DISCUSSION

The maximum axial thermal stress calculations using the Bilinear Model in Table 4 suggest that increases in stress are linked with increases in joint spacing and the maximum axial stress approaches the theoretical maximum axial stress calculated based on Westergaard’s formula (from Equation 5) for very large slab sizes. The Westergaard solution for maximum 1086

Table 12.

Saw-cut depth to slab thickness ratio (a/d) for Mix 555.44 for different joint-spacing. Concrete ages (hrs) 6

8

Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.0801 (Bottom) 0.0913 (Bottom) 0.0944 (Bottom) 0.0962 (Bottom) 0.0968 (Bottom) 0.0983 (Bottom) 0.0988 (Bottom)

Table 13.

a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.0541 0.121 0.145 0.164 0.171 0.195 0.211

0.30 0.70 0.60 0.55 0.50 0.45 0.40

0.265 0.467 0.534 0.592 0.618 0.711 0.794

0.05 0.15 0.05 0.0 Too late Too late Too late

Nominal strength (σN) for Mix 555.44st (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.096 0.200 0.713

0.069 0.172 0.565

0.057 0.155 0.487

0.049 0.141 0.432

0.043 0.127 0.384

0.038 0.111 0.335

0.032 0.085 0.260

0.027 0.077 0.237

0.022 0.062 0.192

0.018 0.050 0.154

Table 14.

Saw-cut depth to slab thickness ratio (a/d) for Mix 555.44st for different joint-spacing. Concrete ages (hrs) 6

8

Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.0614 (Bottom) 0.0687 (Bottom) 0.0703 (Bottom) 0.0712 (Bottom) 0.0714 (Bottom) 0.072 (Bottom) 0.0722 (Bottom)

Table 15.

a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.0532 0.1034 0.1194 0.1314 0.1354 0.1484 0.1564

0.85 0.55 0.45 0.35 0.30 0.25 0.20

0.267 0.383 0.434 0.474 0.491 0.549 0.593

0.65 0.40 0.30 0.25 0.20 0.10 0.05

Nominal strength (σN) for Mix 688.38 (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.797 1.564 2.351

0.236 0.739 1.337

0.171 0.557 1.039

0.141 0.466 0.878

0.122 0.404 0.764

0.106 0.352 0.666

0.092 0.303 0.573

0.078 0.256 0.482

0.065 0.212 0.398

0.053 0.172 0.322

axial stress does not accurately assess the crack spacing development in concrete pavements, especially in the first 24 hours. Equations 2, 3, 5 and 6 used for computing thermal stresses are influenced by the elastic moduli of the concrete. It is clear that Mix_3 (Anna), representing a high early strength concrete, exhibits the highest elastic moduli at early ages among the six mixtures 1087

Table 16.

Saw-cut depth to slab thickness ratio (a/d) for Mix 688.38 for different joint-spacing. Concrete ages (hrs) 6

8

Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.0607 (Bottom) 0.0678 (Bottom) 0.0695 (Bottom) 0.0703 (Bottom) 0.0706 (Bottom) 0.0712 (Bottom) 0.0713 (Bottom)

Table 17.

a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.053 0.1026 0.1186 0.1295 0.1345 0.1465 0.1545

Too early Too early Too early Too early Too early 0.95 0.95

0.265 0.380 0.429 0.469 0.486 0.542 0.585

1.00 0.80 0.75 0.70 0.70 0.60 0.55

Nominal strength (σN) for Mix 688.38st (MPa). Notch depth-to-slab thickness ratio

Time (hrs)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

6 8 10

0.478 1.126 1.196

0.142 0.453 0.871

0.103 0.335 0.725

0.085 0.278 0.632

0.073 0.240 0.557

0.064 0.210 0.485

0.055 0.181 0.415

0.047 0.153 0.346

0.039 0.127 0.283

0.032 0.103 0.227

Table 18. Saw-cut depth to slab thickness ratio (a/d) for Mix 688.38st for different joint-spacing. Concrete ages (hrs) 6 Joint spacing L (ft)

Tensile stress

12 20 24 28 30 40 60

0.0689 (Bottom) 0.0777 (Bottom) 0.0798 (Bottom) 0.0810 (Bottom) 0.0814 (Bottom) 0.0823 (Bottom) 0.0826 (Bottom)

8 a/d

10

Tensile stress

a/d

Tensile stress

a/d

0.0539 0.1113 0.1303 0.1442 0.1502 0.1672 0.1782

Too early 0.9 0.8 0.75 0.70 0.65 0.60

0.290 0.418 0.475 0.523 0.543 0.615 0.673

0.80 0.60 0.50 0.45 0.40 0.30 0.25

studied here. As expected, Mix_3 (Anna) attains the largest axial thermal stress among the six mixtures with all other conditions the same. In the concrete mixtures presented in Tables 8, 12, 14, 16, and 18 (excludes Mix_11), the concrete strength gain is high enough that the induced thermal stresses will not be able to propagate the cracks at the pre-determined notch depth ratio of 0.25 to 0.33 and panel size of 4 ft. In fact, cracks will not initiate at 12 ft spacing for this thermal history and concrete material parameters. Cracks will only propagate at longer spacing (20 to 40 ft) due to the effect the slab length has on the axial stress development as the concrete material cools the first night. This is very consistent with the UTW field observation that typically results in every 5th to 8th saw-cut joint propagating a crack, i.e., 20 to 32 ft spacing between propagated joint cracks. Table 10 is the one exception to the aforementioned behavior. This concrete mixture contained 35 percent slag and gains strength and elastic modulus more slowly. As shown in Table 10, it is much easier to propagate cracks at early ages, i.e., the required notch depth ratios are very small (<0.25). There may be a means to increase the elastic modulus of the concrete without proportionally increasing its strength gain. However, this may be very difficult without significant 1088

research to develop appropriate strategies and material combinations. Furthermore, the main factors in the concrete modulus of elasticity are related to the aggregate type and aggregate volume. One active way of potentially propagating the cracks is thermally cooling the surface of the slab (using water and wind) after the peak concrete temperatures have been reached. This has some appeal since it would limit early-age drying shrinkage, however, it may promote de-bonding of the concrete from the underlying asphalt concrete layer before the bond strength has developed sufficiently. Another promising technique to assure early age joint cracks at the desired spacing may be to dynamically fracture the joint with a mechanical device (Cockerell, 2007). 7

SUMMARY

From this Ultra-Thin Whitetopping (UTW) study, the field observation, laboratory testing, and analytical analysis support each other in terms of the observed cracking pattern at the joints after the first 24 hours. Certainly, selecting of “best” saw-cutting pattern for an UTW project is a complicated task, since it involves accurate early age prediction of pavement temperature profile, thermal stress fields, and characterization of the specific concrete material mechanical properties. This study reveals that 4 by 4 ft UTW panels will not crack at every saw-cut joint for the given climatic condition and concrete mixture types analyzed and tested. The analytical study suggests that initial larger joint spacing, such as 6 by 6 ft, is fine but still may not propagate cracks at every joint. Shorter slab sizes such as 4 × 4 ft are not necessarily detrimental especially in parking lots since they reduce the shear stress at the concrete-asphalt interface and these slab sizes reduce later age curling and loading stresses. ACKNOWLEDGMENTS This publication is based on the results of ICT-R27-3A Design and Concrete Material Requirements for Ultra-Thin Whitetopping. ICT-R27-3A was conducted in cooperation with the Illinois Center for Transportation; the Illinois Department of Transportation, Division of Highways; and the U.S. Department of Transportation, Federal Highway Administration. A special thanks to Matt Beyer for his collection of the temperature profile data and early-age elastic and fracture parameters. REFERENCES Burden, R.L. & Faires, J.D. (Seventh Edition) 2001. Numerical Analysis. Brooks/Cole. Cockerell, A. 2007. Method and Apparatus for Forming Cracks in Concrete, U.S. Patent No. 7,308,892. Gaedicke, C., Villalobos, S., Roesler, J. & Lange, D. 2007. Fracture mechanics analysis for saw cutting requirements of concrete pavements. In Transportation Research Record 2020: 20–29. TRB, National Research Council, Washington, D.C. Grasley, Z.C. 2006. Measuring and Modeling the Time-Dependent Response of Cementitious Materials to Internal Stresses. Ph.D. Thesis. University of Illinois. Urbana, IL. Ioannides, A.M. & Khazanovich, L. 1998. Nonlinear temperature effects on multilayered concrete pavements. ASCE Journal of Transportation Engineering 124(2): 128–136. Rasmussen, R.O. & Rozycki, D.K. 2001. Characterization and modeling of axial slab-support restraint. In Transportation Research Record 1778: 26–32. TRB, National Research Council, Washington, D.C. Roesler, J.R., Bordelon, A., Ioannides, A.M., Beyer, M., and Wang, D. 2008. Design and Concrete Material Requirements for Ultra-Thin Whitetopping, Illinois Center for Transportation Series No. 08–016, University of Illinois, Urbana, IL, 181 pp. Roesler, J. & Wang, D. 2008. An Analytical Approach to Computing Joint Opening in Concrete Pavements. Proceedings of the 6th RILEM International Conference on Cracking in Pavements, June 2008, Chicago, 79–87. Timoshenko, S.P. & Goodier, J.N. (Third Edition) 1970. Theory of Elasticity. McGraw-Hill, Inc., page 4.

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Westergaard, H.M. 1926. Analysis of stresses in concrete pavements due to variations of temperature. Proc. Highway Research Board, Vol. 6: 201–215. Wimsatt, A.W., McCullough, B.F. & Burns, N.H. 1987. Methods of analyzing and factors influencing frictional effects of subbases. Center for Transportation Research, University of Texas at Austin, Research Report 495-2F. Zhang, J. & Li, V.C. 2001. Influence of supporting base characteristics on shrinkage-induced stresses in concrete pavements. ASCE Journal of Transportation Engineering 127(6): 455–462.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Effect of a changed climate on gravel roads P.O. Aursand Norwegian Public Roads Administration (NPRA), Norway

I. Horvli ViaNova Plan and Traffic AS, Norway

ABSTRACT: In the Norwegian Public Roads Administrations (NPRA) R&D program “Climate and Transportation” the main goal is to improve planning, design, operation and maintenance of the road network in Norway in order to adapt to future climate changes. This implies to come up with recommendations and to develop revised guidelines to cope with a changed climate based on the Intergovernmental Panel on Climate Change (IPCC) reports and Norwegian climate research (RegClim). One of the tasks is to investigate the effect of a changed climate on gravel roads, which is described in this paper. This task will be dealing with analyses of pavement condition, estimation of changes in maintenance costs and proposal for actions to cope with negative consequences of a changed climate. There are limited data available on gravel roads in Norway; hence, a survey in all the NPRA regions was carried out. Pavement and drainage condition data, current maintenance methods, maintenance costs, and intervals where collected and analyzed. The results were used together with the estimated change in climate to do some preliminary estimation for rehabilitation and maintenance needs and the corresponding maintenance costs. 1

INTRODUCTION

In the Norwegian Public Roads Administrations (NPRA) R&D program “Climate and Transportation” the main goal is to improve planning, design, operation and maintenance of the road network in Norway in order to adapt to future climate changes. One of the tasks is to investigate the effect of a changed climate on gravel roads, which is described in this paper. This will make a basis for revised guidelines and maintenance routines to cope with a changing climate. The gravel road network in Norway consists of 5657 km of county roads (2007), 17388 km municipal roads and 48500 km of forest roads. The gravel road network is unevenly spread around the country with a concentration in the eastern and central regions. Traffic volume on the county roads are on average AADT = 1200. The standard for maintenance of gravel roads used by NPRA is described in the Handbook 111 (NPRA 2005). There are given requirements for evenness, crossfall and dust dependent on AADT. The condition of a gravel road will be influenced by climate, traffic, material properties and drainage conditions. The most important climatic factors for gravel roads are temperature (frost, freeze/thaw-cycles/spring thaw weakening) and precipitation (total rainfall, intensity). Other factors like wind and cloud cover will also have some influence. Today’s climate (mean yearly precipitation and temperature) in Norway is shown in Figure 1. The anticipated change in climate found by the Intergovernmental Panel on Climate Change (IPCC) (2007) and Norwegian climate research (RegClim) (National Transport Plan 2007–2019 (2007)) is shown in Figure 2. From the climate data over the last 30 years and the anticipated climate change, the present and future situation for the different regions in Norway is summarized in Table 1.

1091

Figure 1.

Normal mean year precipitation and temperature.

Figure 2.

Anticipated change in mean yearly precipitation and temperature.

Table 1.

Average climate parameters in the different regions. Precipitation

Region

Present (mm/year)

Future (mm/year)

Future (mm/summer)*

Change in number of freeze-thaw cycles (days)

East South West Mid North

900 1500 3000 2000 1500

990 1605 3660 2440 1800

578 936 2135 1423 1050

+55 −50 −60 0 −30

* Summer is defined as the bare ground season between April 01–October 31.

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2

CONDITION OF GRAVEL ROADS

Because there are limited data available on gravel roads in the Norwegian Road Data Bank (NRDB), a survey in all the NPRA regions was carried out in February 2008. The answers represent around 40% of the county gravel road network. The main areas of interest were pavement and drainage condition, current maintenance methods, maintenance costs and intervals. Figure 3 shows the answers from the respondents regarding pavement and drainage condition. Results show that over 50% of the pavements are in a poor or very poor condition. This implies lack of bearing capacity, lack of cross fall, unevenness, wheel-tracks and potholes, edges preventing drainage and thin gravel surface layer making grading difficult or impossible. At the same time 40% of the ditches has a poor condition, and in some locations totally missing. All these factors acting together will be an even bigger challenge in the future under a changed climate with increased precipitation. The main method of investigating the condition today is by video/photo documentation or visual inspection in situ. Use of FWD, DCP or GPR is not very common on gravel roads today. It is therefore a great lack of condition data in the NRDB on the gravel road network in Norway making the condition assessment difficult and not very accurate. 2.1 Backlog calculations/estimation Over the years there have been budget limitations leading to a significant backlog in required maintenance of gravel roads. A study made by Johansen et al. (2004) calculated the accumulated maintenance backlog to 906–954 mill NOK (129–136 mill USD) for the road pavement and approximately 200 mill NOK (28 mill USD) for the drainage system on the county gravel road network. The accumulated maintenance backlog for road pavement distributed on the different regions is shown in Table 2. The drainage system maintenance backlog was calculated to 928 mill NOK (132 mill USD) (2004) for the whole county road network in Norway. Estimation for the part linked to the gravel roads is shown in Table 3 giving 204 mill NOK (29 mill USD) for this part of the county roads. NRDB also shows that the relative part of gravel roads of the county road network differs quite a lot from region to region as shown in Table 3. The maintenance backlog for the county gravel road network in Norway linked to the road pavement and drainage is all together estimated to: • Gravel surface layer • Base course and subbase course • Drainage

54–100 mill NOK (8–14 mill USD) 853 mill NOK (121 mill USD) 204 mill NOK (29 mill USD)

Pavement condition 16%

Drainage condition (ditches) 10%

5%

40%

47% 32%

50%

Very poor

Figure 3.

Poor

Average

Good

Very good

Very poor

Poor

Average

Pavement and drainage condition on Norwegian county gravel roads.

1093

Good

Very good

Table 2. Drainage system backlog on the gravel road fundament (base and subbase) (Price level and road lengths 2004). Part of roads with strengthening need

Region

Gravel county road length (km)* (%)*

East South West Mid North

1831 779 56 2135 1207

Total

6010

Backlog

(km)

Base and subbase (mill NOK)

Gravel surface layer (mill NOK)

SUM (mill NOK)

68 % 23 % 52% 52% 45%

1239 182 29 1102 548

340,8 50,2 7,9 303,0 150,6

24,1–34,0 3,8–12,6 0,5–0,9 15,1–34,4 10,1–18,2

365–375 54–63 8–10 318–337 161–169

52%

3100

852,5

53,7–100,1

906–954

* Ref. Johansen Jonny, Evensen Ragnar, Holen Åsmund (2004). Table 3. Estimation of maintenance backlog for the drainage system. (Price level and road lengths 2004).

Region

Accumulated drainage backlog, total (mill NOK)

Gravel roads, part of total (%)

Estimated drainage system backlog (mill NOK)

East South West Mid North Total

156,3 168,4 136,6 250,4 215,9 927,5

30,5 13,0 0,9 35,5 20,1 22

47,7 21,9 1,2 88,9 43,4 204

This gives totally 985–1039 million NOK (140–148 million USD) in accumulated maintenance backlog that also has to be taken into account when estimating the strengthening needs to meet more severe climatic loads caused by climate changes in the near future. 2.2 Data from the Norwegian Road Data Bank (NRDB) There are limited data in the NRDB on gravel roads. Only data from the secondary roads/ county roads are available. For the municipal gravel roads and forest roads, very few systematically collected data exist. These data are available in the NRDB for County gravel roads: • • • • • 3

Road length AADT Drainage condition (limited data on ditches, good data on culverts) Bearing capacity (Falling Weight Deflectometer (very limited data)) Structural- and material data (scarce data) MAINTENANCE ON GRAVEL ROADS TODAY

The main maintenance actions on a gravel road pavement are gravel surfacing, grading, dust control, ditch clearing and in some cases stabilization (e.g. bitumen). The frequency of maintenance actions is controlled by the roads condition and budgets. Often the need for maintenance is bigger than the budgets. Comparing the length of gravel road being maintained each year with the total length of gravel roads, gives an indication on how 1094

much maintenance is done each year with the combined effects of both budgets and needs. A questionnaire was sent to 21 contract districts to investigate the maintenance frequencies. The answers showed that with today’s budgets and climatic situation, the county gravel roads are being graded approximately 2,5 times a year, approximately 40% of the total length gets a new gravel surfacing and approximately 9% of the ditches are being cleared each year. Figure 4 shows the timing of each maintenance action. Grading and ditch clearing is done all year round, while gravel surfacing is mainly done in spring but also to some extend in the autumn. Spring gravel surfacing can be trigged by spring thaw weakening. Table 4 summarizes the maintenance action frequencies from the questionnaire. One important factor in maintenance is the triggering factor for when a maintenance action is being preformed. Figure 5 shows the triggering factor/condition for gravel surfacing, grading and ditch clearing. Time of year for gravel surfacing

Time of year for grading

Time of year for ditch clearing

27% 33%

33% 38%

40%

62% 5%

33%

29%

Spring

Summer

Figure 4.

Maintenance action Grading Gravel surfacing Ditch clearing

Springthaw weakening condition 6%

Figure 5.

Autumn

Spring

Summer

Autumn

Maintenance frequencies, result from questionnaire.

Triggering condition for gravel surfacing

Regular cycle 28%

Summer

Timing of maintenance actions.

Table 4.

Other according to contract 22%

Spring

Autumn

Funds 11%

% per year

Maintenance frequency (pr. Year)

Period between maintenance action (Years)

230 40 9

2,3 0,4 0,09

0,4 2,5 11

Triggering condition for grading

Triggering standard for ditch clearing Low bearing capacity in springthaw weakening period 5%

Cannot grade - too thin surfacing 16% Other according to contract 5%

Evenness, tracking and potholes 52%

Thin Complains surfacing 11% problems grading Edges 33% preventing drainage Lack of 5% crossfall 11%

Regular cycle 10%

Whenever required 15%

Funds 10%

Other according to contract 20%

Ditch not working properly 40%

Triggering factors/condition for maintenance.

1095

4

FUTURE SITUATION; NEEDS AND CHALLENGES

4.1 Future climates effect on gravel roads No studies indicate that a temperature increase will have a significant effect on unbound materials. According to Lerfald & Hoff (2007), a changing freezing condition is the main factor that will affect these materials; hence, unbound materials are not significantly affected by temperature change unless they go from a frozen state to a thawed state. This means that a change in temperature around 0°C will affect the state of these materials the most. A freeze-thaw cycle is defined as a change in temperature around 0°C with an amplitude of minimum ±2°C. This parameter was defined to describe the number of freeze-thaw cycles. The change in number of days with these freze-thaw cycles are shown in Figure 6 in addition to the localization of the county gravel roads. More freeze-thaw cycles and mild periods during the winter season will increase the accumulated length of the thawing period leading to increased deterioration. In particular this will be true for the gravel road network, as the sub-base and base course on these roads often consists of slightly frost susceptible materials. The freezing index will decrease in most areas, and the level at which the frost fronts stabilises during winter will be higher up, in some cases in the pavement structure in stead of in the subground as it is today. For gravel roads, this is critical because of the frequent presence of frost susceptible materials in the road structure. The inland areas in the southern and eastern part of Norway will have a great increase in the amount of days with temperatures changing around 0°C, and approximately 33% of the county gravel road network is located in these areas. The present climate in these areas includes dry summers and cold stabile winters, which have resulted in the use of frost- and water-susceptible construction materials without any adverse consequences. With a changed climate as described, a decrease in the condition of these roads will be much likely. Stabilisation of the base course or the use of coarser material in maintenance will probably be important tasks for preparing these roads for the changed climate. Gravel surfaces are sensitive to rainfall when the road is unfrozen. Heavy rainfall will then lead to washing of materials implying development of potholes, corrugation and unevenness. Long-lasting rain will soak the surface, and the E-modulus will be reduced. Increased rainfall in general leads to higher ground water table, infiltration of rainwater and more melt water

Figure 6. Localization of county gravel roads compared with change in number of freeze-thaw cycles (days) (left) and change in groundwater reservoir (right).

1096

in the subgrade and the drainage systems in springtime. This again leads to increased water content in the pavement and reduction in bearing capacity. Figure 6 shows the anticipated rise in ground water reservoir and; thereby, a rise in ground water level. The greatest increase in precipitation will find place in the costal areas of western and northern Norway, but as indicated on Figure 6 there are few county gravel roads in the western part of the country; therefore, an increase in precipitation will have strongest effect on the gravel roads located in the north. These roads represent approximately 50% of the county gravel road network in Norway. For these roads an upgrading of the drainage system is required. As shown in Table 2 a great amount of the gravel road network has poorly constructed drainage system, and this will be a critical factor. Intense rainfall could also be a reason to stabilise the surfacing. The EU North Hemisphere Project ROADEX II has demonstrated a huge effect of improving the drainage system on the low volume road network in the north, Berntsen & Saareketo (2005). Calculations as well as field investigations showed increased service life on these roads in the range of 50–100% and more by improved drainage only. LCC calculations showed positive cost benefit values even with ditch clearing every second year, making drainage improvement to be the most cost-efficient strengthening method of all alternatives. 4.2 Future standard and needs The standard for operation and maintenance (Handbook 111) for roads including gravel roads in Norway is under revision. In the new standard a better-defined quality assessment system will be given. This will make it easier for contractors as well as for road owners to follow up on the operation and maintenance contracts. 4.3 Life cycle cost calculations Maintenance costs have been estimated for each region through the use of a revised model (MOTIV) used by the Norwegian Public Roads administration for budget estimations, Evensen & Holen (2008). In these models there is some trade-off between climate data and maintenance costs. These have been used in addition to other estimations of links between climate and maintenance frequencies. The results from these first preliminary calculations are summarized in Table 5. The calculated changes in maintenance costs are done with respect to the climate in the two norm periods of 1960–1990 and 2070–2100, representing todays and future climate, respectively. The yearly maintenance costs for the county gravel road network within the norm period of 2070–2100 will, according to these calculations, increase with 31 million NOK (4,4 million USD) or 19% compared to the present maintenance needs. A more proactive solution is to improve the quality of the gravel roads to reduce the expected increased maintenance costs caused by a changing climate. One strategy could be to fill the accumulated backlog gap in order to make a less vulnerable gravel road network. The effect of upgrading of drainage up to 30% of the calculated backlog and/or strengthening of the pavement (base and surface) at a level of 40% at 5 years intervals over 20 years has been estimated as shown in Table 6. The calculations showed a reduction in the maintenance costs by about 30% each year as a result of improving drainage and strengthening the pavement. The cost of the drainage was, however, far less than the cost of the strengthening; hence, the drainage was much more cost-efficient than the strengthening. This preliminary study indicates that it will be cost efficient to do drainage and strengthening upgrading of the gravel road network to reduce the excessive costs due to the expected climate change. 5

CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusions This work indicates that the predicted climate change will affect the condition of gravel roads on the secondary road network in Norway significantly. The drainage system and the base and surface accumulated maintenance backlog are major limiting factors for a good riding 1097

Table 5.

Maintenance needs per year and estimated effects on climate change. Maintenance needs today (norm Effect of climate change on maintenance costs (norm period 1960–1990)1000 NOK period 2070–2100) Difference 1000 NOK Graveling

Region

Graveling

East South West Mid North Whole C SUM Acc. Over 20 years

Grading

Ditch clearing

Grading

Ditch From From From clearing precipitation freeze/thaw precipitation

From precipitation

22178 17315 2661 65452 26829 134435

8423 3583 258 9821 5552 27637 163261

363 154 11 423 239 1190

2778 1379 623 15837 6104 26721

6653 −5195 −798 0 −5366 −4705

1685 502 113 4321 2221 8842 31238

73 22 5 186 96 381

2688693

552736

23792

534424

−94103

176833

7612

Table 6. Maintenance costs and present value over 20 years life cycle at different investment rates (0% and 5%).

Strategy

Maintenance cost (mill NOK)

Drainage/ Strengthening costs (mill NOK)

SUM Maint + Drain/strength (mill NOK)

per year

Present value

Present value

Present value

mill NOK/year r = 0% r = 5% r = 0% r = 5% r = 0% r = 5%

No improvement 194 138 Drainage 129 Strengthening Drain + Strength 72

3890 2754 2584 1448

2423 1716 1610 902

0 82 279 361

59 201 259

3890 2836 2863 1809

2423 1775 1811 1162

quality and sufficient bearing capacity on the gravel road network in Norway. This preliminary study indicates that it will be cost efficient to do drainage and strengthening upgrading of the gravel road network to reduce the excessive maintenance costs due to climate change. 5.2 Recommendations Following recommendations are given: • Upgrading and more frequent maintenance of the drainage system is recommended. • Review of rehabilitation and maintenance plans in an optimization process by the use of LCC and asset management calculations together with cost benefit analyses. • More detailed studies on the effect of climate change on gravel roads should be made as a basis for plans to cope with a changing climate. • The condition survey mapping system for gravel roads should be improved through the use of video, Ground Penetrating Radar (GPR) and Falling Weight Deflectometer (FWD). • Simple maintenance actions as the removal of edges and surface reshaping should be made more frequently to allow water to drain more effectively from the surface. • Removing ice and snow from the edges during spring should be done to increase springthaw bearing capacity by draining melt water. 1098

ACKNOWLEDGEMENT The Norwegian Public Roads Administration who has sponsored this work is highly acknowledged.

REFERENCES Alzubaidi, Hossein (2002): On Rating of Gravel Roads, PhD thesis, KTH, Sweden. Alzubaidi, Hossein (2005): Rating of Gravel Roads—Method Description/Bedömning av grusväglag, Metodbeskrivning 106:2005, Vägverket publikasjon 2005: 60, Sverige 2005-11-01, ISSN:1401-9612 (in Swedish). Berntsen & Saareketo (2005): Drainage On Low Traffic Volume Roads- Problem description, improvement techniques and Life Cycle Costs, ROADEX II report April 2005. Evensen, Ragnar (2007): Asessment of Computer System for Calculation of Road Deterioration/Vurdering av EDB-system for beregning av nedbrytning av veg, ViaNova Plan og Trafikk AS, Desember 2007 (in Norwegian). Evensen & Holen (2008): Maintenance of gravel surface layers/Arbeidsnotat for vedlikehold av grusdekker, Statens vegvesen, MOTIV-revisjon 2008 (in Norwegian). Evensen, R. & Holen (2008): Maintenance of drainage systems/Arbeidsnotat for drift og vedlikehold av drens- og avløpsanlegg, Statens vegvesen, MOTIV-revisjon 2008 (in Norwegian). IPCC 2007: Climate change 2007: The physical Science Basis, summary for policymakers. (http:// www.ipcc.ch/). Johansen, J. Evensen, R. & Holen, Å. (2004): Secondary Roads. Maintenance Backlog/Fylkesveger. Etterslep vedlikehold, Hp 4: Grøfter, kummer og rør. Hp 5/6: Vegfundament/Vegdekke—grusveg, November 2004, ViaNova Plan og Trafikk AS, del av Statens vegvesens etatsprosjekt Vegkapitalprosjektet 2000–2004 (in Norwegian). Hansen, M.W. & Stensvold, B. (2005): Asessment of Maintenance Backlog for the Secondary Road Network/Beregning av vedlikeholdsetterslep for fylkesvegnettet, Statens vegvesen, del av Statens vegvesens etatsprosjekt Vegkapitalprosjektet 2000–2004 (in Norwegian). Lerfald, B.O. & Hoff, I. (2007): Climate Influence of Road Material/Klimapåvirkning av vegbyggingsmateriale. State of the art studie, Statens vegvesen Etatsprosjekt Klima og transport, Sintef rapport nr SBF IN A07014, 2007-12-04 (in Norwegian). National Transport Plan 2007–2019 (2007)/Nasjonal Transportplan 2007–2019. Arbeidsdokument: Virkninger av klimaendringer for transportsektoren (in Norwegian). NPRA (2005). Handbook 111—Standard for operation and maintenance/Håndbok 111—Standard for drift og vedlikehold. Vegdirektoratet, 2003. (in Norwegian).

1099

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Water impact on the structural behavior of a pavement structure S. Erlingsson Highway Engineering, VTI—The Swedish National Road and Transport Research Institute, Sweden Faculty of Civil and Environmental Engineering, University of Iceland, Iceland

ABSTRACT: An accelerated load test using a Heavy Vehicle Simulator (HVS) has been performed at VTI’s test facility. The objective was to investigate the response behavior and performance of a commonly used flexible pavement structure in Sweden. The instrumented structure consists of 10 cm bounded layers, granular base and subbase resting on sandy subgrade. The test was divided into three phases: a pre-loading phase, a response phase and the main accelerated loading test where 1,000,000 load cycles were applied. After applying the first 500,000 load cycles the water table was raised and further 500,000 loading cycles were applied. Raising the groundwater table increased the rate of rutting developed in all unbound layers. From the sensor registrations it is clearly seen that the stiffness of all unbound layers decreased as the water table was raised, thus the pressure cells revealed lower registrations but the vertical strain gauges increased their readings. Further, it was observed that the rate of rutting accelerated. This has been interpreted as the impact of higher water content on the characteristics of the unbound layers, the subgrade, subbase and base course. 1

INTRODUCTION

An accelerated load test, referred to as SE06, using a Heavy Vehicle Simulator (HVS) was conducted at the Swedish Road and Transport Research Institute (VTI) test facility in Linköping, Sweden during the winter of 2003 and 2004. The objective was to investigate the response behaviour and performance of a commonly used pavement structure in Sweden. The HVS machine is a linear full-scale accelerated road-testing machine with a heating/cooling system to keep constant temperature during testing (Wiman & Erlingsson, 2008). The length of the tested structure was 6 metres and the loading was in both directions (bi-directional). The test was divided into three phases: a pre-loading phase consisting of 20,000 load applications, a response phase to get information on the general response behaviour of the structure due to various loading, and the main accelerated loading test where 1,000,000 load cycles were applied with dual tyre configuration with a tyre pressure of 800 kPa and an axle load of 120 kN. After applying the first 500,000 load cycles the water table was raised and further 500,000 loading cycles were applied. Raising the groundwater table increased the rate of rutting developed in the structure in all unbound layers. The response of the structure and the permanent deformation development was monitored during the test. Therefore it was possible to investigate the influence of the location of the ground water table on the behaviour of the structure. 2

THE PAVEMENT STRUCTURE

The pavement structure was tested in an indoor concrete pit (depth 3 m, width 5 m and length 15 m) under constnt environmental conditions (Wiman, 2006). The structure is shown in Figure 1. It consisted of 10.1 cm thick Hot Mix Asphalt, divided into 4.8 cm surface course and 5.3 cm bituminous stabilized base. Underneath, there was a 10.8 cm thick unbound aggregate base over a 14.2 cm thick subbase resting on sandy subgrade. The grain size distribution curves of the unbound layers are shown in Figure 2. 1101

0.0 4.8

Asphalt Concrete Bituminous Base

10.1

Granular Base Course 20.9 Granular Subbase 35.1 Subgrade, sand 30 cm gwt

Instrumentation

65.1

Pressure cell Horizontal strain, longitudinal Horizontal strain, transversal Vertical strain

Depth [cm]

Vertical deflection

Figure 1. A cross-section of the tested pavement structure along with the vertical location of the instrumentation. The location of the groundwater table, 30 cm below the top of the subgrade, which was introduced after 500,000 repetitions is shown as well.

Mass passing (finer than), [%]

100 80 60

Base Course Subbase Subgrade

40 20 0 0.001

0.01

0.1

1

10

100

Particle size, D [mm] Figure 2. The grain size distribution curves of the subgrade sand, the subbase and the base course. The vertical black lines show the boundaries of clay, silt, sand, gravel and boulder particles respectively.

The subgrade material used consisted of single sized fine sand with over 90% of the grains in the range of 0.075–0.6 mm. The fine content was less than 2% and the optimum water content was estimated to be 14.4%. Measurement gave 9.9% moisture content during the construction. The subbase was natural gravel in the size range 0–80 mm with around 7% fine content. During construction the water content was measured as 4.5%. The base course was a natural gravel mixed with crushed aggregates. The grain size curve was in the range 0–31.5 mm with a fine content around 8%. The optimum water content was estimated to be 4.5% and measurements during the construction revealed 2.2% moisture content (Wiman, 2006). 1102

Table 1.

Distribution of the centre of loading during the main testing phase.

Position [cm] Frequency [%]

3

–25 0.4

–20 1.6

–15 6.1

–10 12.2

–5 18.3

0 23.4

5 18.3

10 12.2

15 6.1

20 1.6

25 0.4

THE HVS TESTING PROJECT

The pavement structure was instrumented to measure its response and performance due to repeated heavy loadings. A schematic overview of the instruments is given in Figure 1. For stresses three sensors were used at each depth. The stress sensors used were soil pressure cells (SPC) from Nottingham University (earth pressure cells). The tangential strain at the bottom of the bituminous bounded layer was measured with eight asphalt H-bar strain gauges (ASG), four in the longitudinal and four in the transverse directions, respectively. The vertical strain (both elastic and permanent strain) was measured with a total of twelve EMU-coils from Nottingham University (inductive coils), three at each depth range. The vertical deflection was measured with linear variable displacement transducers (LVDT’s) in relation to the concrete bottom of the test pit. The HVS test was divided into three steps. The first step was a pre-loading step. Thereafter comprehensive response measurements were carried out and finally an accelerated load test was performed. The pre-loading step consisted of 20,000 passes of 30 kN single wheel load with a tyre pressure of 700 kPa. The wheel followed an evenly lateral distribution curve to achieve even compaction. The purpose of the pre-loading phase was to relieve some possible residual stresses and cause some post-compaction. Thereafter a comprehensive response phase was carried out where the response of the structure was estimated from single wheel as well as dual wheel configuration for different tyre pressures and axle loads. The accelerated testing phase was carried out at 10°C with a single axle, dual tyre configuration with a wheel loading of 60 kN and tyre pressure of 800 kPa. The centre to centre spacing of the two tyres was 34 cm. The lateral distribution of the loading followed a normal distribution where the wander was divided into nine segments and values of stresses and strains for the middle points of each segment used (see Table 1). The structure was tested for 500,000 load repetitions where the accumulated permanent deformations of the unbound base course, subbase and the upmost 30 cm of the subgrade were monitored as well as the total rut manifested on the surface. Then water was pumped, in a gently manner, into the concrete pit where the structure was located until it rose to the level of 30 cm below the top of the subgrade. This is the same level as the lower plate of the lowest strain sensor in Figure 1. Now additionally and identical 500,000 load repetitions were applied and the accumulated permanent deformation as well as the rutting on the surface were monitored. In addition some response testing was carried out. The performance of the two states where the groundwater table was absent and where it was located at a 30 cm depth below the top of the subbase were both modelled. They are here referred to as the moist versus the wet state of the structure, respectively. Figures 3–5 shows typical registrations from the sensors. 4

THE RESPONSE BEHAVIOR OF THE STRUCTURE

The response of the structure was estimated with regular intervals during the main accelerated testing phase. Figure 3 shows the induced vertical stress measured from the pressure cells under the centre of one of the wheels at 15.5 and 60.0 cm depths due to dual tyre loading combination after approximately 250,000 (moist state) and 750,000 (wet state) loading repetitions. Higher registrations are made in the moist state indicating stiffer structure. Figure 4 shows the induced vertical strain measured from the EMU inductive coils under the centre of one of the wheels over the depth range 10.1–20.7 cm and 35.3–50.5 cm due to a dual tyre loading combination after approximately 250,000 (moist state) and 750,000 (wet state) loading repetitions. Approximately 50% higher registrations are made in the wet state indicating softer structure. 1103

Figure 5 shows the induced horizontal strain measured from the strain gauges under the centre of one of the wheels at the bottom of the bituminous base due to a dual tyre loading combination after approximately 250,000 (moist state) and 750,000 (wet state) loading repetitions. Registration in both the longitudinal (X) and the transverse direction (Y) 150 SPC 214 - d = 15.5 cm

100

stress, σ [kPa]

stress, σ [kPa]

150

0 -50

0 -50

0

500

40

1000 1500 2000 Time, t [ms]

2500

3000

0

500

40 stress, σ [kPa]

SPC 218 - d = 60.0 cm

20

v

v

50

v

v

50

stress, σ [kPa]

SPC 214 - d = 15.5 cm

100

0

-20

1000 1500 2000 Time, t [ms]

2500

3000

SPC 218 - d = 60.0 cm

20 0

-20 0

500

1000 1500 2000 Time, t [ms]

2500

3000

0

500

1000 1500 2000 Time, t [ms]

2500

3000

Figure 3. Induced vertical stress registration of two pressure cells sensors located at 15.5 cm and 60.0 cm depths respectively during a dual wheel loading conditions from both the moist (left) and the wet (moist) phases of the test.

0.004

0.004 Z-35 d = 10.1/20.7 cm

Z-35 d = 10.1/20.7 cm

0.003 strain, ε [-]

0.002

v

v

strain, ε [-]

0.003

0.001 0

-0.001 1500

2000 2500 Time, t [ms]

-0.001 1500

3000

2000 2500 Time, t [ms]

3000

0.0008 Z-29 d = 35.3/50.5 cm

0.0006 strain, ε [-]

0.0004

Z-29 d = 35.3/50.5 cm

0.0004

v

v

strain, ε [-]

0.001 0

0.0008 0.0006

0.002

0.0002 0

-0.0002 2000

2500 3000 Time, t [ms]

0.0002 0

-0.0002 2000

3500

2500 3000 Time, t [ms]

3500

Figure 4. Induced vertical strain registration of two inductive coil sensors over the depth range 10.1–20.7 cm and 35.3–50.5 cm during a dual wheel loading conditions from both the moist (left) and the wet (right) phases of the test.

1104

800

800 ASG 107 - X ASG 108 - Y

ASG 107 - X

600 strain, ε [με]

ASG 108 - Y

400

t

400

t

strain, ε [με]

600

200 0

-200

200 0 -200

0

500

1000 Time, t [ms]

1500

2000

0

500

1000 Time, t [ms]

1500

2000

Figure 5. Induced horizontal strain registration of the ASG gauges at the bottom of the bituminous base during a dual wheel loading conditions from both the moist (left) and the wet (right) phases of the test. X = longitudinal direction and Y = transversal direction.

are shown. Both directions show lower registrations in the moist state indicating stiffer structure. The development of sensors registrations during the test is further shown in Figures 6 to 8. Figure 6 shows the development of the vertical stress as registered at two different depths, 17.5 and 44.0 cm respectively at the centre line of the wheel path. As shown in Figure 1 the uppermost located sensor is in the granular base course but the lower one is in the sandy subgrade. During the first part of the main testing phase, that is load cycles 20,000–530,000 the registered vertical stress is quite constant for the sensor in the granular base. The sensor in the subgrade shows some increase in the registration as the number of load cycles increases. This indicates that the subgrade stiffness is increasing with the number of load pulses indicating that some post-compaction is taking place as a result of the load pulses. As the ground water table is raised, after 530,000 load repetitions, all pressure cells show significant reduction in their registrations. However as the test continues the structure seems to slowly regain its strength as all sensors increase their readings as the number of load repetitions increases. This might be interpreted as a post compaction effect due to increased moisture in the structure. As no moisture sensors were installed this has not been verified. Figure 7 shows the development of the vertical strain as registered over four different depth intervals, 10.1–20.7 cm, 20.7–35.3 cm, 35.3–50.5 cm and 50.5–65.5 cm respectively. Figure 7 shows that the readings are quite constant until 530,000 load repetitions. After the ground water table was raised all sensors show higher readings. The two intermediate sensors, at 20.7–35.3 cm (granular subbase) and 35.3–50.5 cm (the uppermost part of the subgrade) indicate some strength recovery as the number of load repetitions increases but the two others do not. The development of the tensile strain at the bottom of the bitumen base is shown in Figure 8. The registration is quite constant as the ground water table is absent but once it is introduced the strain increase as the structure becomes softer. Some strength recovery seems to take place with increasing number of load pulses and as the number of load repetitions approaches 1,000,000. 5

MODELLING OF PAVEMENT STRUCTURE BEHAVIOR

The response of the pavement structure has been estimated through numerical analysis. For further details of the analysis method, see Erlingsson (2007). A nonlinear elastic behaviour has been assumed for the granular layers using the k – θ expression (May & Witczak, 1981; Gomes-Correia et al., 1999). In a normalized form this equation is frequently written as: ⎛ 3p ⎞ M r = k1 ⋅ pa ⋅ ⎜ ⎟ ⎝ pa ⎠ 1105

k2

(1)

SPC-214 d = 17.5 cm

60 SPC-215 d = 44.0 cm

v

150

Vertical stress, σ [kPa]

Vertical stress, σv [kPa]

200

100 50 0 0

40

20

0

250000 500000 750000 1000000 Number of load repetitions, N

0

250000 500000 750000 1000000 Number of load repetitions, N

Figure 6. Induced vertical stress at three two depths, 17.5 and 44.0 cm, as a function of load repetitions. The vertical dotted line indicates when the level of the ground water table was raised.

0.0010 Z-35 d = 10.1/20.7 cm

Vertical strain, ε [-]

0.0030

v

v

Vertical strain, ε [-]

0.0040

0.0020 0.0010 0.0000

0.0004 0.0002

250000 500000 750000 1000000 Number of load repetitions, N

0

0.0010

250000 500000 750000 1000000 Number of load repetitions, N

0.0010 Z-29 d = 35.3/50.5 cm

v

0.0008

Vertical strain, ε [-]

v

0.0006

0.0000 0

Vertical strain, ε [-]

Z-38 d = 20.7/35.3 cm

0.0008

0.0006 0.0004 0.0002 0.0000

Z-30 d = 50.5/65.5 cm

0.0008 0.0006 0.0004 0.0002 0.0000

0

250000 500000 750000 1000000 Number of load repetitions, N

0

250000 500000 750000 1000000 Number of load repetitions, N

1200

Horizontal strain, εt [-]

Horizontal strain, εt [-]

Figure 7. Induced vertical strain over four different depth ranges, 10.1–20.7 cm, 20.7–35.3 cm, 35.3–50.5 cm and 50.5–65.5 cm, as a function of load repetitions. The vertical dotted line indicates when the level of the ground water table was raised.

ASG-108 X

1000

ASG-114 X

800 600 400 200

800 ASG-107 Y ASG-113 Y

600 400 200 0

0 0

0

250000 500000 750000 1000000 Number of load repetitions, N

250000 500000 750000 1000000 Number of load repetitions, N

Figure 8. Induced a) longitudinal and b) transverse horizontal tension strain at the bottom of the asphalt layer as a function of load repetitions. The vertical dotted line indicates when the level of the ground water table was increased.

1106

where k1 and k2 are experimentally determined constants, p is the mean normal stress level of the loading and pa is a reference pressure, pa = 100 kPa. The accumulation of the vertical strain in the pavement materials is based on a best fit approach from repeated load triaxial testing. For all the unbound layers a simple three parameter work hardening model has been used (Tseng & Lytton, 1989) (2) where N stands for the number of load repetitions and ε0, ρ and β are regression parameters. For the bituminous bounded layers the evolution of the plastic strain was based on (3) where a1, a2 and a3 are model parameters and T is the temperature in °C of the layer. The loading amplitude in the laboratory is different from the loading in the field. Different load pulses in the laboratory are therefore scaled to match the real loading in the accelerated test. By dividing the pavement structure into thin layers the rutting development can now be evaluated as a function of load repetitions manifested on the surface (Erlingsson, 2007 & 2008). The material parameters used in the numerical analyses for the response of the structure are given in Table 2. They are based on plate load (PL) tests, falling weight deflectometer (FWD) tests during the construction of the structure, and an indirect tension test (ITT) of the bituminous layers. The parameters used for the permanent deformation predictions are further given in Table 3 and 4. They are based on repeated load triaxial testing in laboratory and values from the literature. No distinction is made in the parameters for the bound layers as to whether the structure was moist or wet as it is believed that even if some potential changes in their moisture content took place in the bound layers it would not affect their material behaviour. This is not the

Table 2.

Material parameters of the different layers used for the response analyses.

Layer Asphalt concrete Bituminous base Base course—Unbound Subbase—Unbound Subgrade

moist wet moist wet moist wet

Stiffness Mr [MPa]

Poisson’s ratio v [–]

5,000 5,000

0.35 0.35 0.35 0.35 0.35 0.35 0.35 0.35

180 120 140 100

k1 [–]

283.9 189.3

Table 3. Material parameters of the bound layers used for the permanent deformation prediction.

Layer

a1 ε rlab [–]

a2 [–]

a3 [–]

Asphalt concrete Bituminous base

0.004 0.004

0.7 0.7

0.4 0.4

1107

k2 [–]

0.4 0.4

Unit weight γ [kN/m3] 25.0 25.0 23.0 23.0 22.5 22.5 17.5 17.5

Table 4. Material parameters of the unbound layers used for the permanent deformation prediction.

Layer Base course

moist wet moist wet moist wet

Subbase Subgrade

ε0 ε rlab [–]

ρ [–]

β [–]

3.5 1.8 18 5.0 200 260

50,000 500,000 80,000 800,000 120,000 120,000

0.4 0.4 0.6 0.6 1.0 1.0

Stress σ [kPa]

Vertical strain ε [-] z

z

0

100

200

300

400

500

600

700

–0.001 0

800

10

10

20

20 Depth [cm]

Depth [cm]

0

30 40 50 60

Calculated, moist Calculated, wet

0.001

0.002

0.003

30 40 50

Measurements, wet

0.000

Calculations, moist Calculation, wet Measurements, moist

Measurements, moist

60

Measurement, wet

70

70

Figure 9. Vertical a) induced stress and b) strain as a function of depth for both moist and wet structure. The loading consisted of a dual wheel configuration with a wheel load of W = 60 kN and a tyre pressure p = 800 kPa. A profile under the centre of one of the tyres is shown.

case for the unbound layers where their permanent deformation characteristics are highly dependent on the moisture content, see Table 4. 6

RESPONSE ANALYSIS

Figure 9 shows the results of the calculated as well as the measured induced vertical stresses and strain of the pavement structures for both moist and wet states. Only the average measurements from three pressure cells are shown at each depth. Here the loading consisted of a dual wheel configuration with a wheel load of W = 60 kN and a tyre pressure p = 800 kPa. A profile under the centre of one of the tyres is shown. The figure shows quite good agreement between the measured and calculated stresses and strains at all three depths. As the asphalt concrete and the bituminous stabilised base were all together around 10 cm thick and quite stiff the vertical induced stresses decreased rapidly with depth and were around 100 kPa at the top of the unbound base and decrease approximately linearly thereafter with depth, see Figure 9a. The deviation between the measurements and the calculations in base course and subgrade were rather small. It is clear that both the measured and calculated stresses were slightly lower in the unbound layer for the wet state. The average value from the nine pressure cells gave 18% lower registrations for the wet state. This was probably a result of vertical upward transport of moisture from the groundwater table after it was introduced. The increased moisture content decreased the stiffness of the respective layer, hence lower stress was registered. Figure 9b shows the average measured vertical strains of all the strain sensors as well as the calculated strains. The numerical analysis with the nonlinear material parameters of the unbound base captured quite well the high measured strains there. For the subbase and the subgrade a linear elastic model seems to give reasonably good agreement with respect to 1108

the measurements. Higher strain values are registered for the wet state. The average increase of the ten strain sensors that gave trustworthy results resulted in about 57% higher registrations for the wet state. The vertical strains were therefore much more affected by the increased moisture than the vertical stresses. 7

RUTTING PREDICTION

Figure 10 shows the results of the rutting prediction as well as the measurement of accumulated permanent deformation, as a function of load repetition for the pavement structure. In the rutting prediction lateral wander has been taken into account by using the vertically induced strain at always the same location, although the loading wandered laterally, see Erlingsson (2007) for further details. Figure 10 shows the development of the permanent deformation for one million load repetitions in the uppermost 30 cm of the subgrade (Sg), the subbase (Sb) and base course (BC). Also the total rut as measured on the surface is shown. After 500,000 load repetitions water was pumped into the test pit until the groundwater table reached the level of 30 cm below the top of the subgrade (see Figure 1). As can been seen in Figure 10 all layers show accelerated development of permanent deformation after raising the groundwater table. The subgrade showed the largest increase. After 500,000 load repetitions the evolution of permanent deformation seems to have reached stagnation but after the water was introduced in the subgrade further permanent deformation started to develop. The subbase and the

2.0 Permanent deformation, δ [mm]

Permanent deformation, δ [mm]

10 Sg measurements

8

Sg calculations 6 4 2 0

Sb measurements Sb calculations

1.5

1.0

0.5

0.0 0

200000

400000

600000

800000 1000000

0

200000

Number of passes, N

600000

800000 1000000

15

2.0

Rut measurements

BC measurements

Permanent deformation, δ [mm]

Permanent deformation, δ [mm]

400000

Number of passes, N

BC calculations

1.5

1.0

0.5

0.0

Rut calculations 10

5

0 0

200000

400000

600000

800000 1000000

Number of passes, N

0

200000

400000

600000

800000 1000000

Number of passes, N

Figure 10 . Permanent deformation evolution as a function of the number of load repetitions. The loading consisted of a dual wheel configuration with a wheel load of W = 60 kN and a tyre pressure of p = 800 kPa. Sg = subgrade, Sb = subbase and BC = Base Course. One million load cycles are shown. After 500,000 repetitions water was gently pumped into the structure, raising the ground water table and the test continued.

1109

base course also show some increase in permanent deformation behaviour after water was introduced but not to the same extent as the subgrade. All the resilient and permanent strain measurements were carried out above the new groundwater table that was introduced. Thus the sensors were not directly saturated. However, increase in resilient and permanent strain was registered in all the unbound layers. This was probably due to the capillarity (suction) of the layer of the transport moisture suctioned vertically upward above the groundwater table. Hence, the water content of the unsaturated layers increased. Unfortunately no measurements of the water content were made in the structure so this has not been verified. The largest influence of the groundwater table was in the sandy subgrade. Both the subbase and the base course were much coarser and therefore had a much lower ability to attract water. They were therefore not affected to the same extent as the subgrade. 8

CONCLUSION

The paper presents results from an HVS testing of one pavement structure. Results regarding the response of the structure due to wheel loading are given as well as permanent deformation development as a function of the number of load repetitions. After 500,000 load repetitions water was introduced in the test pit and additional 500,000 load pulses were applied. This increased the development of the rutting in the unbound layers. The major findings from this study were: • HVS testing helps to increase our understanding of pavement behaviour under external heavy wheel loading. HVS tests can be used to help develop a mechanistic based pavement design method. • Numerical analysis where nonlinear base behaviour is modelled can predict the response behaviour of the structure with reasonable accuracy. • Rutting prediction using a simple power law function can give good agreement with actual measurements of permanent deformation development. • Raising the groundwater table increased both the resilient and the permanent strain of all unbound layers above the groundwater table in the pavement structure. • After ground water was introduced, the strength is partly regained as the test continues. This might be due to some additional compaction which was lost as the water was introduced. REFERENCES Erlingsson, S. 2007. Numerical modelling of thin pavements behaviour in accelerated HVS tests. Road Materials and Pavement Design, an International Journal. Vol. 8/4: 719–744. Erlingsson, S. 2008. Water influence on the performance of a pavement structure in a HVS test. Proceedings of the 3rd International Conference on Accelerated Pavement Testing, Madrid, Spain, 1–3 October, CD-ROM. Gomes-Correia, A., Hornych, P. & Akou, Y. 1999. Review of models and modeling of unbound granular materials. In: Gomes-Correia (ed.) Unbound granular materials—Laboratory testing, in-situ testing and modeling. A.A. Balkema, Rotterdam. May, R.W. & Witczak, M.W. 1981. Effective Granular Modulus to Model Pavement Response. Transportation Research Record 810, National Research Council, Washington D.C.: 1–9. Tseng, K.H. & Lytton, R.L. 1989. “Prediction of Permanent Deformation in flexible Pavement Materials,” Implication of Aggregates in Design, Construction, and Performance of Flexible Pavements, ASTM STP 1016. In: H.G. Schrauders and C.R. Marek, (Eds). American Society for Testing and Materials, Philadelphia: 154–172. Wiman, L.G. 2006. Accelerated Load Testing of Pavements—HVS Nordic tests at VTI Sweden 2003– 2004. VTI report 544A, Swedish National Road and Transport Research Institute, Linköping, Sweden. Wiman, L.G. & Erlingsson, S. 2008. Accelerated Pavement Testing by HVS—a Trans-national Testing Equipment. Transport Research Arena Europe 2008, Ljubljana, 21–24 April, CD-ROM.

1110

Reinforcement of structural layers

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Investigation of the effect of a polypropylene fiber material on the shear strength and CBR characteristics of high plasticity Ankara clay M. Mollamahmutoglu Bayburt University, Bayburt, Turkey

Y. Yilmaz Department of Civil Engineering, Kirikkale University, Kirikkale, Turkey

ABSTRACT: Nowadays, many soil improvement methods have evolved with different materials used. In this study, a series of laboratory tests are carried out to investigate the effect of a polypropylene fiber material on the shear strength and California Bearing Capacity (CBR) characteristics of high plasticity Ankara clay. First, geotechnical properties of Ankara clay are presented. Then, results of unconfined compressive strength, triaxial strength (CU type) and CBR tests conducted on the various polypropylene fiber/clay mixtures (0.1%, 0.2%, 0.3% and 0.4% by dry weight) are given. Samples were compacted at optimum moisture contents and maximum dry unit weights obtained from the standard Proctor compaction effort. Standard Proctor compaction tests and CBR tests revealed that percentage of 19 mm length F type polypropylene fiber did not influence much the optimum moisture content, maximum dry unit weight and CBR values. Unconfined compression tests showed that inclusion of fiber content increased the axial strain at failure. Moreover, consolidated-undrained (CU) triaxial test results exhibited that due to inclusion of 19 mm length F type polypropylene fiber, the cohesion intercept decreased slightly but the internal angle of friction increased considerably.

1

INTRODUCTION

The inclusion of randomly oriented fibers into a soil mass is one of the most interesting phenomena studied in soil improvement engineering. The reinforcement of cohesionless soils such as sand, silt or fly ash with randomly oriented fibers has been extensively studied (Gray & Ohashi 1983, Frietag 1986, Maher & Gray 1990, Al-Refeai 1991, Maher & Ho 1994, Michalowski & Zaho 1996, Consoli et al. 1998, Santoni et al. 2001). On the other hand, there are few attempts considering cohesive soils (Kumar et al. 2006, Cai et al. 2006). In addition, reinforcement of cohesive soils with randomly oriented fibers is incomplete and the findings are contradictory. It is therefore aimed to contribute to the literature in this perspective. The details of the experimental program and the findings are presented below.

2

ENGINEERING PROPERTIES OF MATERIALS TESTED

The particle size distribution curve of the Ankara clay is shown in Figure 1. The results of specific gravity, consistency limits and classification of Ankara clay and some technical properties of F type polypropylene fiber are given in Tables 1 and 2, respectively.

1113

100 90 80

Percentage smaller

70 60 50 40 30 20 10 0 0.001

0.01

0.1

1

10

Particle size, D (mm)

Figure 1.

The particle size distribution curve of the Ankara clay.

Table 1. Geotechnical properties of Ankara clay. Property

Value

Liquid limit, % Plasticity limit, % Specific gravity, Gs USCS Classification symbol

68.2 27.1 2.65 CH

Table 2.

Properties of the F type fiber used.

Property

Value

Content Appearance Standard Length (mm) Tensile strength (kPa) Young modulus (kPa) Elongation (%) Density (g/cm3)

100% pure polypropylene Fibril net shaped fiber ASTM C – 1116 – 1997 Type III 19 400 2600 15 2.91

14.5 Pure Clay Clay + 0.1% fiber Clay + 0.2% fiber Clay + 0.3% fiber

14.0

Dry unit weight, kN/m3

Clay + 0.4% fiber

13.5

13.0

12.5 15

20

25

30

35

40

Water content, w (%)

Figure 2.

3

Compaction curves of compacted the clay-fiber mixtures.

STANDARD PROCTOR TESTS

Prior to compaction, clay and fiber were mechanically mixed at 0.1%, 0.2%, 0.3% and 0.4% by weight of dry clay until homogenous mixtures were obtained and then a required amount of water was added and compacted properly. 1114

Table 3. Maximum dry density and optimum water content of the mixtures. Mixture

Maximum dry unit weight, (kN/m3)

Optimum water content (%)

Pure clay Clay + 0.1% fiber Clay + 0.2% fiber Clay + 0.3% fiber Clay + 0.4% fiber

14.04 14.32 14.25 13.57 13.47

27.86 28.36 27.85 28.41 27.81

Dry unit weights of the compacted samples are plotted against the corresponding water contents as shown in Figure 2. From Figure 2, it is clear that the optimum water content of compacted Ankara clay are not affected considerably by the inclusion of randomly oriented fiber material. On the other hand, as fiber content increases in the mixture the maximum dry unit weight exhibits decreasing tendency except for 0.1% and 0.2% fiber contents. Maximum dry unit weights and optimum water contents of the mixtures are also tabulated in Table 3. From Table 3, it is seen that the maximum dry unit weights range from 13.47 kN/m3 to 14.32 kN/m3 and the optimum water contents vary from 27.81% to 28.41%, respectively. 4

STRENGTH TESTS

The strength characteristics of fiber amended clay samples compacted at their relevant optimum moisture contents are investigated by means of unconfined compression tests at the shear rate of 1.2 mm/min and consolidated undrained (CU) triaxial tests at the shear rate of 0.8 mm/min. 4.1 Unconfined compressive strengths The unconfined compressive strengths of the fiber amended clay samples and their corresponding axial deformations at failure are given in Table 4. Table 4 shows that the unconfined compressive strength is increased by the inclusion of randomly oriented fiber material up to 0.2% fiber content. Further increase in fiber content beyond 0.2% decreases unconfined compressive strength. Moreover, it is clear from Table 4 that as the percentage of fiber content increases in the mixture, the axial strain where the failure of the specimens occurs are also increased. 4.2 Consolidated-Undrained (CU) shear strengths The effective internal friction angle and the cohesion intercept of the fiber amended clay samples obtained from Consolidated-Undrained (CU) triaxial tests are given in Table 5. Table 5 reveals that the inclusion of randomly oriented fiber material decreases cohesion intercept and increases internal friction angle dramatically. 5

CALIFORNIA BEARING RATIO (CBR) TESTS

California Bearing Ratio (CBR) tests were carried out according to Standard Test Method for CBR (California Bearing Ratio) of Laboratory-Compacted Soils (ASTM D 1883-99). The relationship between the fiber content and CBR values is given in Table 6. Table 6 shows that as the randomly oriented fiber content increases CBR value of the mixtures slightly decreases except for 0.1% fiber content. 1115

Table 4.

Unconfined compressive strengths of the compacted specimens.

Percentage of fiber in the mixture

Unconfined compressive strength, kPa

Axial strain at failure, %

0 0.1 0.2 0.3 0.4

178.3 170.5 209.9 155.2 190.3

4.2 5.6 5.8 6.8 6.7

Table 5. Consolidated-Undrained shear strength parameters of the compacted specimens.

Table 6. CBR values of the compacted specimens.

Percentage of fiber in the mixture

Percentage of fiber

CBR, %

c' (kPa)

φ' (º)

0 0.1 0.2 0.3 0.4

212 28 48 87 77

4.9 20.9 21.4 12.6 20.0

0 0.1 0.2 0.3 0.4

3.6 3.75 3.27 3.2 2.4

6

CONCLUSIONS

The following conclusions can be drawn from the study: 1. As the percentage of randomly oriented 19 mm length F type polypropylene fiber content in the mixture increased, the maximum dry unit weight decreased slightly. But, the optimum water contents of the mixtures were not affected remarkably by the fiber content. 2. As the percentage of fiber content increased, the axial strain at failure increased slightly. Moreover, inclusion of randomly oriented fiber material decreased cohesion intercept but increased internal friction angle dramatically. 3. Inclusion of fiber into Ankara clay did not considerably influence its CBR characteristics. In addition, as a general tendency, the fiber content decreased CBR value of the mixtures slightly. REFERENCES Al-Refeai, T.O. 1991. Behaviour of granular soils reinforced with discrete randomly oriented inclusions. Geotextiles and Geomembranes 10: 319–33. Cai, Y., Shi, B., Ng, C.W.W. & Tang, C-S. 2006. Effect of polypropylene fibre and lime admixture on engineering properties of clayey soil. Engineering Geology 87(3–4): 230–240. Consoli, N.C., Prietto, P.D.M. & Ulbrich, L.A. 1998. Influence of fiber and cement addition on behaviour of sandy soil. Journal of Geotechnical and Geoenvironmental Engineering (ASCE) 124: 1211–1214. Frietag, D.R. 1986. Soil randomly reinforced with fibers. Journal of Geotechnical Engineering (ASCE) 112: 823–5. Gray, D.H. & Ohashi, H. 1983. Mechanics of fiber reinforcement in sand. Journal of Geotechnical Engineering (ASCE) 109: 335–351. Kumar, A., Walia, B.S. & Mohan, J. 2006. Compressive strength of fiber reinforced highly compressible clay. Construction and Building Materials 20: 1063–1068. Maher, M.H. & Gray, D.H. 1990. Static response of sand reinforced with randomly distributed fibers. Journal of Geotechnical Engineering (ASCE) 116: 1661–1677. Maher, M.H. & Ho, Y.C. 1994. Mechanical properties of kaolinite/fiber soil composite. Journal of Geotechnical Engineering (ASCE) 120: 1381–93. Michalowski, R.L. & Zaho, A. 1996. Failure of fiber-reinforced granular soils. Journal of Geotechnical Engineering (ASCE) 122: 226–234. Santoni, R.L, Tingle, J.S. & Webster, S. 2001. Engineering properties of sand fiber mixtures for road construction. Journal of Geotechnical and Geoenvironmental Engineering (ASCE) 127: 258–268.

1116

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of geogrid displacement on subbase reinforcement using specially designed pullout test M.V. Akpinar & T. Sert Civil Engineering Department, Karadeniz Technical University, Trabzon, Turkey

ABSTRACT: The main objective of this study was to determine vertical and horizontal displacements of geogrid samples during pullout tests. Laboratory pullout tests were performed on 1.5 m long 1 m wide geogrid specimens using the same type of soils at similar moisture content and density. Vertical and horizontal displacements of aggregates and geogrids during the pull tests were computed by utilizing digital image processing. Sensors mounted above and below the geogrid samples were used to monitor displacements during the tests. The digital image process was conducted through the 300 mm long and 150 mm plexiglas windows opened on the sides of the special designed large scale pullout test device. A feature of the testing program is that displacements of geogrid samples at each connection of longitudinal and transverse ribs were captured and computed through non-contact measurements. The vertical and horizontal displacements of the geogrid ribs (transverse and longitudinal) were found to be very small. 1

GENERAL INFORMATION

The behavior of reinforced road embankment is largely affected by interaction mechanisms that occur between the reinforcement material and the backfill soil. The main function of the reinforcement element is to distribute stresses within the base/subbase in order to increase the stability of reinforced road subsoils. The geogrids correspond tensile strains as they transfer loads from unstable soil parts to stable soil. The distribution of stresses in a reinforced soil layer depend on the shear strength properties of the soil, the tensile properties of the grid element, and the stress transfer mechanism that takes place between soil and geogrid. 1.1 Geogrids and pullout test Geogrids are commonly used for retaining walls, highway subgrades, bases, subbases and railway ballasts. In order to enhance these structures’ economic life and reinforce the stability of soil layers, geogrid reinforcement materials are preferred. Geogrids are geosynthetic materials with apertures, which are characterized by a combination of transverse and longitudinal ribs. Geogrid apertures keep the aggregate materials together by preventing the lateral and horizontal movements. The aggregates in the pavement layers including the subgrade are exposed to lateral and vertical forces. This will in time cause lateral deformation in the soil layer and also settlement in the vertical direction. Pull-out tests have been commonly employed to study the soil–geogrid interactions under vertical and horizontal forces. Several research findings on the pull-out behavior of geogrids can be found in the literature (Jewell, 1980; Dyer, 1985; Palmeira & Milligan, 1989; Fannin & Raju, 1993; Alfaro et al., 1995; Lopes & Ladeira, 1996; Ochiai et al., 1996; Lopes & Lopes, 1999, Teixeira et al., 2007). The pullout interaction mechanisms between soil and geogrid reinforcements are complex. This is because the pullout resistance of geogrids includes two components: The interface shear resistance that takes place along the longitudinal elements and the passive resistance that develops against the front of transverse elements (Teixeira et al. 2007). 1117

Figure 1.

Aggregate-geogrid penetration. Table 1.

Pullout box dimensions from different articles. Pullout box dimensions

Literature name

Length (m)

Width (m)

Height (m)

Sugimoto et al. 2001 Sugimoto et al. 2003 Nernheim et al. 2004 Teixeira et al. 2007 Zornberg et al. 2005 Palmeira 2004 Moraci et al. 2006

0.68 0.68 1.50 1.50 1.52 1 1.70

0.3 0.3 0.6 0.7 0.61 1 0.6

0.625 0.625 0.6 0.48 0.28 1 0.68

Small dimensions of pullout test devices are not expected to apply to individual-rib pullout devices (Farrag et al. 1993). Comparatively large dimension requirements for pullout devices (e.g., in ASTM D6706) are needed to capture the interactions between the longitudinal and horizontal ribs when testing geogrid reinforcements. Such interactions are not present when testing individual ribs in small-scale pullout devices (Teixeira et al. 2007). Measuring the displacements along the geogrid provides an appropriate evaluation of the pullout resistance. Usually, displacements along the geogrid reinforcement length are measured using cables connected to the LVDTs mounted at the back of the box. These cables run inside the box and are in direct contact with the soil. Under vertical pressure load these wires may very well deform in the vertical direction thus resulting in error measurements. This study describes a technique to capture displacements and compute local displacements of typical geogrid soil reinforcement products using a digital image processing technique. A feature of the testing program is that displacements of geogrid samples at each connection of longitudinal and transverse ribs are captured and computed through noncontact measurements. 2

MATERIAL & METHOD

This study proposes a method to estimate displacement of geogrids used on pavement subbases based on the results of pullout tests. The pullout test device designed and constructed for this study, is the first in Turkey considering its dimensions (1 m long, 1 m wide and 0.80 m high). The apparatus is capable of performing both pullout and large scale direct shear tests due to its rail mechanism. The test apparatus is made of rolled steel plates, angles, and U-sections, bolted together to give the dimensions shown in Figure 2. Two hydraulic pistons are used to apply vertical and horizontal loads during the pullout mechanism. Vertical piston with its 0.8 m by 0.8 m steel plate 1118

lvdt

geogrid or geomembrane

horizantal load cell

Figure 2.

vertical load cell Plexiglas window

View of complete large-scale pullout test device.

20 cm

5 cm

5 cm diameter pressure gage

Vertical positioned load cell

Figure 3.

loading plate

strain gage

20 cm diameter pressure gage

Horizontal positioned load cell

Data logger

Measurement sensors and the data acquisition system that are used in the pullout tests.

applies the vertical pressure and the lateral piston pulls out the geogrid. The outer portion of the geogrid specimens are clamped into a flat type of clamp and serrated by bolts. For the pullout tests, 2 load cells with 20 ton force capacity, 8 small pressure cells with 1 MPa capacity, one large pressure cell with 2 MPa capacity, 8 strain gages with 0–5000 micro strain capacity, one vertical LVDT (100 cm) and two horizontal LVDT (50 cm) are used (see Figure 3). In order to transfer the data from measured sensors, 16 bit data acquisition systems are used. Each of these data acquisition systems have 8 channels summing to total 1119

of 24 channels. All instrumentation is monitored by a computer connected to three electronic datalogger which was programmed to scan the instrumentation at desired time intervals. The thickness of the soil layers above and below the reinforcement is 300 mm and 300 mm, respectively. The lower half of the pullout box is filled and compacted with subgrade soil material at every 100 mm level and the geogrid material is placed on top of it. After placement of the geogrid, the upper part of the box is filled and compacted with subbase at every 100 mm level. Figure 4 shows pressure cells and strain gage sensors mounted 50 mm above the geogrid sample. The subbase soil material’s gradation curve is shown in Figure 5. The curve gives the typical subbase aggregate gradations used in Turkish highways. A 200-mm diameter pressure gage is located on top of the compacted subbase layer. The vertical load is applied and as soon as the pressure gage data reaches the 35 kPa constant stress level, the lateral piston starts to pull out the geogrid sample at a rate of 1 mm/min. Tests are performed until rupture or a total horizontal displacement of 150 mm is achieved. Figure 6 shows the results obtained experimentally from large-scale pullout tests using 50 × 50 mm and 30 × 30 mm aperture size geogrids. Biaxial geogrid specimens are subjected to pullout test under constant rate of 0.5 mm/min strain. The pullout test device with plexiglas windows is the first application device found in the literature. Digital image method was conducted through the 300 mm long and 150 mm plexiglas windows opened on sides of the pullout test device (see Figures 7 and 8). Multiple targets were painted on the geogrid specimens at the intersection locations shown in Figure 8 (points 1, 2, 3, and 4).

Pressure gage Strain gage

Passing Percent (%P)

Figure 4.

5 cm diameter pressure cells and strain gage sensors mounted 5 cm above the geogrid sample.

100 90 80 70 60 50 40 30 20 10 0 0,0001

Subbase Material Gradation Subgrade Material Gradation

0,001

0,01

0,1

1

Sieve Size, log D (mm)

Figure 5.

Aggregate gradation curves.

1120

10

100

-9 -8 -7

Pullout Force (kN/m)

-6 -5 5×5 aperture size -4 3×3 aperture size

-3 -2 -1 0 1 0

-50

-100

-150

-200

-250

Displacement (mm)

Figure 6.

Two different displacement curves obtained from 5 × 5 cm and 3 × 3 aperture size geogrids.

Subbase

Geogird subgrade

geogrid Figure 7.

A view from the Plexiglas window before the test.

Y X Figure 8.

Initial and final images used to compute the displacements in X and Y directions.

1121

Table 2. Computed horizontal displacement values after testing.

Point No. 1 Point No. 2 Point No. 3 Point No. 4

Horizontal (mm)

Vertical (mm)

0.01 0.01 0.03 0.04

0.41 0.3 0.12 0.11

The intersections of the longitudinal and transverse ribs of the geogrid are painted with green color and the rest with white color. Initial and final images are taken at the beginning and the completion of pullout test, respectively. Coordinates of the transverse and longitudinal members are recorded. The geogrid intersections displacements are computed based on the initial and final marks on the green points. Some aggregates are painted to orange color to make the view much clear to understand where the soil particles are moving towards. Lateral and vertical scales at side of the plexiglas are used as a reference scale to measure horizontal and vertical displacements of the geogrids and aggregates. The high-resolution digital camera and data acquisition system are used to record specimen displacements of the soil and geogrid sample. A computer code is developed to track each connection of longitudinal and transverse ribs and soil particles in Y and X directions. The X and Y displacements of each point previously assigned (see Figure 8) are computed from selected reference coordinate system. 3

TEST RESULTS

The computed vertical and horizontal displacement values by utilizing the image processing are listed in Table 2. Preliminary test results show that vertical and horizontal displacements computed from the image processing gives very small displacement values indicating that under 35 kPa constant stress level the geogrid samples will remain in the soil layer. The geogrid sample is considered to be fully bonded to both soil layers to prevent slip at the geogrid/soil interface. The design coefficient of interaction against direct sliding is expected to be high. No ruptures are observed on the samples after the pullout test completion. The concentrated local forces normal to the geogrid plane are insignficant under 35 kPa constant stress level. Several studies have used tell-tail strings to measure the internal displacements along the reinforcement. Displacements along the length of the specimens are monitored using telltails connected to the LVDTs at the back of the pullout box. At least three “tell-tail” steel wires are connected along the longitudinal or transverse sections of the geogrid specimen at the pullout box end, center, and few cm apart from the edge of the sleeves. The displacements of these metal wires are measured during the pullout test to determine the distribution of displacement along the geogrid specimen length. It is important to point out that assuming the geogrid moves in only horizontal direction along the reinforcement length may be incorrect. As several other important aspects such as non uniform soil compaction and variations in the vertical load distribution may significantly require the geogrid to deform out of the horizontal plane. Under vertical pressure these wires may very well deform in the vertical direction thus giving error measurements. Figure 7 shows the shape of a geogrid sample undergoing deformation during the pullout test. The geogrid sample is not anymore positioned on horizontal plane due to the fact that vertical load is not distributed homogenous throughout the box. The vertical displacement is almost zero at point 4 and increases gradually to the maximum at the center point 1. 4

CONCLUSIONS

This paper described a noncontact measurement technique to capture displacements and compute local displacements of typical geogrid soil reinforcement products using a 1122

digital image processing technique. It is believed that the image processing can be used as an alternative technique for obtaining vertical and horizontal displacement values of the geogrids inside the pullout box. This technique will be very effective in studying the deformation behavior of geogrid reinforced structures. The test results indicated that the horizontal displacement of the geogrids in pullout test were negligible. ACKNOWLEDGEMENTS This study is funded by the TÜBİTAK project no: 106M423 and Karadeniz Technical University. We also thank Eyüp Gedikli for his help on the digital image processing. REFERENCES Alfaro, M.C. et al. 1995. Pullout interaction mechanism of geogrid strip reinforcement. Geosynthetics International 24, pp. 679–698. Dyer, M.R., 1985. Observations of the stress distribution in crushed glass with applications to soil reinforcement. D.Phil. Thesis, University of Oxford, Oxford, UK. Fannin, R.J. et al. 1993. On the pull-out resistance of geosynthetics. Canadian Geotechnical Journal 303, pp. 409–417. Jewell, R.A. 1996. Soil reinforcement with geotextiles. Ciria Special Publication 123, Thomas Telford Ltd., UK, 332 p. Lopes, M.L. et al. 1996. Role of specimen geometry, soil height and sleeve length on the pull-out behaviour of geogrids. Geosynthetics International 36, pp. 701–719. Lopes, M.J. et al. 1999. Soil-geosynthetic interaction—influence of soil particle size and geosynthetic structure. Geosynthetics International 64, pp. 261–282. Moraci, N. 2006. Factors affecting the pullout behaviour of extruded geogrids embedded in a compacted granular soil. Geotextiles and Geomembranes 24 (2006) 220–242. Nernheim A. et al. 2004. Cyclic pullout tests on geogrid. International Conference on Geotechnical Engineering. Sharjah- United Arab Emirates. Ochiai, H. et al. 1996. The pull-out resistance of geogrids in reinforced soil. Geotextiles and Geomembranes 141, pp. 19–42. Palmeira, E.M. et al. 1989. Scale and other factors affecting the results of pull-out tests of grids buried in sand. Geotechnique 393, pp. 511–524. Palmeira, E. M. 2004. Bearing force mobilisation in pull-out tests on geogrids. Geotextiles and Geomembranes 22 (2004) 481–509. Sugimoto, M. et al. 2001. Influence of rigid and flexible face on geogrid pullout tests. Geotextiles and Geomembranes 19 (2001) 257–277. Sugimoto, M. et al. 2003. Pullout Behavior of Geogrid by Test and Numerical Analysis. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 129, No. 4. Teixeira, S.H.C. 2007. Pullout Resistance of Individual Longitudinal and Transverse Geogrid Ribs. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 133, No. 1. Zornberg, J.G. 2005. Pullout of Geosynthetic Reinforcement with In-plane Drainage Capability. GRI-18 Geosynthetics Research and Development in Progress.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Performance of flexible pavements reinforced with steel fabric S.F. Said, H. Carlsson & H. Hakim VTI, Swedish National Road and Transport Research Institute, Linköping, Sweden

ABSTRACT: This paper describes the rehabilitation procedure of an old cracked asphalt pavement located on the E6 motorway in the west of Sweden. A trial was performed to design the road structure with steel fabric reinforcement in the asphalt concrete. Three fullscale 100-meter test sections were built. Two test sections were reinforced with steel fabrics and one section was left without reinforcement as a reference road section. These sections were instrumented with strain gauges. The sections were tested by means of deflection measurements with Falling Weight Deflectometer, strain measurements at the bottom surface of the overlays, strain on the steel bars, unevenness and rut depth measurements, and manual distress surveys. The objective is to evaluate the performance of rehabilitated road structures reinforced with steel fabric. Strain measurements at the bottom surface of the asphalt layers show lower strains in the reinforced test sections than in the reference section without reinforcement. Performance evaluation and conclusions after seven years of traffic are presented in this paper. 1

BACKGROUND

A highway road section, 800 m long, on the E6 motorway at Ljungskile in the southwest of Sweden was seriously damaged due to its low bearing capacity. Longitudinal and transversal cracks were frequently observed. Alligator cracks in the wheel paths were also observed (Figure 1). There were also rutting in the wheel paths. This section was opened to traffic in 1991. The AADT is about 7000, of which heavy vehicles account for about 14 percent. Already after 5 years the road section had longitudinal cracks in the wheel paths (Jansson 1996). This type and frequency of damage were not expected until after 20 years. In a damage investigation, different rehabilitation options were proposed, such as complete reconstruction or milling, steel reinforcement, and new bituminous layers. After thorough consideration, the steel reinforcement alternative was chosen for economic reasons. In order to increase the bearing capacity of the pavements it was decided that the most reasonable alternative is placement of steel net at the bottom of the new layers. This should reduce the principal stresses and the vertical deformations and result in an increase in bearing capacity and longer service life of the road section. The purpose of this work is to evaluate the possible increase in the bearing capacity of the section by means of FWD measurements and measurement of the strain at the bottom of the newly laid layers and evaluation of the development of deterioration over time. 2

EXISTING ROAD STRUCTURE

In 2000 the road was rehabilitated by milling away the two upper layers of the existing structure that consisted of porous asphalt and dense asphalt concrete. After the milling operation, levelling layers were placed on the road and two new layers, a binder course and

1125

Figure 1.

Table 1. Layer

Damages on the E6 motorway at Ljungskile.

Structure of the road section with rehabilitation measures in chronological order. Thickness, mm

Porous asphalt, HABD16/B85 45 Binder, ABb22/B85 50 Reinforcement #100 mm ø6 mm Levelling Porous asphalt, HABD16/B85 45 Dense asphalt concrete, HABT12/B85 35 Roadbase AG25/B180 50 Roadbase AG25/B180 50 Unbound roadbase 70 Sub-base 650 Subgrade silty clay

Year of construction 2000 2000 2000 2000 1991 1991 1991 1990 1990 1990

Comments

On sections 2 and 3 Thickness varied Milled away in 2000 Milled away in 2000

a porous asphalt wearing course, were also laid. Table 1 shows the structure of the road section and the rehabilitation measures in chronological order. The old remaining roadbase (AG25/B180) was deteriorated and of poor quality with extensive cracking. 3

CONSTRUCTION OF TEST SECTIONS

Three 100-meter sections were chosen as test sections. One test section was reinforced with steel fabrics in both lanes, one test section was reinforced only in the slow traffic lane, and one section was constructed without reinforcement as a reference road section. The test sections during construction are shown in Figure 2. The steel mesh was installed successfully without any problem during construction. Figure 3 shows the steel reinforcement under construction and as can be seen from the photo, the steel mesh is located at the bottom of the levelling layer. Figure 4 shows the structures of the road sections according to cored samples. It is evident that the levelling layer is much thicker than intended. The results of the cores indicated that the thickness of the asphalt layers is thinner (on average approximately 20 mm) on section 1 than on sections 2 and 3. The test sections are instrumented with strain gauges both in the asphalt layer and on the steel bars. The asphalt strain 1126

Figure 2.

Steel reinforcement placed on the test section.

Figure 3.

Steel mesh and levelling layer. Test Sections 1:1

1:2

1:3

2:2

2:3

2:4

3:2

3:3

3:4

0

Porous asphalt 50

Binder course

Depth (mm)

100

Reinforcement Levelling

150

Strain gauge Old base course

200

250

300

Figure 4. Structures of the test sections 1, 2, and 3, illustrating placement of steel reinforcement and strain gauges in the structures.

1127

gauges used are of the H-shape type and manufactured by Dynatest with three gauges per test section located in the right wheel path. Further details of the test sections have been reported by Said et al. (2002). 4

FIELD MEASUREMENTS

In order to follow up the deterioration in the field, measurements of deflection by Falling Weight Deflectometer (FWD), strain measurements, and measurements of rut depth are performed periodically, together with manual distress inspection. 4.1 Falling Weight Deflectometer (FWD) The FWD measurements have been used to evaluate the bearing capacity of the road structures. The FWD measurements were performed with a KUAB 50 kN FWD equipment. The measurements were made in the right wheel path. The results of the measurements have been analyzed according to the Swedish Road Administration’s Standard Method (VV 114:2000), all with the purpose of making a comparison between the test sections. From deflection basins, represented by average deflection basins, see Figure 5, it is concluded that in this case it is not possible to find significant differences between the test sections based on FWD measurements. The influence of the steel reinforcement on the FWD deflections is too small compared to the influence of the stiffness of the asphalt layers, unbound pavement layers, and subgrade to be detected by FWD measurement performed in this case. To investigate the steel mesh’s influence on FWD deflection, the FWD measurement program probably needs to be extended, for example with measurements at higher temperatures or higher loads. However, further research is needed to understand FWD results where steel reinforcement is present in pavement. 4.2 Strain measurements Strain measurements were performed at the same time as the FWD measurements. The loading was done using the FWD equipment at three loading levels: 30 kN, 50 kN and 63 kN. Figure 6 shows an example of strain signals at about 10°C under a loading of 50 kN.

Distance from loading center (mm)

0

200

400

600

800

1000

1200

Deflection (µm)

100 Sec. 1

200 Sec. 2

300 Sec. 3

400 500 Figure 5.

Average deflection basins from FWD measurements in 2007.

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Strain (με)

Asphalt strain gauges are located on the milled surface just below the levelling layers. After placement of the levelling, binder and surface layer, the strain gauges end up at different depths from the surface, as shown in Figure 4. The strain gauges are located at a depth of 150 mm and 170 mm in the reference and reinforced sections respectively. Placement of strain gauges at different depths complicates the comparison between test sections and the evaluation of the reinforced pavement. Figure 7 shows the strain measurements at 50 kN load performed in autumn (October) when temperatures are around 10°C. The first measurements were made in October 2001 after construction of the road test. The strains are between 15 and 45 microstrain. It should be mentioned that these strain levels are relatively small. The lowest values are for reinforced section No. 3 and the highest values are for the reference section, No. 1. Figure 7 shows strain development until 2007. There were no measurements the years 2004 and 2006. Strain measurements vary to some extent within

Section 1

50 45 40 35 30 25 20 15 10 5 0

Section 2 Asphalt Steel

0.0

0.1

0.2

0.3

0.0

0.1

0.2

0.3

Time (Seconds) Figure 6.

Examples of strain gauge signals from sections 1 and 2 in the field loaded by FWD.

160 140

Sec.1:1 Sec.1:2

120

Strain (μm/m)

Sec.1:3 100

Sec.2:2 Sec.2:3

80

Sec.2:4

60

Sec.3:2

40

Sec.3:3

20

Sec.3:4

0 2001

2002

2003

12°C

8°C

13°C

2004

2005 10°C

Year

Figure 7.

Development of measured strains in the test sections.

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2006

2007 15°C

each year’s measurements (same temperature), in particular with regard to the reference section. Section 1:3 shows significantly lower strain than sections 1:1 and 1:2. Two of the strain gauges in the reference sections have shown a significant increase in strain up until 2003. Strain gauge 1:3 (sec.1) shows a reduction in strain level indicating the probable formation of cracks. The third strain gauge in the reference section and two of the strain gauges in the one-lane reinforced section (No 2) showed accelerated development in strain level after 2005. However, the development in strain levels in the two-lane reinforced section (No 3) is moderate. It is evident from these measurements that the reinforced sections show significantly lower strain levels than the reference section, despite the strain gauges in the reinforced sections being located 20 mm deeper than in the reference section. But it is also worth mentioning that the thickness of the new bituminous layers in the test sections turned out to be different due to unexpectedly thick levelling layers in the reinforced sections. Figure 8 shows the calculated horizontal strains in the reference section using BISAR. The strain level at 170 mm is about 25 percent larger than the strain level at a depth of 150 mm from the pavement surface. Conclusions from these measurements are that the measured strains show lower strain values for the reinforced structures, which indicate longer fatigue for structures with steel fabrics. 4.3 Rut depth A low speed laser profilometer called Primal, illustrated in Figure 9, was used to measure transverse profiles of the test sections. The profilometer produces highly accurate measurements of the transverse surface profile at intervals of 2 cm with an accuracy of 0.1 mm. The first measurements were performed in August 2000 before the road was opened to traffic. Figure 10 shows the average rut depth per section based on both wheel paths. The presented rut depths are the total rut depths measured on the surface and it is not possible to determine how much of the rut is generated by asphalt layer, unbound pavement layer, and subgrade, respectively. Figure 11, representative transverse profiles are presented and no indication of flow rutting can be seen in the shape of the profiles. This means that the rutting mainly depends on deformation/compaction of the layers. It is concluded from Figure 10 that rut development is smaller in the structures with the reinforced pavements than in the reference structure.

Horizontal strain (μm/m) –150

–100

–50

0

50

0,00

0,05

Depth (m)

0,10

0,15

0,20

0,25

0,30

Figure 8.

Calculated strain profile of the reference test section using BISAR.

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100

150

Figure 9.

Low speed laser profilometer on the E6 in Ljungskile.

Propagation of rut depth (mm)

12 10 Sec.1 Reference Sec.2 Reinforced L1

8

Sec.3 Reinforced L1-2

6 4 2 0 2000

2001

2002

2003

2004

2005

2006

2007

2008

Year

Figure 10.

Development of average rut depth per section.

10

5

0

Profile (mm)

0

500

1000

1500

2000

2500

3500

4000 Section 1 Section 2 Section 3

–5

–10

–15

–20 Cross profile (mm)

Figure 11.

3000

Representative transverse profiles per section.

1131

5

CONCLUSIONS

The comparison of deterioration between a reinforced and a traditionally constructed road structure has been presented above. The following can be concluded: • Results from Falling Weight Deflectometer measurements have not in this case been able to show any significant differences between the test sections with or without steel reinforcement. • Measured strains in the field show lower strain values for the reinforced structures • Rut development is smaller in structures with the reinforced pavements than in the traditionally constructed road structure. • Referring to the strain levels and rut depth developments, the service life for the reinforced structure will be prolonged significantly in the studied case. ACKNOWLEDGEMENT The construction of the test road sections was financed by The Swedish Road Administration. The recent evaluation work is part of a joint project called SPENS (Sustainable Pavements for European New Member States). The project is financed by the European Commission and national funds from countries of the participant partners. REFERENCES Jansson H. 1996. Falling Weight Deflectometer measurements at E6 Ljungskile. VTI utlåtande No. 626 The Swedish Road and Transport Research Institute. In Swedish. Linköping: Sweden. Design Manual 2006. ATB VÄG The Swedish Road Administration: In Swedish. Said S.F., Zarghampour H., Johansson S., Hakim H. and Carlsson H. 2002. Evaluation of pavement structure reinforced with steel fabrics. Proceeding of the 6th International conference on the Bearing Capacity of Roads and Railways and Airfields, Lisbon: Portugal.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of asphalt road pavement rehabilitation using steel mesh reinforcement J.M.C. Neves IST Technical University of Lisbon, Lisbon, Portugal

A.R.D. Alves EP S.A., Castelo Branco, Portugal

ABSTRACT: The aim of this paper is to illustrate the benefits of steel reinforcement in asphalt pavements, related to the reduction of thickness overlay (economic advantage) and to the increasing of road bearing capacity (technical advantage). The study is based on fullscale test sections conducted on an asphalt road, reinforced in the interface of the bituminous layers by a range of steel mesh types. The paper describes the pavement structure design, construction methodology and plan instrumentation with strain gauges. The efficiency of the general bearing capacity increase of test sections by the use of steel reinforcement was demonstrated by deflection and strain measurements under Falling Weight Deflectometer tests. Linear elastic modelling of the test sections’ behaviour was used in order to validate the effect of reinforcement. The main conclusions of the paper deal with the advantages and disadvantages identified for this technique in experimental work. Practical recommendations are also made for design, construction, monitoring and modelling. 1

INTRODUCTION

Reinforcement techniques have an important role in pavement construction and maintenance and can pursue different purposes. In general, it could be said that these techniques have technical, economic and environmental objectives. One of the techniques is steel mesh reinforcement. The basic principle of this technique is inserting or laying the steel meshes in the interface of bituminous layers, either during the maintenance of existing pavements or during the construction of new roads. The main purposes considered for this reinforcement technique are to increase the bearing capacity and to avoid the rutting of the pavement. Several studies concerning steel reinforcement, supported with important experimental work, including either laboratorial tests or instrumentation and monitoring of test sections, have been developed in the last years. However, the study presented in this paper has intended the better understanding of this reinforcement technique for the Portuguese materials (steel and pavement materials) and execution conditions. The project financed by the European Commission—REFLEX: “Reinforcement of flexible road structures with steel fabrics to prolong service life,”—was developed from 1999 to 2002 with the main purpose of studying the performance of new and rehabilitated asphalt pavements reinforced with steel fabrics (Lechne, 2005). This research was focusing not only on the bearing capacity but also on resistance against thermal cracking, reflective cracking, plastic deformations and flow rutting. Laboratorial tests and measurements performed in test sections have been conducted in order to study design and construction techniques more adapted to this reinforcement technique. Measurements performed during the construction have shown the sensitivity of this technology given by the fundamental material properties of asphalt and steel.

1133

More recently (2001–2005), a study concerning COST 348—REIPAS: “Reinforcement of Pavements with Steel Meshes and Geosynthetics”—has achieved design approaches regarding either the utilization of geosynthetics or steel grids (COST 2004, Rathmayer et al. 2005). Korkiala-Tanttu & Rathmayer (2005) have concluded from laboratory and in situ tests that pavement rutting was reduced by the use of steel grids in bitumen bound layers or unbound granular base. Those researchers have also achieved a more efficient reinforcement in the cases where the bearing capacity of the pavement is low. Despites it is recognized that the steel reinforcement for bearing capacity purposes is more efficient in lower pavement layers, such as subgrade or sub-base layers, this paper has aimed to evaluate this structural effect when upper bituminous layers are used for this type of reinforcement. This procedure could take more advantage in the case of pavement’s rehabilitation. Falling Weight Deflectometer (FWD) is a current device used in Portugal for in situ structural evaluation of existing pavements and it is also useful as an important quality control tool in the case of road construction and maintenance. This test could not be a suitable measurement tool to quantify the improvement performance of steel reinforcement (Korkiala-Tanttu & Rathmayer 2005). In general, design of reinforced pavements using several techniques, including steel meshes, is often supported by theoretical models. Multy-layer theory is a current method used in order to check reinforcement performance. Equivalent stiffness is currently used in order to considerate the presence of steel meshed in the reinforced layer. Nevertheless, more advanced modelling, as the finite element method, could be desired in this case and for further investigations (Rathmayer et al. 2005). This paper presents some results of a research study, based on an experimental flexible pavement, developed by the “Instituto Superior Técnico” (IST) of the Technical University of Lisbon (Alves 2007). The full-scale experimental pavement was located near Vila de Rei, Portugal. During the construction of the test sections in 2005, strain gauges were also installed in the bituminous layers and the unbound granular material of the subbase layer. The study comprised the evaluation of bearing capacity by in situ FWD tests. The design and construction phases of test sections are summarized. The monitoring of the test sections’ behaviour during in situ load tests has demonstrated the benefits of the incorporation of steel meshes in terms of bearing capacity. A theoretical study based on the structural analysis of the experimental pavement, using a simple linear elastic modelling, has demonstrated the major influence of the thickness of the bituminous layers and the steel mass by unit area on reinforcement efficiency.

2

CASE STUDY DESCRIPTION

The evaluation of the benefits of steel meshes for bearing capacity was supported by an experimental case study performed on a flexible pavement of a rehabilitated rural road, located at Vila de Rei, in the centre of Portugal. The structure of the road pavement was composed of wear and binder bituminous layers, a subbase layer of unbound granular material and subgrade soil. The unbound granular of the subbase layer was composed of crushed limestone (0/25). Asphalt concrete of both bituminous layers was composed of crushed aggregates, sand and filler with a 50/70 grade bitumen binder. An adequate lenght of the experimental road was chosen for the construction of test pavements, characterized by different thicknesses of bituminous layers and types of steel meshes. Similar materials and thicknesses were provided for the subbase and subgrade layers. The steel meshes selected for this experimental study are shown in Table 1. The meshes were 100 × 100 mm square. The steel resistance class used in their manufacture is A500 (Fe360). The mesh panels were rectangular, with dimensions of 6.00 × 2.40 m2. 1134

Table 1.

Properties of steel meshes.

Type

Diameter of steel bar (mm)

Mass by unit area (kg/m2)

AQ-30 AQ-38 AQ-50

3.0 3.8 5.0

1.10 1.77 3.08

G4, M4, P4, S4

G6, M6, P6, S6

G8, M8, P8, S8 G10, M10, P10, S10

28 m

28 m

28 m

4 cm

6 cm

8 cm

10 cm

Binder layer (MB)

15 cm

15 cm

Subbase (AGE)

28 m

4 cm

Wearing course (BB)

15 cm

15 cm

Subgrade

a) Pavement structures of the test sections G4, G6, G8, G10

M4, M6, M8, M10

P4, P6, P8, P10

S4, S6, S8, S10

7.0 m

7.0 m

7.0 m

7.0 m

AQ-50

AQ-38

AQ-30

(no steel mesh)

3.5 m

b) General view of steel mesh placement in the test sub-sections Figure 1.

Design of the test sections.

A total of four test sections were constructed. Figure 1a shows the pavement structures of these test sections where it could be observed that binder layer thickness was the only variable characteristic related to pavement geometry. Each test section, with a total length of 28 m, was subdivided into four other subsections, 7 m in length (Figure 1b): three sub-sections were reinforced with different steel meshes, as shown in Table 1; one sub-section was constructed without a steel mesh, as a reference. As already mentioned, a total of 16 test sections were constructed: – – – –

4 sub-sections reinforced with AQ-50 (G4, G6, G8, G10) steel mesh; 4 sub-sections reinforced with AQ-38 (M4, M6, M8, M10) steel mesh; 4 sub-sections reinforced with AQ-30 (P4, P6, P8, P10) steel mesh; 4 sub-sections without steel meshes (S4, S6, S8, S10).

In each test section, the steel meshes were placed in the interface of the binder layer and wearing course, as shown in Figure 2a. Figure 2b shows a detail of the steel meshes’ setting on the surface of the subjacent bituminous layer. 1135

a) General view of steel mesh placement

b) Detail of the steel mesh setting system Figure 2.

Construction of test sections.

Test sub-sections S6, S10, G6 and G10 were instrumented with strain gauges manufactured by Kyowa of type KFL-30-350-C1-11, in order to measure longitudinal and transversal strains in binder and subbase layers: – Bituminous strain gauges to measure the horizontal strains at the bottom of the binder layer. Some of the gauges were placed to measure strain in the longitudinal direction, and other gauges placed to measure strain in the transverse direction. – Unbound strain gauges to measure vertical strains. They were located at the top of the subbase layer. All the strain gauges were located in the centre of the instrumented test sub-sections (Alves 2007). The plan instrumentation adopted in this work was based on the experience obtained in other full-scale experimental pavements constructed in Portugal (Neves & Gomes-Correia 2002). The properties of all the construction procedures and pavement materials were in accordance with the Portuguese technical standards (EP 1998). More details concerning the construction of the test sections are described by Alves (2007). 1136

3

EVALUATION OF BEARING CAPACITY OF TEST SECTIONS

Physical and mechanical laboratory tests were performed in general with pavement materials used in the test sections, in order to provide an adequate quality control. In the case of bituminous materials, test specimens were obtained from cores extracted in the S10 test section. With these specimens, the thickness of pavement layers was controlled and NAT—Nottingham Asphalt Tester—was used to evaluate the stiffness of bituminous mixtures. Tests were carried out at a temperature of 20ºC and the average values obtained for the wearing and binder stiffness were 3500 MPa and 6500 MPa, respectively. In order to evaluate the bearing capacity of the experimental sections, in situ FWD tests were carried out. The equipment used in these tests was a DYNATEST model 8081, able to apply a nominal peak load of 65 kN on a circular plate of 30 cm diameter. Deflections were measured by geophones placed at a distance of 0, 300, 450, 600, 900, 1200, 1500, 1800, 2100 mm from the centre of the test plate. An example of the bearing capacity increase observed during FWD tests is shown in Figure 3, in the case of sub-sections G8, M8, P8 and S8 (8 cm of binder layer thickness). The values represented in this figure are the mean values obtained from the test results. The general decrease of deflections is more evident for D1 deflections (plate centre). This behaviour is directly related to bituminous reinforcement due to the presence of steel mesh in the wear and binder layers’ interface. In fact, a certain scattering of FWD results was observed, mainly in the case of other deflections. However, the back-analysis of the FWD measurements has confirmed that the behaviour detected was due to the physical and mechanical heterogeneities of subgrade soil. Table 2 shows the linear elastic modulus obtained from FWD back-analysis achieved for all test subsections. It could be observed that there is an important heterogeneity of subgrade values that unfortunately could not be eliminated during the construction of the test sections. During some tests, strains were measured by the gauges, simultaneously with the application of the load test to the pavement. Loads were applied at the centre of the gauges installed in the experimental pavement structures. These measurements were useful for achieving a better quality of FWD back-analysis.

500

D1 (0 mm)

400

Deflexions (µm)

D2 (300 mm) D3 (450 mm) 300

D4 (600 mm) D5 (900 mm) D6 (1200 mm)

200

D7 (1500 mm) D8 (1800 mm) 100

D9 (2100 mm)

0 S8

P8

M8

Test section

Figure 3.

Example of FWD results.

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G8

Table 2.

FWD back-analysis. Linear Elastic Modulus (MPa)

Test section

Wear layer

Binder layer

Subbase

Subgrade

G10 G8 G6 G4

3200

2700

500 600 560 620

150 200 70 120

M10 M8 M6 M4

2400

2700

500 510 490 600

180 200 100 300

P10 P8 P6 P4

1900

2700

500 540 670 650

200 170 140 200

S10 S8 S6 S4

1200

2700

500 570 560 550

200 170 70 140

The temperatures of the air and of the pavement surface were always measured during

in situ load tests and they were considered in the FWD back-analysis. 4

ANALYSIS OF STRUCTURAL BEHAVIOUR

The numerical analysis of the structural behaviour of the test sections during the in situ tests was performed by the linear elastic multi-layer methodology. The ELSYM5 code was used in this analysis. A parametric study was conducted in order to evaluate the influence of the type of steel mesh and pavement structure on the reinforcement of the bearing capacity. The effect of the reinforcement placed in the interface of the wearing course and the binder layer was simulated by a single bituminous layer characterized by an equivalent thickness and an equivalent stiffness. In the case of the type of steel mesh studied, the steel mass by unit area was used as a variable. The increase of the bearing capacity due to the steel reinforcement was measured by the variation of the equivalent stiffness of the bituminous layers, i.e. by the non-dimensional quotient between equivalent stiffness with steel mesh (reinforced pavement) and equivalent stiffness without steel mesh (non-reinforced pavement). Figure 4a shows an increase of the bearing capacity due to the steel mass by unit area. This behaviour was achieved for all the test sections with different equivalent layer thickness: 8, 10, 12 and 14 cm. This effect is more accurate in the case when a steel mesh with a higher mass by unit area is used and for pavements characterized by thin equivalent bituminous layer. The effect of the pavement structure on the bearing capacity is shown in Figure 4b. This figure shows that a less important reinforcement of the pavement is achieved for the structures with higher equivalent layer thickness. A parametric study always confirmed, as expected, an increase of the bearing capacity, more important in the case of thin bituminous layers of the pavement structure and if a steel mesh is used in the reinforcement with a high value of steel mass by unit area. 1138

Equivalent stiffness with steel mesh/ Equivalent stiffness without steel mesh

1.6 1.5 1.4

8 cm 10 cm

1.3

12 cm 14 cm

1.2 1.1 1.0 0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

2

Steel mass by unit area (kg/m )

Equivalent stiffness with steel mesh/ Equivalent stiffness without steel mesh

a) Influence of the type of steel mesh 1.6 1.5 1.4 3.08 kg/m2 (AQ-50) 1.77 kg/m2 (AQ-38)

1.3

1.10 kg/m2 (AQ-30) 1.2 1.1 1.0 8

10

12

14

Equivalent thickness (cm)

b) Influence of the thickness of bituminous layers Figure 4. capacity.

Influence of the type of steel mesh and of the thickness of bituminous layers on the bearing

A theoretical and parametric study of the benefit of steel reinforcement for the resistance of the pavement to rut depth and fatigue cracking was also performed. By the use of Shell methodology for the two criteria, it was concluded that an increase of the number of equivalent standard axle load of 130 kN (Ndim) is always achieved. The variation of equivalent standard axle loads of traffic supported by the test sections with respect to the fatigue criteria is shown in Figure 5. The same conclusion was obtained in the parametric study related to the rut depth criteria. However, the effect of reinforcement is more important in the case of fatigue criteria and it is more sensitive to the steel mass (Figure 5). 1139

1.80 1.70 1.60 1.50 1.40 Increase of Ndim 1.30 1.20 1.10

3.0

2.5

2.0 1.5

Steel mass by unit area (kg/m2)

1.0 0.5 0.0 14

13

12

11

10

9

1.00 8

Bituminous layer thickness (cm)

Figure 5. Variation of equivalent standard axle loads of traffic supported by the test sections with respect to the fatigue criteria.

5

CONCLUSIONS AND RECOMMENDATIONS

This paper concerns the evaluation of asphalt road pavement rehabilitation using steel mesh reinforcement. The theoretical and practical knowledge presented are based on a case study of pavement rehabilitation. The main aspects of the design, construction, instrumentation and behaviour monitoring are described in order to demonstrate the influence of the steel mesh on the bearing capacity of the test sections and on the resistance of the bituminous mixtures to fatigue cracking. In general, the reinforcement by the use of steel meshes had positive effects on the increase of the bearing capacity, taking into account certain factors, such as the type of the steel mesh and the thickness of the bituminous layers. During the construction of the test sections, the main difficulties were related to the setting system of the steel meshes on the subjacent bituminous layer, because the work traffic tends to pull out the panels. The system adopted in this experimental study was adequate. Instead, more reliable methods should be investigated. The main conclusions of the paper, from analysis of structural behaviour of the test sections during the in situ load tests, can be summarized as follows: – FWD tests have demonstrated the increase of the bearing capacity in the case of the test sections reinforced. – The influence of the steel reinforcement on the bearing capacity of the test sections depended on the type of the steel mesh and on the thickness of the bituminous layers. Evaluation of the structural behaviour of the test sections during the FWD tests demonstrated that a greater benefit is achieved in the case of pavements with thin bituminous layers and when a steel mesh with higher mass by unit area is used. – Resistance to fatigue cracking and rut depth can be expected to increase when reinforcement is provided. This effect seems to be more important in the case of fatigue criteria and it is more sensitive to the steel mass value. A more realistic numerical approach for the structural behaviour of the test sections is needed. In the present work, the linear elastic multi-layer analysis was possible by the use of equivalent thickness and equivalent stiffness for bituminous materials, reinforced by the 1140

presence of the steel meshes. Nevertheless, other numerical tools could be more appropriate for this evaluation. For example, some specific aspects of the reinforcement with an influence on pavement behaviour, e.g. diameter of the steel bars, size of the mesh, adherence of steel-bituminous material, corrosion of the steel, could be considered by the finite element method. Despite the restricted development of the work presented in this paper, the main conclusions obtained from the case study could be useful for further research on this subject. REFERENCES Alves, A.R.D. 2007. Reinforcement of Bituminous Mixtures with Steel Meshes. MSc Thesis. Technical University of Lisbon. Portugal (in Portuguese). COST 348 2004. Assessment of Benefits and Goals for Different Reinforcement Applications. REIPAS— Reinforcement of Pavements with Steel Meshes and Geosynthetics, Draft Report of WG1. EP 1998. Technical Specifications for Road Construction. Portuguese Road Administration, Portugal (in Portuguese). Korkiala-Tanttu, L. & Rathmayer, H.G. 2005. Steel Grids, an Efficient Way to Improve the Durability of the Pavement. Proc. 7th intern. conference on the Bearing Capacity of Roads, Railways and Airfields, Trondheim, Norway, 27–29 June 2005. Lechner, L. 2005. Steel Reinforced Asphalt Layers—Investigations and Experiences in Germany. Proc. 7th intern. conference on the Bearing Capacity of Roads, Railways and Airfields, Trondheim, Norway, 27–29 June 2005. Neves, J.M.C. & Gomes-Correia, A. 2002. Bearing Capacity of a Flexible Pavement during the Construction Phase. In Correia & Branco (eds.), Bearing Capacity of Roads, Railways and Airfields, Proc. 6th intern. conference, Lisbon, Portugal, 24–26 June 2002. Volume 1: 677–684. Rotterdam: Balkema. Rathmayer, H.G. & Korkiala-Tanttu, L. 2005. On Design Principles of Reinforced Pavement Structures—the COST 348 REIPAS action. Proc. 7th intern. conference on the Bearing Capacity of Roads, Railways and Airfields, Trondheim, Norway, 27–29 June 2005.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

In-situ strain measurement during dynamic shear loading of an unbound geogrid reinforced pavement section B.R. Cox, B. Curry, C.M. Wood & C. Young University of Arkansas, Fayetteville, Arkansas, USA

J.S. McCartney University of Colorado at Boulder, Boulder, Colorado, USA

ABSTRACT: The goal of this paper is to present the details of an approach that can be used to evaluate the strain distribution in large-scale, geogrid-reinforced, unbound pavement test sections during application of dynamic surface loads. The approach is based on a 4-node isoparametric finite element formulation; wherein shear and normal strains are calculated from the response of geophones embedded in a reinforced pavement test section subject to different magnitudes of dynamic load. Details are provided on the construction of a large-scale reinforced pavement test section, application of dynamic surface loads using a Vibroseis (shaker) truck, instrumentation, and data reduction procedures used to obtain strain distribution as a function of depth. Results from the study show log-linear increases in shear and normal strain at all depths in the pavement test section as a result of increasing surface load amplitude. A reduction in the shear and vertical normal strains in the sub-base and subgrade layers (below the geogrid) from that measured in the base course layer was also observed. The preliminary results from this study indicate that the presence of the geogrid in the base course may contribute to a decrease in strains transmitted to underlying layers. Additional comparative studies using the testing approach described in this study are needed to confirm these findings. 1

INTRODUCTION

1.1 Background Many state departments of transportation throughout the U.S. are evaluating the use of biaxial geogrids and woven geotextiles as basal reinforcement layers in pavements. There are many potential positive effects of basal reinforcement with geosynthetics on the performance of pavements (Holtz et al. 1998; Berg et al. 2000; Zornberg et al. 2008), including: • • • • • • • •

Redistribution in vertical stresses applied to the subgrade. Reduction in shear stresses and strains at the subgrade-base interface. Reduction in penetration of base aggregate into the subgrade under repeated loading. Increase in pavement strength due to the possible use of open-graded, free draining aggregates permitted due to the decreased likelihood of intrusion and pumping. Reduction in excavation required for the removal of unsuitable subgrade materials. Reduction in the thickness of aggregate needed to provide a stable bearing surface. Reduction in differential settlement and rutting of the pavement surface. Prevention of crack propagation from the subgrade into the base course.

These effects have the cumulative impact of reducing the overall cost of pavement systems through more efficient use of materials, reduced maintenance needs, and increased service lifetimes. Empirical evidence of these benefits was noted in full-scale field studies (Miura et al. 1990; Fetten et al. 1998; Huntington 1999; Al Qadi and Appea 2003; Warren 2005; Hufenus et al. 2006; Zornberg et al. 2008), full-scale test tracks (Halliday and Potter 1984; Barksdale et al. 1989; 1143

Cancelli et al. 1996; Hayden et al. 1999; Perkins and Cortez 2005), and laboratory-scale box tests (Haas et al. 1988; Al Qadi et al. 1994; Smith et al. 1995; Collin et al. 1996; Montanelli et al. 1997; Perkins et al. 1998; Perkins et al. 1999; Kinney 1999; Leng and Gabr 2002; Tingle and Jersey 2005; Chebab et al. 2007). However, although many of the benefits listed above are related to the impact of the geosynthetic reinforcement layer on the strain distribution in the pavement profiles, there have been only limited measurements of in-situ strain distributions during dynamic loading of pavements in the previous studies (Perkins et al. 1999). This lack of measurements is due to historical challenges in selection and installation of instrumentation suitable for capturing the dynamic response of relatively thin pavement layers under different loading magnitudes, as well as associated challenges in data acquisition and data reduction. Recent advances in field instrumentation and data acquisition for soil dynamics has provided tools that can be used to address these challenges (Zeghal et al. 2005; Rathje et al. 2004, 2005; Cox et al. 2008). Measurement of in-situ strains is expected to yield important information as to the performance of pavement systems, revealing: (1) the effects of different variables on pavement performance (i.e., pavement layer geometry, unsaturated stress state, geosynthetic and soil properties, geosynthetic-soil interaction, loading characteristics), and (2) relevant material properties governing the mechanical behavior of reinforced pavement systems that can be used in analytical modeling efforts. Without this information, it is difficult to verify mechanistic analyses that form the basis of reinforced pavement design. The goal of this paper is to describe the measurement of the distribution in shear and normal strains as a function of depth in an instrumented geogrid-reinforced pavement test section during application of different magnitudes of dynamic shear stresses to the pavement surface. These results will be used to interpret the impact of geosynthetic reinforcement on the test section performance. The results presented in this paper are from the first stage in a twostage characterization program for reinforced pavements. The second stage involves application of many cycles of constant compression load to the pavement surface. The second stage, which also incorporates measurement of in-situ strains using the approach outlined in this paper, was conducted to provide information that has traditionally been obtained from fullscale field characterization tests or laboratory-scale box tests (e.g., permanent rutting profiles with time), but in an accelerated fashion. The results of the second stage will be discussed in a subsequent paper. 1.2 In-situ strain calculation Dynamic traffic loading induces body waves (compression and shear) that propagate through pavements and induce compression (normal) and shear strains in the pavement materials (Figure 1a). High-amplitude strains, or large numbers of moderate-amplitude strains, may induce permanent deformation in the pavement. It is therefore important to be able to quantify the distribution of strain within pavements. Most previous geotechnical investigations that computed in-situ strains from dynamic measurements have used displacement-based approaches (Zeghal et al. 2005; Rathje et al. 2004, 2005; Cox et al. 2008). Displacement-based strain computation methods (Rathje et al. 2005) are established using definitions of strain from mechanics, as follows: ∂ui ∂yi

(1)

∂ui ∂u j + ∂y j ∂yi

(2)

εi =

γ ij =

where ε represents normal strain, γ represents engineering shear strain, u represents displacement, y represents direction, and i and j are direction subscripts that take on 1, 2 or 3 to represent the three, orthogonal coordinate dimensions. To compute in-situ strains, displacements are measured at known, discrete points in the soil and numerical methods are used to estimate 1144

Traffic direction uz4 Base Course Geogrid

Figure 1.

(0,b)

uz3

uy3

Body waves (–a,0)

Subbase Subgrade

uy4

uz1

Elements of interest

uy1

(0,0)

(0,–b)

(a,0) uz2

(a)

uy2

(b)

(a) Schematic of dynamic loading of layered pavement system; (b) Typical 4-node element.

the derivatives in Equations (1) and (2). For three-dimensional problems, there are six strain components (three normal and three shear). However, if plane strain conditions are assumed only three components of strain (two normal and one shear) are relevant. It is possible to compute these strains within a pavement if elements (arrays) of instrumentation can be embedded to sense the vertical and horizontal displacements caused by passing stress waves (Figure 1a). In order to do this, the locations of the in-situ measurement points should be chosen so as to create 4-node rectangular arrays, each similar to that shown in Figure 1(b). For each array, the horizontal direction is defined as y, the vertical direction is z, and the displacements measured in these two orthogonal directions are uy and uz, respectively. The sides of this rectangular array measure 2a in the y direction and 2b in the z direction. Using this coordinate system, the pertinent plane strain components are εy, εz, and γxz. To compute the strain components within the rectangular array the 4-node isoparametric element formulation often used in finite element analysis (e.g., Cook et al. 1989) may be used. For this formulation, the horizontal and vertical displacements (uy and uz, respectively) are known at the nodal points and a linear variation of displacement is assumed between nodes. The resulting expressions that describe the variations in normal vertical, normal horizontal, and shear strain across an element (with a size of 2a × 2b) in terms of the nodal displacements are:

ε y ( y, z ) =

1 ⎡ −uy1 (1 − z / b ) + uy 2 (1 − z / b ) + uy3 (1 + z / b ) − uy 4 (1 + z / b ) ⎤⎦ 4a ⎣

(3)

ε z ( y, z ) =

1 [ −uz1(1 − y / a ) + uz 2 (1 − y / a ) + uz 3 (1 + y / a ) + uz 4 (1 + y / a )] 4b

(4)

u u u 1⎡ u γ y z ( y, z ) = ⎢ − y1 (1 − y / a ) − z1 (1 − z / b ) − y 2 (1 + y / a ) + z 2 (1 − z / b ) a b a 4⎣ b u u ⎤ u u + y3 (1 + y / a ) + z 3 (1 + z / b ) + y 4 (1 − y / a ) − z 4 (1 + z / b ) ⎥ b a b a ⎦

(5)

These expressions provide strain values within the rectangular element at any location (y, z) and are first-order accurate. It is important to note that these expressions are only applicable to rectangular elements. The most critical assumption employed in this strain formulation is the linear variation of displacement between nodes. For this assumption to be valid, the wavelength of the stress waves traveling through the instrumentation array should be much larger than the element size. To ensure that the computed strains are not significantly 1145

affected by the linear variation assumption, Rathje et al. (2005) recommended that the larger dimension of the instrumentation array be smaller than 1/5 of the wavelength. This assumption is assessed in Section 4. In this study, the strain response of a reinforced pavement system subject to dynamic shear loading is considered. While dynamic compression loading is more representative of actual traffic loading, strains calculated from dynamic shear loading have proven less complicated to evaluate. Thus, dynamic shear loading is considered first, and dynamic compression loading will be considered at a later date. The experiment conducted in this study involves the horizontal excitation of a circular loading footprint on the ground surface. The pavement response to this excitation was recorded using three embedded sensor arrays. Details regarding the experimental setup and layout of the sensor arrays are provided below. 2

EXPERIMENTAL SETUP

2.1 Test section An unbound, geogrid-reinforced, un-surfaced pavement test section was constructed at the Engineering Research Center (ERC) at the University of Arkansas. A schematic of the crosssectional geometry of the test section is shown in Figure 2. In plan view, the test section had an approximate extent of 4 m by 4 m. In this study, an asphaltic concrete surface layer was not used to permit rapid demolition and reconstruction of test sections in the same location, but it may be evaluated in the future. The subgrade soil at the site is a low plasticity silt (USSC classification of ML), with a California Bearing Ratio of 1. A preliminary test section was constructed with aggregate base atop the subgrade, but adequate compaction was not obtained due to pumping failure of the saturated subgrade silt. Accordingly, 50 cm of the subgrade silt was excavated and replaced with 25 cm of subgrade re-compacted at its optimum moisture content, and 20 cm of compacted sandy red clay (USSC classification of SC), which served as a subbase layer. A 30 cm layer of compacted Class 7 aggregate base (SB2) was used as the primary component of the unbound pavement section. A Mirafi BasXgrid 12 geogrid was placed between the first and second compaction lifts in the base course to provide basal reinforcement. The pavement test section was instrumented with an array of 2-D geophone (velocity transducers) packages embedded in the base and subbase layers during compaction. The coordinates of the geophone packages in the pavement section is shown in Figure 3. Also shown in this figure are the actual thicknesses of the pavement layers and geogrid. The center of the rectangular elements formed by each combination of 4-nodes is used in this study as a

Static hold down force and dynamic shear force

30 cm

Class 7 Base Course

20 cm

Subbase Red Clay

0.91 m circular loading base plate 2-D velocity transducers Biaxial geogrid Not to scale 3m

Subgrade Silt Figure 2.

Geogrid-reinforced pavement cross section evaluated in this study.

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Horizontal distance (cm) –20 –15 –10 –5

0

5

10

15

20

Depth from surface (cm)

0 Class 7 Base Course

10

Nodes

30

Geogrid Subbase Red Clay

40 50

Subgrade Silt

60 Figure 3.

Strain calculation points

20

Scale drawing of pavement model layout with sensor locations. Geophone package in vertical calibration configuration

Epoxy seal

Vertical geophone

Horizontal geophone

Shake Table

(a) Figure 4.

Calibrated proximeter

(b) 2-D geophone package: (a) Picture and schematic view; (b) Calibration.

strain calculation point (Gauss point). A strain calculation point is located inside the aggregate base and subbase layers, as well as at the interface zone encompassing the geogrid and the base-subbase interface. 2.2 Construction and calibration of 2-D geophone packages Geophones (velocity transducers) have traditionally been used in geotechnical engineering to monitor particle motion due to passage of stress waves (Stokoe and Santamarina 2000). Geophones with a natural frequency of 28 Hz are used in this study to measure the particle velocity response at discrete points in the pavement test section during dynamic loading. Geophones are passive analog devices comprised of a spring-mounted magnetic mass, which generates an electrical signal proportional to its velocity with respect to a surrounding wire coil. As the movement of the magnetic mass is constrained to one dimension, an acrylic package was constructed to hold two geophones in orthogonal directions (vertical and horizontal), as shown in the picture and schematic in Figure 4(a). The sensor package is compact and lightweight, measuring 2.5 cm in height and 5 cm in width. The electrical cable contains two individually twisted and shielded conductor pairs that carry the geophone signals back to the ground surface. Each geophone was calibrated on a shake table after hardening of 1147

the waterproofing epoxy. The shake table was driven with a sinusoidal motion with constant amplitude, but sweeping frequencies from 10 to 100 Hz. The amplitude and phase response of the geophone as a function of frequency was calibrated against a reference proximeter. The results of a typical calibration are shown in Figure 5. The results in Figure 5 indicate that the voltage response of a geophone is sensitive to the frequency of particle motion. The equation of free motion of a damped single degree of freedom oscillator was fitted to the calibration curve, also shown in Figure 5. The factor S is a constant, fn is the natural frequency of the geophone (about 28 Hz) and D is the damping ratio. 2.3 Soil properties The granulametric curves of the three soils in the pavement section are shown in Figure 6(a). The subgrade silt has a relatively high proportion of fines (60%). It has a liquid limit of 28 and a PI of 11. The CBR of this soil is approximately 1.0, so a subbase layer was added to stabilize the soil and to minimize piping. The red clay subbase is a residual soil from Arkansas, and is gap-graded with both larger-size chert particles as well as clay fines. The clay fraction has a liquid limit of 64 and a PI of 28, and does not show significant swelling upon wetting. Due to the chert particles it is classified as a sandy clay (SC). The aggregate base is a well graded gravel that contains a wide range of particle sizes. Standard Proctor compaction tests were performed on the subgrade silt and the red clay, while a

0.8 0.7 Calibration factor (V/in/sec)

Sf

Amplitude =

2

2 2

2

( fn − f ) + ( 2Dfn f ) 2

0.6 0.5 0.4 0.3 0.2 0.1 0.0 0

20

40

60

80

100

Frequency (Hz)

100 90 80 70 60 50 40 30 20 10 0

(a) 100

Typical amplitude calibration curve for a geophone and calibration equation.

Dry unit weight (kN/m3)

Percent finer by mass

Figure 5.

Subgrade Silt Subbase Red Clay Class 7 Base Course 10

1 0.1 Grain size (mm)

25.0 22.5

In-situ

20.0 aggregate base conditions

17.5 15.0 Subgrade Silt Subbase Red Clay Class 7 Base Course

12.5 10.0

0.01

0

(b )

In-situ subbase conditions

5 10 15 Compaction water content (%)

20

Figure 6. (a) Grain size distribution curves for pavement soils; (b) Compaction curves for pavement soils.

1148

modified Proctor test was performed on the aggregate base. The red clay and aggregate base were adjusted for the coarse fraction size using AASHTO T224 before compaction. The compaction curves using these conditions are shown in Figure 6(b). In the field, the subgrade silt and red clay were compacted using a vibratory sheepsfoot roller, while the aggregate base was placed using three passes of a vibratory plate compactor. The subgrade silt water content was approximately 16%, but the density was not measured in this test. The red clay was compacted wet of optimum. The water content and dry density in the field were measured using a neutron gauge before placement of the aggregate base, and were found to be 19% and 15 kN/m3, respectively. The aggregate base was also placed wet of optimum, at a water content of approximately 7%. The water content and dry density of the aggregate base measured using the neutron gauge prior to loading (after providing 1 day for “curing”) were found to be 4.65% and 22.9 kN/m3, respectively. It was expected that the field dry densities for the red clay and aggregate base measured in-situ would be larger than measured in the lab due to the presence of the coarse fraction. The compaction effort imposed by the vibratory plate compactor was likely greater than the compaction effort used in the laboratory. 2.4 Construction procedures After clearing of vegetation at the location selected for the test section at the ERC [Figure 7(a)], the subgrade silt was removed. Attempts at compaction of a preliminary test section indicated that the subgrade silt was too soft for dynamic compaction, and intrusion of aggregate particles was noted due to compaction alone. Accordingly, the subgrade was dried and re-compacted using a vibratory sheepsfoot roller [Figure 7(b)] and a 20 cm-thick layer of compacted red clay was placed as a subbase layer [Figure 7(c)]. Two 8-cm diameter holes were cored in the subbase, and geophone packages were placed at the heights shown in Figure 3. The red clay was re-compacted by hand into the holes around the sensors. The cables were placed in flexible electrical conduits [Figure 7(d)] for ease of removal after testing. A 10-cm thick lift of aggregate base was then placed directly above the subbase layer, and a geogrid was placed atop this first lift [Figure 7(e)]. The geogrid was stretched across the section, but it was not placed into tension. A pair of sensors was then placed atop the geogrid at the heights shown in Figure 3 in locations directly above those in the subbase layer [Figure 7(f)]. Aggregate base material passing the number 10 sieve was used for leveling around the location of the sensors to both protect the sensors as well as to avoid the possibility of a larger particle distorting the orientation of the sensor during compaction. After placement of two additional lifts of aggregate base of thicknesses of approximately 7 cm, the uppermost pair of sensors was placed at the height shown in Figure 3. The final lift of aggregate base was then placed atop these sensors, which also had a thickness of 7 cm. The aggregate base was compacted using three passes of a hand-driven vibratory plate compactor, as shown in Figure 7(g). During placement of the different layers, the heights of the lifts and the locations of the geophone packages were assessed using a leveling beam placed across the width of the test section, as shown in Figure 7(h). It was necessary to measure the exact coordinates of the geophones before and after testing, as the distances between each geophone are small and critical to accurate strain calculations. The leveling beam was also useful in assessing the location of the sensors after compaction, and measuring the deflection of the surface after testing. 2.5 Vibroseis loading system The dynamic loading source employed in this study is a biaxial vibroseis truck owned by the University of Arkansas. In addition to its mobility, this truck has the advantage of having a servo-controlled hydraulic loading system that can apply variable static hold-down forces up to 62 kN as well as an additional superimposed peak-to-peak horizontal or vertical dynamic load of up to 53 kN. A picture of the loading system of the truck is shown in Figure 8(a). The truck has a 0.9 m diameter steel base plate that can be pressed onto the ground surface using a pair of hydraulic pistons. Dynamic loads were applied to the pavement by providing 1149

(a)

(b)

(c )

(d )

(e)

(f)

(g)

(h)

Figure 7. Construction pictures: (a) Site prior to construction; (b) Removal of subgrade and re-compaction; (c) Placement of red clay subbase; (d) Cables leading to geophones placed in holes filled with re-compacted red clay; (e) Placement of geogrid atop first lift of base; (f) Placement of geophones atop geogrid; (g) Compaction of aggregate base; (h) Completed test section with leveling rod.

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Guide shafts

Static hold-down pistons

Hydraulic pump

Direction of loading for the current study

(a) Oscillating mass 0.91 m diameter base plate

Vibration isolators

Figure 8.

(b)

(a) Vibroseis truck components; and (b) Vibroseis truck in shear loading configuration.

a sinusoidal driving voltage pattern to a servo-control solenoid valve that drives a 140-kg steel mass along a low-friction shaft. The vibration of the oscillating mass and base plate is isolated from the truck using pressurized rubber air bags. In this study, the vibroseis was operated in the horizontal in-line direction of vibration, thus generating strong shear waves traveling downward from the ground surface, polarized in line with the arrangement of the geophone array, as shown in Figure 8(b). 2.6 Data acquisition During testing, the data recorded included: (1) the vibroseis drive signal, (2) the input ground force signal from accelerometers connected to the base plate and oscillating mass on the vibroseis truck, and (3) a total of 16 output signals from embedded geophones in the eight separate sensor packages. The signals from the accelerometers and geophones were recorded at a sampling rate of 100K samples/sec using a 32-channel Data Physics dynamic signal analyzer. During this field testing study, the oscillating mass of the vibroseis was driven with a 30 Hz sinusoidal waveform of variable amplitude (i.e. variable ground forces were input into the pavement). While this sampling rate may be considered as oversampling in terms of frequency domain measurements, it was chosen so that enough data points would be digitized in the time domain to allow accurate determination of the stress wave velocity between the sensors in the array shown in Figure 3. 3

RESULTS

3.1 Loading patterns Throughout the duration of testing described in this study, a static hold-down force of approximately 40 kN (one half of an ESAL) was applied through the circular base-plate to the ground surface. This resulted in a vertical surface stress of approximately 60 kPa, as shown in Figure 9. Five increments of dynamic horizontal (shear) loading were applied to the ground surface, as shown in Figure 9. Only horizontal loading is used in this study. This type of loading is not intended to replicate traffic loading. Instead, it is used as a convenient way to evaluate stain distribution throughout the pavement test section. Vertical vibration of the footprint will also be evaluated in future studies to evaluate pore water pressure generation during cyclic loading. During each loading increment, approximately 20 cycles were applied to the ground surface at a frequency of 30 Hz. A frequency of 30 Hz was used as FWD tests indicate that pavements typically show resonant amplification at this frequency (Ketcham 2008). 1151

Applied static surface normal stress (kPa) Applied dynamic surface shear stress (kPa)

60

22

Time

12

6

2

28

Time

20 cycles at 30 Hz (0.667 sec loading increment) Figure 9.

Loading patterns used to determine in-situ strain distributions.

(a)

(c)

(b)

(d)

Figure 10. Displacement time histories for nodes at depths of: (a) 7 cm; (b) 26 cm; (c) 38 cm; (d) 50 cm.

3.2 Nodal displacement response Calibration factors were applied to the geophone output voltages to obtain particle velocity time histories. The particle velocity time histories were then numerically integrated in the time domain using the trapezoidal rule to obtain displacement time histories. The displacement time histories for the loading increment of 28 kPa are shown in Figures 10(a) to 10(d) for the nodes along the left side of the sensor array (refer to Figure 3) at depths of 7, 26, 38, and 50 cm, respectively. The displacement time histories are of primary interest in the subsequent 1152

shear strain evaluation procedures. The data in Figure 10 indicates that the displacement magnitude decreased with depth in the soil profile, with a greater decrease in magnitude between depths of 26 and 38 cm than between depths of 7 and 26 cm. 4

DATA REDUCTION TO OBTAIN STRAIN TIME HISTORIES

As discussed above, the corners of the sensor arrays may be considered as nodes of single, quadrilateral finite elements. This configuration allows the strains anywhere within the element to be calculated from the displacements at the sensors (nodes) using a 4-node, isoparametric finite element formulation (Rathje et al. 2004, 2005). For the pavement characterization test, the vertical (z) and horizontal in-line (y) components of particle displacement at each sensor location are used to calculate the in-plane shear strain (γyz) induced at the center of the arrays (refer to Figure 3). Examples of shear strain time histories calculated at the center of each of the three rectangular arrays of geophones are shown in Figure 11. The attenuation of shear strain as a function of depth is readily apparent. The strain time histories calculated at the center of the array generally have very consistent amplitudes over all 20 cycles of loading. For example, the shear strain time history for the uppermost element, shown in Figure 11(a), showed the most variability but still had an average shear strain over the 20 cycles of 0.26% ± 0.05%. The 4-node, isoparametric finite element formulation provides strain values within the element that are first-order accurate. The most critical assumption in the method is the linear variation of displacement between nodes (Rathje et al. 2004, 2005). For this assumption to be valid, the size of the array in the direction of wave propagation should be less than about one-fifth of the wavelength of the highest significant frequency (i.e., the shortest wavelength) used during testing (Rathje et al. 2005). The highest frequency used during in-situ liquefaction tests was 30 Hz. The compacted aggregate base tested in these studies has a shear wave velocity (Vs) of approximately

(a)

(b)

(c)

Figure 11. Typical shear strain time histories obtained from finite element calculations for the centers of elements at depths of: (a) 16.5 cm; (b) 23 cm; and (c) 44 cm.

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300 m/s. Therefore, a 30 Hz wave propagating through this material would have a wavelength of about 10 m, which is about fifty times greater than the vertical dimension of the sensor array. It is therefore believed that a linear variation of displacement between nodes is a valid assumption for this test setup. 5

ANALYSIS OF IN-SITU STRAIN MEASUREMENTS

5.1 Shear response The average peak shear strains during each of the loading increments shown in Figure 9 are summarized in Figure 12(a) on a logarithmic scale and in Figure 12(b) on a natural scale. When the shear strain is plotted on a logarithmic scale in Figure 12(a), a log-linear trend in shear strain with the magnitude of the applied surface stress is observed, with parallel trends for the strains at each depth. When the shear strain is plotted on a natural scale in Figure 12(b), it is clear that there is a greater difference in shear strain generated in the soil above and below the geogrid layer (depth of 28 cm). This difference increases with the magnitude of applied surface shear stress. The potential impact of the geogrid layer on the strain distribution within the test section is easier to visualize on the shear strain profiles with depth, shown in Figure 13. This data shows a

(a)

(b)

Figure 12. In-situ peak shear strains for different peak amplitudes of shear stresses applied to the pavement surface (a) Log strain; (b) Natural strain.

Geogrid

Figure 13.

Shear strain profiles with depth during dynamic shear loading.

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(a)

(b)

Figure 14. Peak vertical normal strain profiles for different peak amplitudes of shear stresses applied to the pavement surface (a) Log strain; (b) Natural strain.

Geogrid

Figure 15.

Normal vertical strain profiles with depth during dynamic shear loading.

significant decay in shear strain with depth in the soil profile. Although this data is preliminary, and does not confirm the role of the geogrid in the redistribution of shear strains in the layered soil system, it indicates that the geogrid may play a role in the reduction of shear strain with depth. In order to confirm this, additional tests of this type need to be conducted on pavement test sections with various reinforcement configurations (including no reinforcement). 5.2 Compression response Applied shearing stresses at the ground surface also lead to a compression response in the soil due to rocking of the vibroseis base plate. This rocking motion is minimized through the use of a relatively high hold-down stress of 60 kPa. Nonetheless, the trends in the vertical normal strain for different depths, shown in Figure 14(a) on a logarithmic scale and in Figure 14(b) on a natural scale, follow similar trends to those observed for the shear strain in Figure 12. The vertical normal strain profiles shown in Figure 15 indicate a similar shape in the strain profile around the depth of the geogrid (28 cm). 6

CONCLUSIONS

Procedures were developed in this study for in-situ measurement of shearing and normal strains during dynamic loading of reinforced unbound pavements. The results of this study 1155

indicate that this approach is useful to compare the shear and normal strains transmitted from the aggregate base layer to underlying soil layers in geosynthetic-reinforced and unreinforced pavement test sections. This approach will be useful to permit rational comparison between different geosynthetic products and design configurations. The large-scale nature of this test section and the flexibility in the loading system permit this approach to be used to evaluate design alternatives experimentally before implementation in the field. In the future, information from such tests can be used to develop design guidelines for reinforced pavements, perform cost-benefit design analyses, and evaluate the impact of stress state (i.e., matric suction) in a controlled setting. Research is currently being conducted on several different reinforced and un-reinforced pavement test sections. In these studies, both shear and normal dynamic stresses are being applied to the pavement surface. In Stage 1, the magnitudes of the dynamic stresses are varied (as presented in this paper) and limited numbers of cycles of loading are applied so as to gauge the influence of load magnitude on response. In Stage 2, magnitude of the dynamic stress will be fixed at a value similar to that expected from a single wheel load (i.e. half of an ESAL) and large numbers of load cycles will be applied to the pavement to determine the degradation of the system as a function of number of loading cycles. REFERENCES Al-Qadi, I.L., Brandon, T.L., Valentine, R.J., Lacina, B.A. and Smith, T.E. (1994). “Laboratory Evaluation of Geosynthetic Reinforced Pavement Sections,” In Transportation Research Record 1439, TRB, National Research Council, Washington, DC, pp. 25–31. Al-Qadi, I.L. and Appea, A.K. (2003). “Eight-years of field performance of a secondary road incorporating geosynthetics at the subgrade-base interface.” 82nd Annual Meeting, Transportation Research Board. Washington, CD-Rom, 21 p. Barksdale, R.D., Brown, S.F. and Chan, F. (1989). “Potential Benefits of Geosynthetics in Flexible Pavement Systems.” National Cooperative Highway Research Program Report No. 315, Transportation Research Board, National Research Council, Washington, DC. Berg, R., Christopher, B. and Perkins, S. (2000), Geosynthetic Reinforcement of the Aggregate Base Course of Flexible Pavement Structures, GMA White Paper II, Geosynthetic Materials Association, Roseville, MN, USA, 130 p. Cancelli, A., Montanelli, F., Rimoldi, P. and Zhao, A. (1996). “Full Scale Laboratory Testing on Geosynthetics Reinforced Paved Roads.” Proceedings of the International Symposium on Earth Reinforcement. Fukuoka/Kyushu, Japan, November, Balkema, pp. 573–578. Chehab, G., Palomino, A. and Tang. X. (2007). “Lab Evaluation and Specification Development for Geogrids for Highway Engineering Applications.” Report to PennDOT. FHWA-PA-2007-009-50110. 136 p. Collin, J.G., Kinney, T.C. and Fu, X. (1996). “Full Scale Highway Load Test of Flexible Pavement Systems with Geogrid Reinforced Base Courses,” Geosynthetics Intentional, Industrial Fabrics Association International, Roseville, MN, Vol. 3, No. 4, pp. 537–549. Cook, R.D., Malkus, D.S. and Plesha, M.E. (1989). Concepts and Applications of Finite Element Analysis. 3rd Edition. John Wiley and Sons, New York, NY. Cox, B.R., Stokoe, K.H., II, and Rathje, E.M. (2008). “An In-Situ Test Method for Evaluating the Coupled Pore Pressure Generation and Non-linear Shear Modulus Behavior of Liquefiable Soils.” ASTM Geotechnical Testing Journal. Accepted. Fetten, C.P. and Humphrey, D.N. (1998). Instrumentation and Performance of Geosynthetics Beneath Flexible Pavements in Winterfort and Frankfort, Maine, Department of Civil and Environmental Engineering Report, University of Maine, 137 p. Halliday, A.R. and Potter, J.F. (1984). “The Performance of a Flexible Pavement Constructed on a Strong Fabric,” Transport and Road Research Laboratory, Report 1123, Crowthorne, Berkshire, 15 p. Haas, R., Wall, J. and Carroll, R.G. (1988). “Geogrid Reinforcement of Granular Bases in Flexible Pavements,” In Transportation Research Record 1188, TRB, National Research Council, Washington, DC, USA, pp. 19–27. Hayden, S.A., Humphrey, D.N, Christopher, B.R., Henry, K.S. and Fetten, C. (1999). “Effectiveness of Geosynthetics for Roadway Construction in Cold Regions: Results of a Multi-Use Test Section,” Proceedings of the Conference Geosynthetics ‘99, Boston, MA, USA, Vol. 2, pp. 847–862. Holtz, R.D., Christopher, B.R., Berg, R.R. and DiMaggio, J.A. (1998). Geosynthetic Design and Construction Guidelines, U.S. Department of Transportation, Federal Highway Administration, Washington, DC.

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Huntington, G. and Ksaibati, K. (1999). “Evaluation of Geogrid-Reinforced Granular Base,” GSP No. 89, Recent Advances in the Characterization of Transportation Geo-Materials, ASCE, pp. 13–24. Ketcham, S. (2008). “Dynamic Response Measurements and Identification Analysis of a Pavement During Falling-Weight Deflectometer Experiments.” Transporation Research Record 1415. p. 78–87. Kinney, T.C. (1999). “Laboratory Tests to Determine the Direction of Movement of Particles on a Horizontal Plane in a Road During Loading,” Proceedings of the Conference Geosynthetics ‘99, Boston, MA, USA, Vol. 1, pp. 279–290. Leng, J. and Gabr, M. (2002). “Characteristics of geogrid-reinforced aggregate under cyclic load.” Journal of Transportation Research Board No. 1786. National Research Council. Washington D.C. 29–35. Ling, H. and Liu, Z. (2001). “Performance of geosynthetic reinforced asphalt pavements.” Journal of Geotechnical and Geoenvironmental Engineering. 127(2), 177–184. Montanelli, F., Zhao, A. and Rimoldi, P. (1997). “Geosynthetic-Reinforced Pavement System: Testing and Design,” Proceedings of the Conference Geosynthetics ’97, Long Beach, CA, USA, Vol. 2, pp. 619–632. Miura, N., Sakai, A., Taesiri, Y., Yamanouchi, T. and Yasuhara, K. (1990). “Polymer Grid Reinforced Pavement on Soft Clay Grounds,” Geotextiles and Geomembranes, Elsevier Applied Science, Oxford, UK, Vol. 9, pp. 99–123. Perkins, S.W. and Cortez, E. (2005). “Evaluation of base-reinforced pavements using a heavy vehicle simulator.” Geosynthetics International. 12(2), 87–98. Perkins, S.W., Ismeik, M. and Fogelsong, M.L. (1998). “Mechanical Response of a Geosynthetic-Reinforced Pavement System to Cyclic Loading,” Proceedings of the Fifth International Conference on the Bearing Capacity of Roads and Airfields, Trondheim, Norway, Vol. 3, pp. 1503–1512. Perkins, S.W., Ismeik, M. and Fogelsong, M.L. (1999). “Influence of Geosynthetic Placement Position on the Performance of Reinforced Flexible Pavement Systems,” Proceedings of the Conference Geosynthetics ‘99, Boston, MA, USA, Vol. 1, pp. 253–264. Rathje, E.M., Chang, W.J. and Stokoe, K.H., II (2005), “Development of an InSitu Dynamic Liquefaction Test,” ASTM Geotechnical Testing Journal, Vol. 28, No. 1, pp. 50–60. Rathje, E.M., Chang, W-J., Stokoe, K.H., II, and Cox, B.R. (2004), “Evaluation of Ground Strain from InSitu Dynamic Testing,” Paper No. 3099, 13th World Conference on Earthquake Engineering, Vancouver, Canada, August. Smith, T.E., Brandon, T.L., Al-Qadi, I.L., Lacina, B.A., Bhutta, S.A. and Hoffman, S.E. (1995). “Laboratory Behavior of Geogrid and Geotextile Reinforced Flexible Pavements.” Final Report Submitted to Atlantic Construction Fabrics, Inc. Amoco Fibers and Fabrics Company and the Virginia Center for Innovative Technology, February, Virginia Polytechnic Institute and State University, Department of Civil Engineering, Blacksburg, VA, USA, 94 p. Stokoe, K. and Santamarina, C. (2000). “Seismic-Wave-Based Testing in Geotechnical Engineering.” GeoEng 2000. Melbourne, Australia. pp. 1490–1533. Tingle, J. and Jersey, S. (2005). “Cyclic Plate Load Testing of Geosynthetic-Reinforced Unbound Aggregate Roads.” Transportation Research Record: Journal of the Transportation Research Board, No. 1936, Transportation Research Board of the National Academies, Washington, DC, 2005, pp. 60–69. Zeghal, M., Elgamal, A.W., Tang, H.T. and Stepp, J.C. (1995). “Lotung Downhole Array II: Evaluation of Soil Nonlinear Properties.” ASCE Journal of Geotechnical Engineering. 121(4): 363–378. Zornberg, J.G., Gupta, R., Prozzi, J. and Goehl, D. (2008). “Case Histories on Geogrid Reinforced Pavements to Mitigate Problems Associated with Expansive Subgrade Soils.” GeoAmericas 2008. Cancun, MX. Mar. 3–6.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Experimental study on bearing capacity of geocell-reinforced bases S.K. Pokharel, J. Han, R.L. Parsons & Y. Qian University of Kansas, Lawrence, Kansas, USA

D. Leshchinsky University of Delaware, Delaware, USA

I. Halahmi PRS Mediterranean Ltd., Tel-Aviv, Israel

ABSTRACT: Geocell, a three-dimensional interconnected geosynthetic made of polymer, has been used to improve base course properties by providing soil confinement to increase its stiffness and to reduce its permanent surface deformation. Research conducted in the past on geocell-reinforced base courses has shown apparent benefits over unreinforced ones. However, the use of geocell reinforcement for base courses on soft subgrade is limited due to lack of established design methods. In this study, laboratory tests were conducted to investigate the behavior of geocell-reinforced bases under static and repeated loading. Two base course materials, Kansas River sand and quarry waste, were used as infill materials. This study investigated the bearing capacity and stiffness improvement provided by geocell reinforcement and the effect of infill materials. This study also evaluated the permanent deformation and the percentage of elastic deformation of geocell-reinforced Kansas River sand and quarry waste compared with unreinforced bases. The test results show that the single geocell reinforcement can increase the bearing capacity, stiffness, and percent of elastic deformation for each cycle and reduce the permanent deformation. 1

INTRODUCTION

AASHTO (American Association of State Highway and Transportation Officials) reports approximately one-fifth of pavement failures occur due to insufficient structural strength. Inadequate bearing capacity of underlying weak subgrade and inefficient load transfer from the base course are two of the main reasons for pavement failures. This fact has led to research efforts to improve the state of pavement design practice and to develop sustainable pavement stabilization techniques. One of the options in this regard is the use of a suitable reinforcement to improve the overall structural strength and stiffness and to reduce the associated costs at the same time. During the last 40 years geosynthetic reinforcement has greatly helped to improve the performance of both paved and unpaved roads and become one of the established techniques for base course reinforcement (Giroud & Han 2004). Geosynthetic reinforcement has been reported to increase bearing capacity and reduce settlement, resulting in extended service life of pavements. Geogrids and geotextiles are commonly used as planar reinforcements at the subgrade-base interface or within the base course to increase the performance. Geocell, a three-dimensional interconnected honeycomb type of polymeric cells, is used within the base course. The majority of the research in the past has focused on planar reinforcements and developed design methods for these products (Giroud & Noiray 1981, Giroud and Han 2004, and Leng & Gabr 2006). For geocell reinforcement a significant gap between the applications and the theories has been identified outlining the need for further research to develop a reliable design method (Yuu et al. 2008).

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The United States Army Corps of Engineers used the idea of cellular soil reinforcement for providing lateral confinement to improve the bearing capacity of poorly graded sand in 1970s (Webster 1979a). Earlier geocells, known as sand grids, were made up of paper soaked in phenolic water resistant resin. Metallic geocells, especially aluminum, were later chosen for better strength but they were costly and difficult to handle. The polymeric geocells currently in use eventually emerged as a suitable alternative. High-density polyethylene (HDPE) is the most common polymer used to make geocell. Pokharel et al. (2009a) reported an improved geocell product made of novel polymeric alloys. Geocell comes in varying shape, size, aspect ratio, height, and thickness. This paper discusses the results of plate load tests conducted to evaluate the bearing capacity improvement for single geocell-reinforced sand and quarry waste. Laboratory tests for this research were carried out using a poorly-graded Kansas River sand and a quarry waste as the granular infill materials. A set of laboratory tests were conducted to study the influence of geocell reinforcement on the bearing capacity and stiffness as compared with unreinforced bases.

2

PAST STUDIES ON GEOCELL REINFORCEMENT

While geotextiles are mostly used for separation, drainage, and filtration, geogrids and geocells are mostly used for reinforcement by providing confinement. Lateral confinement, increased bearing capacity, and the tensioned membrane effect are the major geosynthetic reinforcement mechanisms (Giroud & Han 2004). Three-dimensional geocells can effectively provide lateral confinement to infill materials. In addition, the friction between the infill material and the geocell walls combine with the action of the reinforced base as a mattress to restrain the subgrade soil from moving upward outside the loaded area and provide the vertical confinement to the infill material and the subgrade. These mechanisms highlight the importance of geocell stiffness for the lateral and vertical confinement. Tests on single geocell-reinforced bases have shown an increase in the resilient modulus from 16.5 to 17.9% for cohesive soils and 1.4 to 3.2% for granular soils (Mengelt et al. 2006). For a given mattress thickness and rut depth, geocell reinforcement has been reported to increase the bearing capacity by twofold (Bathurst & Jarrett 1989). Shimizu & Inui (1990) also reported increased bearing capacity by geocell reinforcement and the extent of the increase correlated to the horizontal stiffness of the cell material. Inclusion of geocell in the granular bases could increase both the bearing capacity and the elastic modulus of the base by providing confinement to the infill material (Han et al. 2008). Pokharel et al. (2009a) found that the behavior of geocell-reinforced sand depends on the initial shape and the elastic modulus and the embedment condition of the geocell. Geocell reinforcement has also been reported to provide good improvement in resistance to repeated loads (Rea & Mitchell 1978). Chang et al. (2008) found the dynamic modulus of subgrade reaction to increase after 100 cycles of loading in a geocellreinforced sandy soil. Studies carried out by Pokharel et al. (2009b) on single geocell reinforcement found a stiffness improvement factor of 1.5 and bearing capacity improvement factor of 2.0 over the unreinforced case. Under repeated loading, geocell-reinforced granular base was found to reduce the plastic deformation and increase the percentage of elastic deformation to 95% of the total deformation at the end of 150 loading cycles (Pokharel et al. 2009b).

3

PROPERTIES OF BASE AND GEOCELL MATERIALS USED IN THE TESTS

In the present study, novel polymeric alloy geocells were used to reinforce two different base materials, Kansas River sand and quarry waste. The properties of the materials used for the tests are summarized below. Kansas River sand used as the granular base for the tests is poorly graded sub-rounded river sand with a mean particle size (d50) of 2.6 mm. The other properties of this sand are: minimum void ratio = 0.354, maximum void ratio = 0.583, specific gravity = 2.65 at 20ºC, 1160

coefficient of curvature, Cc = 0.98, coefficient of uniformity, Cu = 2.73, friction angle = 41ºC, γmin = 16.4 kN/m3, and γmax = 19.5 kN/m3. The grain size distribution of this sand is presented in Figure 1. The quarry waste used in the tests was brought from a local quarry site in Kansas. Quarry waste is a waste material produced during the production of aggregates and has not been well utilized. Geocell may provide a “green” solution to recycle quarry waste for roadway construction. The quarry waste used as the granular base for the tests has a mean particle size (d50 ) of 1.2 mm. The other properties are: liquid limit = 20, plastic limit = 12, specific gravity = 2.76, optimum moisture content = 9%, coefficient of curvature (Cc ) = 0.77, coefficient of uniformity (Cu ) = 12, California bearing ratio (CBR) = 57 at 7% moisture content and 38 at the optimum moisture content. The grain size distribution curve for this material is shown in Figure 1 and the compaction curve is shown in Figure 2. The geocell used for the tests was made of novel polymeric alloy, which is characterized by flexibility at low temperatures similar to HDPE and elastic behavior similar to engineering thermoplastic. The geocell had tensile strength of 23.27 N/mm. The elastic modulus of the geocell at 2% strain was 620 MPa. The 2% strain was chosen because the measured strains in geosynthetics in the field were typically within this range. The geocell used in this study

100 80 % passing

Quarry waste Kansas River sand

60 40 20 0 0.01

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Figure 1.

Grain size distribution curve of Kansas River sand (Han et al. 2008) and quarry waste.

Dry density ( g/cm3)

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Zero air void curve 2.1 2.0 1.9 4

Figure 2.

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Compaction curve of quarry waste.

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Figure 3.

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had two perforations of 100 mm2, each on both pallets. The perforations were located at a distance of 16 cm center to center. The height of the geocell was 100 mm and the thickness of the geocell wall was 1.1 mm. A single geocell was laid out in a near circular shape with a diameter of 205 mm. The selection of this shape was based on the earlier study by the authors (Pokharel et al. 2009a). The stress-strain curve of this geocell is shown in Figure 3. 4

TEST SETUP

Laboratory plate load tests were conducted in a medium-scale loading apparatus designed and fabricated at the geotechnical laboratory at the Department of Civil, Environmental, and Architectural Engineering at the University of Kansas. The loading system has a 15.2 cm diameter air cylinder with a maximum air pressure of 2,100 kPa. The steel loading plate has the same diameter as the air cylinder. The details of the test setup are shown in Figure 4. The test box is square and has a plan area of 60.5 × 60.5 cm2 with an adjustable depth. The geocell was placed at the center of the box and filled and embedded in the base material. The Kansas River sand was placed and compacted to 70% relative density in three layers, 5.0 cm thick for each of the first two layers and the top layer of 2.0 cm. For the quarry waste, 95% compaction was achieved at the optimum moisture content. For comparison purposes, unreinforced sand and quarry waste samples were prepared in a similar way and tested under static loading. For both base materials, static and repeated loading tests were conducted. The static tests were conducted on both reinforced and unreinforced sections by increasing the load in increment of 35 kPa. The repeated load tests were conducted only on the reinforced sections at an applied pressure of 345 kPa (corresponding to approximately 70% of the pressure at failure under the static loading) for the sand and 550 kPa for the quarry waste. The repeated load was applied at 1 cycle/minute for 150 cycles. The loading was selected based on the typical tire pressures for highway trucks and construction equipment ranging from 345 kPa to 550 kPa. Quarry waste can be used as the surface layer in an unpaved road so the loading 550 kPa was used. However, the Kansas River sand could only withstand a static load of approximately 500 kPa; therefore, a cyclic load of 345 kPa was chosen. 5

RESULTS AND DISCUSSIONS

Benefits of geocell reinforcements on the Kansas River sand and the quarry waste were investigated in this study. The details on the geocell-reinforced Kansas River sand are also 1162

Figure 4.

Test setup.

discussed in Pokharel et al. (2009a, b). For comparison purposes, the main results of the geocell-reinforced Kansas River sand are presented here as well along with those for the geocell-reinforced quarry waste. To study the effectiveness of single geocell reinforcement in two types of base materials, one specific type of geocell made from novel polymeric alloy was used in this study. As shown in Figure 5, under static loading the improvement factors for the geocellreinforced Kansas River sand over the unreinforced base are 1.75 in terms of ultimate bearing capacity and 1.5 in terms of stiffness. The improvement factor of the stiffness is defined as the ratio of the slope of the initial portion of the load-displacement curve for the reinforced base to that for the unreinforced base. Improvement was also observed for the geocell-reinforced quarry waste; however, the degree of improvement was not as significant as that for the geocell-reinforced Kansas River sand. Since the quarry waste has significant fines content, it has apparent cohesion after compaction. However, one of the contributions of geocell is to provide apparent cohesion to granular material; therefore, the cohesion existing in the base material minimizes the benefit of the geocell for lateral confinement under static loading. However, the loss of the moisture in the base would minimize the apparent cohesion and it is expected that the benefit of the geocell would become more significant at such a condition. Due to the limited capacity of the load frame, the tests for the quarry waste were carried out to the maximum static pressure of 900 kPa only. The improvement provided by the geocell is expected to be more evident at failure pressure. For roadway applications, the behavior of the base under repeated loading is more important than that under static loading. The results of the geocell-reinforced Kansas River sand under repeated loading are presented in the paper by Pokharel et al. (2009b). Similar test results for unreinforced and geocell-reinforced quarry waste are presented in Figure 6. The displacement at a load of 0 kPa is the permanent deformation of the base course. The difference in the displacements between 0 and 552 kPa is the elastic deformation. Figure 6 shows 1163

Applied pressure (kPa) 0

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Figure 5. Pressure-displacement curves for unreinforced and geocell-reinforced bases under static loading.

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Figure 6. Displacement versus number of loading cycles for quarry waste base under repeated loading.

that the single geocell reduced the permanent deformation of the quarry waste base by a factor of approximately 1.5 compared to the unreinforced section. For comparison purposes, the percentage of elastic deformation of the geocell-reinforced Kansas River sand and quarry waste and the unreinforced quarry waste sections are shown in Figure 7. The percentage of elastic deformation is defined as the percentage of the elastic deformation to the total deformation at each cycle. Figure 7 shows that for the Kansas River sand, it took 10 cycles to reach 80% or more of elastic deformation and the elastic deformation exceeded 95% of the total deformation for each cycle at the end of 150 loading cycles. For the unreinforced quarry waste section, it took 10 cycles to reach 90% elastic deformation and it reached 99% of the total deformation at the end of 150 cycles. For the reinforced quarry waste section, however, it took less than 10 cycles to reach 90% or more elastic deformation and the percent of elastic deformation almost reached 100% of the total deformation for each cycle at 50 loading cycles. Figure 7 does not include a curve for unreinforced Kansas River sand because it failed before reaching the 1164

% Elastic deformation

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Figure 7.

Percent of elastic deformation under repeated loading.

maximum pressure (345 kPa) in the first loading cycle. This comparison shows that the Kansas River sand had a smaller percentage of elastic deformation compared to the unreinforced and reinforced quarry waste due to its poor gradation, sub-rounded particles, and lack of apparent cohesion. Figure 7 also shows that the reinforced quarry waste had a higher percentage of elastic deformation than that of the unreinforced quarry waste due to the contribution of the geocell. 6

CONCLUSIONS

This paper presents the results of experimental work conducted to investigate the behavior of geocell-reinforced bases under static and repeated loading. Both static and repeated plate loading tests were performed on a single geocell embedded in Kansas River sand and quarry waste bases to provide the confinement. The following conclusions can be drawn for this study: 1. Geocell reinforcement improved the bearing capacity and the stiffness of the Kansas River sand by improvement factors of 1.75 and 1.5, respectively, under static loading. However, geocell reinforcement had a minor effect on the stiffness of the quarry waste under static loading due to the existence of apparent cohesion. 2. The single geocell reduced the permanent deformation of the quarry waste base by a factor of approximately 1.5 compared to the unreinforced base. 3. The Kansas River sand had a lower percentage of elastic deformation compared with the unreinforced and reinforced quarry waste due to its poor gradation, sub-rounded particles, and no apparent cohesion. The reinforced quarry waste had a higher percentage of elastic deformation than the unreinforced quarry waste due to the contribution of the geocell. The above conclusions were obtained based on the test on geocell made of novel polymeric alloy. Geocells made of other materials may have different behavior and should be evaluated by testing. ACKNOWLEDGMENTS This research was funded jointly by the University of Kansas (KU), Transportation Research Institute from Grant #DT0S59-06-G-00047, provided by the US Department of Transportation—Research and Innovative Technology Administration and PRS Mediterranean, Inc. in Israel. Their support is greatly appreciated. The loading apparatus used in this research was designed and fabricated by Mr. Howard Jim Weaver, the lab supervisor in the Department of Civil, Environmental, and Architectural Engineering (CEAE) at KU. 1165

Undergraduate student, Mr. Milad Jowkar, in the CEAE Department at KU assisted in the lab test. The authors are thankful for their great help. REFERENCES Bathurst, R.J. & Jarrett, P.M. 1989. Large-scale model tests of geocomposite mattresses over peat subgrades. Transportation Research Record 1188: 28–36. Chang, D.T., Chang, C.H., Kou, C.H. & Chien, T.W. 2008. Bearing capacity and resilient property studies for sandy soil with confinement of geocells. Proceedings of Transportation Research Board 87th Annual Meeting (CD-Rom), January 13–17, 2008, Washington, D.C. Giroud, J.P. & Han, J. 2004. Design method for geogrid-reinforced unpaved roads. I. Development of design method. ASCE Journal of Geotechnical and Geoenvironmental Engineering, 130 (8): 775–786. Giroud, J.P. & Noiray, L. 1981. Geotextile-reinforced unpaved road design” ASCE Journal of the Geotechnical Engineering Division. 107(GT9): 1233–1254. Han, J., Yang, X.M., Leshchinsky, D. & Parsons, R.L. 2008. Behavior of geocell-reinforced sand under a vertical load. Journal of Transportation Research Board, 2045: 95–101. Leng, J. & Gabr, M.A. 2006. Deformation-resistance Model for Geogrid-Reinforced Unpaved Road. Journal of the Transportation Research Board, No. 1975, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 146–154. Mengelt, M.J., Edil, T.B. & Benson, C.H. 2006. Resilient modulus and plastic deformation of soil confined in a geocell. Geosynthetic International. 13(5): 195–205. Pokharel, S.K., Han, J., Leshchinsky, D., Parsons, R.L. & Halahmi, I. 2009a. Experimental evaluation of influence factors for single geocell-reinforced sand. TRB 88th Annual Meeting, January 11 to 15, Washington, D.C. Pokharel, S.K., Han, J., Leshchinsky, D., Parsons, R.L. & Halahmi, I. 2009b. Behavior of geocellreinforced granular bases under static and repeated loads. Accepted for presentation and publication at the International Foundation Congress & Equipment Expo 2009, March 15–19, 2009, Orlando, Florida. Rea, M. & Mitchell, J.K. 1978. Sand reinforcement using paper grid cells. Regular meeting—Rocky Mountain Coal Mining Institute: 644–663. Shimizu, M. & Inui, T. 1990. Increase in the bearing capacity of ground with geotextile wall frame. Geotextiles, Geomembranes and Related Products, Den Hoedt (ed.), Balkema, Rotterdam: 254. Webster, S.L. 1979. Investigation of Beach Sand Trafficability Enhancement Using Sand-Grid Confinement and Membrane Reinforcement Concepts. Report GL-79–20 (1). U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS. Yuu, J., Han, J., Rosen, A., Parsons, R.L. & Leshchinsky, D. 2008. Technical review of geocell-reinforced base courses over weak subgrade. Proceedings of GeoAmericas, Cancun, Mexico, March 2 to 5, 2008: 1022–1030.

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Utilization of recycled materials

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The influence of virgin aggregate content on the strength and modulus of cold in place reclaimed asphalt pavement H. Wang & P. Hao Chang’an University, Xi’an, China

K. Zhang Wirtgen Group, Shanghai, China

ABSTRACT: Virgin crushed stone aggregate is often added to improve the gradation and increase the strength of the reclaimed asphalt pavement (RAP) materials treated with cement. The compaction, unconfined compressive strength (UCS), indirect tensile strength (ITS) and resilient modulus tests were conducted on 0%, 15% and 30% virgin aggregate content blended with RAP. Samples were treated using 3%, 5% and 7% 325# Portland cement respectively, and were cured for 7, 28 and 90 days. The results show that, with the increasing amount of cement content and virgin aggregate content, the optimum moisture content and maximum dry density of RAP/virgin aggregate blends will increase slightly. The increases of cement content, curing period and aggregate content will all lead to the increasing test values of UCS, ITS and resilient modulus. The proper cement content and virgin aggregate content were suggested around 5% and 15%, respectively, in this study. 1

INTRODUCTION

Recycling of pavement materials has become a viable alternative in road maintenance and rehabilitation. Experience has indicated that reclaimed asphalt pavement is a very beneficial approach from technical, economical, and environmental perspectives (Taha et al. 1999; Lee, et al. 2005; Johnson et al. 2006; Wu et al. 2006). Some of the advantages of utilizing reclaimed asphalt pavement include the retention of existing geometrics, conservation of resources, preservation of the environment and reduction in life-cycle cost. Based on incomplete data, it is estimated that as much as 91 million metric tons (100.1 million tons) of RAP may be produced during resurfacing and widening projects each year in the United States (Jason, 2005). Among the numerous RAP recycling approaches, RAP materials blended with some percent of virgin crushed stone aggregate and stabilized by cement are increasingly being adopted as road bases and sub-bases. The addition of cement to RAP and aggregate base material increases the strength and durability of the base layer (Guthrie et al. 2002). The authors of the research findings immediately cited above suggested that a 100% RAP aggregate should not be recommended for use as a base material unless stabilized with cement. Through compaction and UCS tests by Taha et al. (2002), cement stabilized RAP-virgin aggregate mixture is demonstrated to be a viable alternative to dense-graded aggregate used in road base construction. Two types of RAP materials (coarse and fine) were incorporated with Portland cement to produce concrete by Huang et al. (2005). The compressive and split tensile strength tests were employed in their research to evaluate the mechanical properties of hardened concrete, indicating that concrete made with RAP had a much higher toughness than concrete without RAP. The strength and stiffness of RAP/aggregate blends were tested by Los Angeles abrasion tests, direct shear tests and R-value tests (Mokwa et al. 2006), indicating that RAP blends exhibit decreased shear strength and decreased stiffness as the quantity of RAP is increased. Mokwa’s test results suggested limits should be established on the maximum amount of RAP blended in the mixture. A tube suction test was performed to access the strength and durability of RAP/aggregate 1169

blends (Guthrie et al. 2007), and the RAP contents in the range of 50 to 75 percent and a cement content of 1.0 percent were suggested in that case. According to the aforementioned research, the mechanical characteristics of RAP material have attracted a lot of attention, but different researchers have suggested different proper RAP contents based on their own applications. 2

OBJECTIVE AND SCOPE

The objective of this study is to investigate the proper virgin crushed stone aggregate content in the blends and to evaluate the strength and stiffness properties of the RAP/aggregate blends. UCS testing, ITS testing, and resilient modulus testing were conducted on three RAP/aggregate blends (100/0, 85/15 and 70/30) with 3 cement contents (3%, 5% and 7%). Three curing periods (7 days, 28 days and 90 days) were considered in these tests. 3

MATERIALS

3.1 Reclaimed asphalt pavement RAP material was collected in a pavement rehabilitation field in Liaoning, China, and the rehabilitation was conducted by Wirtgen cold recycler WR2500S. The test results of rotary extraction on the milled RAP (AASHTO T164, Method A) indicated an average asphalt content of 5% by weight of the mix. The recovered asphalt type was penetration grade 60–70. RAP materials should not be dried in a high temperature oven because of the propensity to become soft and clustered; thus they were dried in the conventional air in the laboratory. 3.2 Portland cement Portland 325# cement was used in the testing program. The setting time and the strength properties are listed in Table 1. 3.3 Gradation Three RAP/virgin aggregate mixtures, S0 (100/0), S15 (85/15) and S30 (70/30), were adopted in the laboratory test. The sieve analyses were performed on the three mixtures and virgin crushed stone aggregate in accordance with AASHTO T27 (see Figure 1). The percent passing of RAP material was about 50% for 4.75 mm sieve and 20% for 0.6 mm sieve, indicating that the pavement materials were crushed into small particles under repeated vehicle loading. The percent passing of 0.075 mm sieve was just 1.0% for the RAP, indicating the fine particles in the original mixture were coated onto coarse particles of the RAP. 4

TEST RESULTS AND DISCUSSION

4.1 Compaction testing Sample preparation: Three blended mixtures (S0, S15 and S30) were stabilized using 3%, 5% and 7% Portland 325# cement, respectively. The compaction test was performed by the Table 1.

Results

Setting time and the strength properties of the cement. Setting time (min.)

Compressive strength (MPa)

Flexural strength (MPa)

Initial

Final

3 days

28 days

3 days 28 days

163

420

15.2

35.4

4.7

1170

7.1

RAP/aggregate 100/0 RAP/aggregate 70/30

RAP/aggregate 85/15 Virgin aggregate

100

Percent passing (%)

90 80 70 60 50 40 30 20 10 0

0 .075 0 .15 0 .3

0 .6 1 .18

2 .36

9 .5

4 .75

13 .2 16

19

26 .5 31 .5

3 7 .5

Grain size (mm)

Figure 1.

Particle size distribution for reclaimed asphalt pavement (RAP) and virgin aggregates.

Table 2. Optimum moisture content and maximum dry density results of all blends. Optimum moisture content (%)

Maximum dry density (g/cm3)

Cement percent (%)

100% RAP

85% RAP

70% RAP

100% RAP

85% RAP

70% RAP

3 5 7

5.2 6.0 6.5

5.4 6.0 6.5

4.8 5.2 5.8

2.18 2.19 2.23

2.25 2.27 2.30

2.29 2.35 2.45

modified proctor testing procedure (AASHTO T180). The mold dimensions were 152 mm in diameter by 120 mm in height. The hammer weight was 4.5 kg, and it had a free-fall distance of 457 mm. Each mix was compacted in 3 layers with 98 blows per layer. Test results: The optimum moisture content (OMC) and maximum dry density (MDD) values are presented in Table 2. The data indicate that as cement content increases for each mixture, the OMC and MDD values will slightly increase. Greater cement content leads to greater water content for the cement hydrate, inducing a higher OMC. Meanwhile, as the density of cement is greater than the RAP, the greater cement content also leads to a higher MDD. Similarly, the maximum dry density will increase as more virgin aggregate is added to RAP, as the specific gravity of virgin aggregate is higher than that of the RAP. 4.2 Unconfined compressive strength testing Sample preparation: Samples were fabricated at 3%, 5% and 7% cement content with the optimum moisture content and maximum dry density by hydraulic press. The cylinder sample dimensions were 150 mm in diameter, and the ratio between diameter and height is 1:1. Nine duplicated samples were prepared for each mixture test. Samples were cured for 7, 28 and 90 days in sealed plastic bags in a temperature of 20 ± 2ºC and a 100 percent relative humidity curing room. The samples were soaked into water in the last day of curing. Test results: The results of the UCS testing conducted in this research are displayed in Table 3. The relationship between virgin aggregate content and UCS are listed in Figure 2 for 1171

Table 3. Unconfined compressive strength data. Curing period (d) 28

90

S0

3 5 7

2.1 2.7 3.6

2.9 3.5 4.9

3.8 4.9 6.2

S15

3 5 7

2.3 3.1 4.6

3.2 4.2 5.7

4.2 5.3 7.4

S30

3 5 7

2.4 3.9 5.5

3.3 4.7 6.7

4.6 5.7 8.6

7

Cement content 7% Cement content 5% Cement content 3%

5 UCS (MPa)

7

52.8%

27.8%

4

44.4% 3

18.5%

2

15 Vigin aggregate content (%)

16.3% 5 34.3% 4 3 0

30

a) Curing period 7 days

9

UCS (MPa)

36.7%

14.3% 19.1%

9.5% 0

Cement content 7% Cement content 5% Cement content 3%

6 UCS (MPa)

6

Cement content (%)

8.6%

13.8%

15 Virgin aggregate percent (%)

30

b) Curing period 28 days

8

Cement content 7% Cement content 5% Cement content 3%

7

14.5%

35.5%

6 20.4%

5

12.2% 13.2%

4 3

7.9% 0

15 Virgin aggregate percent (%)

30

c) Curing period 90 days

Figure 2.

Virgin aggregate content—unconfined compressive strength test results.

detailed discussion. The UCS increasing rates of RAP/virgin aggregate blends to those of the 100% RAP were also calculated and are listed in the figure. From Table 3 and Figure 2, it can be seen that at any cement content and at any curing period, the increasing virgin aggregate contents lead to higher UCS values. As the gradation 1172

of RAP material is relatively fine, the RAP blended with 10~30 mm virgin aggregate will have a more proper gradation, and the addition of virgin aggregate is beneficial to raise UCS. Meanwhile, the virgin crushed stone aggregate has a higher strength than the RAP, and the addition of virgin aggregate to RAP would raise the general UCS. At any curing period and any virgin aggregate content, the increasing of cement contents also leads to higher UCS values. But, excessive amounts of cement could induce the bigger possibility of shrinkage cracking of mixtures and lower economy efficiency. It is suggested not to exceed 6% if the requirement of designed strength can be met (Scullion, 2002). From the point of UCS increasing rate of RAP/virgin aggregate blends to 100% RAP, the cement content has more pronounced effect on the UCS at higher virgin aggregate content. At the 3% cement content, the UCS increasing rate increases from 9.5% to 19.1% when the virgin aggregate content increases from 15% to 30%, while at the 7% content, the UCS increasing rate increases from 27.8% to 52.8%. When the cement content is low (blends used as sub-base), the blending of virgin aggregate will have relatively smaller influence on the increasing of UCS, and/thus the virgin aggregate content can be reduced properly to decrease the construction cost. The UCS increasing rate becomes less pronounced with increases in curing periods. Take the 5% cement content blend as an example; the increasing rate decreases from 44.4% to 34.3% and 20.4% from the curing period of 7 days to 28 days and 90 days, respectively. So it is important to provide an effective curing environment (sufficient moisture and proper temperature) for the blends in the first several curing days in field construction. 4.3 Indirect tensile strength testing Sample preparation and compaction for indirect tensile strength testing were similar to the above section on UCS sample preparation. The results of the ITS testing conducted on 90 curing days samples are listed in Figure 3. The ITS increasing rates of RAP/virgin aggregate blends to those of the 100% RAP were also calculated and are listed. Similar to the UCS, the increasing of both cement contents and virgin aggregate contents leads to higher ITS values. The addition of cement and virgin aggregate is obviously beneficial to raise the ITS values of the RAP/virgin aggregate blends. In contrast to the UCS, from the point of ITS increasing rate of RAP/virgin aggregate blends to 100% RAP, the cement

Cement content 7% Cement content 5% Cement content 3%

1.0

34.2% 21.1%

ITS (MPa)

0.8

39.6%

0.6 25%

0.4 25.9%

0.2

0

15 Virgin aggregate content (%)

Figure 3.

Virgin aggregate content—indirect tensile strength test results.

1173

40.7%

30

content has less pronounced effect on the ITS at higher virgin aggregate content. At the 3% cement content, the ITS increasing rate increases from 25.9% to 40.7% when the virgin aggregate content increases from 15% to 30%, while at the 7% content, the UCS increasing rate increases from 21.1% to 34.2%. The cement contributes more to the UCS than to the ITS of the RAP/virgin blends. It should be kept in good balance between the cement content and virgin aggregate content to achieve the best increasing efficiency of the blends’ strengths.

4.4 Resilient modulus testing Resilient modulus is an important index to characterize the mechanical property of pavement material, and is also a major parameter in the pavement structure design. Sample preparation and compaction for resilient modulus testing were similar to UCS and ITS sample preparation. The results of the resilient modulus testing conducted on 90-day curing days samples are listed in Figure 4. The resilient increasing rates of RAP/virgin aggregate blends to those of the 100% RAP were also calculated and are listed. Similar to the UCS and ITS, the increasing of both cement contents and virgin aggregate contents leads to higher resilient modulus values. From the point of resilient modulus increasing rate, the resilient modulus has the same tendency with UCS and a different tendency from ITS. The cement content has more pronounced effect on the resilient modulus at higher virgin aggregate content. At the 3% cement content, the resilient modulus increasing rate increases from 15.8% to 23.6% when the virgin aggregate content increases from 15% to 30%, while at the 7% content, the resilient modulus increasing rate increases from 20.1% to 27.5%. The base resilient modulus (stiffness) should be designed in proper range. The pavement will be subjected to high tension stress and strain and induce pavement cracking with a low resilient modulus base, while the base material itself will be subjected to shrinkage cracking by moisture loss and temperature variation with an excessively higher resilient modulus (George et al. 2002). Cement content should be kept in proper range to keep good balance between increasing strength and reducing shrinkage. Virgin aggregate content should also be kept in proper amount to keep good balance between increasing strength, raising modulus and reducing economic cost, controlling construction segregation. The Portland Cement Association (PCA) suggests a target UCS of between 2.1 MPa (300 psi) and 3.1 MPa (450 psi) after 7 days of curing (George

Resilient modulus (MPa)

2500

Cement content 7% Cement content 5% Cement content 3%

27.5%

2000 20.1% 24.4%

1500 17.9% 23.6%

1000

15.8%

0

15 Virgin aggregate content (%)

Figure 4.

Virgin aggregate content—resilient modulus test results.

1174

30

et al. 2002). According to the UCS, ITS and resilient modulus testing results, considering the mechanical characteristics and economic cost of cement treated cold in place reclaimed materials, the cement content and virgin aggregate content is suggested around 5% and 15%, respectively, in this study. 5

CONCLUSIONS

The compaction test, UCS, ITS and resilient modulus tests were performed to study the proper range of virgin aggregate content in the cold in-place recycled materials stabilized with cement. Through the laboratory tests, the following conclusions were reached: 1. The optimum moisture content and maximum dry density of RAP/virgin aggregate blends will slightly increase as the amounts of cement content and virgin aggregate content increase. 2. The increasing of cement content, curing period and aggregate content will all lead to increasing test values of UCS, ITS and resilient modulus. From the point of testing value increasing rate of the blends to the 100% RAP, the cement content has more pronounced effect on the UCS and resilient modulus at higher virgin aggregate content, while less pronounced effect on the ITS. The cement content contributes more to the UCS and resilient modulus than the ITS. 3. To keep balance between increasing strength and reducing shrinkage, to maintain the coordination between the increasing strength and controlling construction segregation, the proper cement content and virgin aggregate content is suggested around 5% and 15%, respectively, in this study. ACKNOWLEDGEMENT This work was supported by the funds of Natural Science Found Committee (NSFC) of China (No. 50878023). REFERENCES Berthelot, C., Marjerison, B., Houston, G., McCaig, J., Warrener, S. & Gorlick, R. 2007, ‘Mechanistic comparison of cement- and bituminous-stabilized granular base systems’, Transportation Research Record, no. 2026, pp. 70–80. Chen, J.S., Huang, C.C., Chu, P.Y. & Lin, K.Y. 2007, ‘Engineering characterization of recycled asphalt concrete and aged bitumen mixed recycling agent’, Journal of Materials Science, vol. 42, no. 23, pp. 9867–9876. George, K.P. Minimizing Cracking in Cement-Treated Materials for Improved Performance. Publication RD123. Portland Cement Association, Skokie, IL, 2002. Guthrie, W.S., Sebesta, S. & Scullion, T. 2002. Selecting optimum cement contents for stabilizing aggregate base materials. Report 4920–2, Texas Transportation Institute, Texas A & M University System, College Station, Texas. Guthrie, W.S., Cooley, D. & Eggett, D.L. 2007, ‘Effects of reclaimed asphalt pavement on mechanical properties of base materials’, Transportation Research Record, no. 2005, pp. 44–52. Huang, B., Shu, X. & Li, G. 2005, ‘Laboratory investigation of portland cement concrete containing recycled asphalt pavements’, Cement and Concrete Research, vol. 35, no. 10, pp. 2008–2013. Jason, H., Recycled roadways. Public Roads, 68, 4: 9–17. Johnson, D.R., Jackson, N.M. & Sauer, T.M. 2006, ‘Field evaluation of pavement rehabilitation using full-depth reclamation’, in Proceedings of the 2006 Airfield and Highway Pavement Specialty Conference, pp. 824–835. Lee, K.W., Huston, M. & Brayton, T. 2005. “Development of Performance Based Mix Design for Cold In-Place Recycling (CIR) of Bituminous Pavements Based on Fundamental Properties,” Research Report No. FHWA-IF-05-014, Federal Highway Administration, Washington, D.C. Mokwa, R.L., Peebles, C.S. & Robinson, E. 2006, “Strength, stiffness, and compressibility of RAP/ aggregate blends,” in Geotechnical Special Publication, pp. 247–255.

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Scullion, T., 2002 “Precracking of soil-cement bases to reduce reflection cracking: Field investigation.” Transportation Research Record, n1787, pp. 22–32. Taha, R., Ali, G., Basma, A. & Al-Turk, O. 1999, ‘Evaluation of reclaimed asphalt pavement aggregate in road bases and subbases’, Transportation Research Record, vol. 1, no. 1652, pp. 264–269. Taha, R., Al-Harthy, A., Al-Shamsi, K. & Al-Zubeidi, M. 2002, ‘Cement stabilization of reclaimed asphalt pavement aggregate for road bases and subbases’, Journal of Materials in Civil Engineering, vol. 14, no. 3, pp. 239–245. Wu, S., Qiu, J., Shui, Z. & Wang, H. 2007, ‘Comparison of dynamic and fatigue properties of virgin and recycled asphalt mixture’, Key Engineering Materials, vol. 348–349, pp. 885–888.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Unbound crushed concrete in high volume roads—evaluation of field behavior and structural performance J. Aurstad & J.E. Dahlhaug Norwegian Public Roads Administration, Trondheim, Norway

G. Berntsen NCC Roads AS, Oslo, Norway

ABSTRACT: In Norway, recycled concrete aggregates were introduced in design codes for road construction in 2005, including material specifications. Until then, utilisation of these materials was limited due to the fact that the mechanical properties of aggregates in many cases did not comply with the specifications concerning mechanical strength. However, a number of field projects have revealed good functional properties (proven suitability), showing that traditional test methods for mechanical properties are clearly not suitable for this kind of materials. A proper evaluation should be based on performance-related (functional) tests. The paper discusses some of these field-lab contradictions with reference to a field trial at highway E6 south of Trondheim where recycled crushed concrete aggregates (RCA) has been used as sub-base layer since 2003 in a pavement designed for rather heavy traffic (Annual Daily Traffic > 10000). Several field and laboratory tests were conducted before, during and after construction. Since then the structural performance and the surface characteristics have been followed up frequently. The registrations so far show very promising results. The project has given valuable inputs to Norwegian pavement design standards and has already encouraged further use of recycled/ secondary materials in Norway. 1

INTRODUCTION

In Norway, recycled concrete aggregate has recently (2005) been introduced in design codes for road construction, including material specifications. A number of field projects have revealed good functional properties (proven suitability), despite the fact that the mechanical properties of the materials in many cases do not comply with specifications concerning mechanical strength. Many traditional test methods for mechanical properties are clearly not suitable for this kind of materials. A proper evaluation should therefore be based on performance-related, functional tests (Reid 2000, Aurstad & Hoff, 2002). Late autumn 2003 two test sections with unbound crushed concrete aggregates as subbase layer were constructed as part of a new Highway E6 at Melhus, 20 km south of Trondheim, Norway. Two different concrete materials/fractions were tried out; 0–100 mm and 20–100 mm. A number of field measurements were conducted, both during and after construction, in order to gain further practical experience with these kinds of materials. Parallel to the field investigations, an extensive laboratory program was carried out on the same materials. Since then the structural performance and the surface characteristics have been followed up frequently, including FWD measurements (with backcalculation of layer stiffnesses), rutting and evenness (IRI) measurements etc. The results from the registrations so far are summerized in this paper.

1177

2

TEST SECTIONS

The E6 highway is the “backbone” of the Norwegian road network, stretching 2600 km from south-east to the very north of Norway. At this specific site at Melhus, the road is designed for approximately 12.500 vehicles/day (annual daily traffic ADT = 12.500). The standard construction for this new road according to Norwegian design guides (Handbook 018) is 15 cm of asphalt on top of 65–85 cm crushed rock materials (dependant on subgrade) as shown in Figure 1. In order to compare the two alternative crushed concrete materials, two adjacent sections of 80 m length were constructed on the test site, as shown in Figure 2. On these test sections the standard construction was modified by replacing the crushed rock sub-base (see Figure 1) with crushed concrete sub-bases of the same thickness. That is, the bearing capacities of these materials were assumed to be equivalent. The standard construction (see Figure 1) was used as reference both north and south of the crushed concrete sections. 3

MATERIALS

The origin of these alternative sub-base materials was discarded pre-fabricated element concrete, as shown in Figure 3. The concrete elements were crushed in a mobile crushing mill which also separated (most of) the reinforcement. The crushed materials were then fractionated into the two required products, 0–100 mm and 20–100 mm (Aurstad et al. 2005). After transportation to the test site, the materials were sprinkled with water before compaction in two layers, each about 30 cm (see Figure 4).

Figure 1.

Pavement construction at E6 Melhus, layer details (shown for two different subgrades).

Reference Section S (standard constr.)

Profile Figure 2.

Section 1 (crushed concrete subbase, fraction 0–100 mm)

0

20

40

60

Section 2 (crushed concrete subbase, fraction 20–100 mm)

80

Test sections, E6 Melhus.

1178

100

120

140

Reference section N (standard constr.)

160 (meters)

Figure 3.

Element concrete stockpile.

Figure 4. Sprinkling of the crushed concrete materials was recommended before paving and compaction.

Figure 5.

In place detection of density/unit weight (sand replacement method).

Some knowledge could be gained almost instantly: Workability: The contractor on this job had no previous experience with recycled materials and was rather sceptical. This caused discussions regarding procedures, type of rollers, need of water sprinkling etc. The effect of abundant water addition was soon clearly demonstrated, both visually and by levelling and plate bearing measurements. The materials performed very well during laying and compaction and only minor crushing and disintegration was observed. The workers were certainly positively surprised by the behaviour of the materials. Contaminants: The importance of “clean”, well-sorted materials was also clearly demonstrated; during the first two hours of construction work three truck tires were punctured by remaining reinforcement steel bars! The compaction was closely monitored with levelling and plate bearing tests for every two passes of the roller (up to 10 passes). Material samples were collected before and after compaction for sieve analyses. After compaction, the in situ dry densities were detected as shown in Figure 5. These values were to be used as input parameters to the laboratory tests that followed. 1179

(a)

Figure 6.

(b)

Crushed concrete before compaction; 0–100 mm (a) and 20–100 mm (b).

Particle size distributions for the two crushed concrete materials are shown in Figure 6. Five samples from each material were sieved, the bold lines show the medium curves (also used as target curves for the triaxial tests, see 4.1). The curves comply with grading requirements for granular sub-base materials in the Norwegian specifications. 4

LABORATORY INVESTIGATIONS

4.1 Test methods There is still some way to go to make alternative materials fully accepted, also in Norway. Partly this has to do with the fact that the materials are rejected in traditional lab tests, and do not in all cases comply with specifications concerning mechanical strength. At least some of the traditional test methods for mechanical properties are clearly not suitable for this kind of materials. To get a picture of this for the Melhus materials, a laboratory program was carried out using both traditional (empirical) and new performance-based (functional) test methods. The “traditional” investigations were: • • • • •

Grading (sieve analyses); samples taken before and after field compaction Density and water absorption Laboratory compaction characteristics; Modified Proctor and Gyratory compaction Resistance to fragmentation; Impact test, Los Angeles, Gyratory compaction CBR

The “performance-based” investigations were based on triaxial tests: In order to make laboratory investigations relevant and comparable to field conditions, the materials should be tested as layers rather than as particles. Also the applied test loadings should be comparable to real traffic. Figure 7 shows the cyclic triaxial test apparatus developed by NTNU/SINTEF in Trondheim, which has been used for testing of different granular materials in Norway the recent years, including the Melhus RCA materials. This equipment allows for rather large scale sylindrical samples (d = 300 mm, h = 600 mm), thus materials with particle size up to about 60 mm can be tested (Skoglund 2002, Hoff 2004). The tests were carried out in accordance with EN 13286-7 “Unbound and hydraulically bound mixtures Part 7: Cyclic load triaxial test for unbound mixtures”. The specimens were compacted with same water content and to same density as measured in field (Figure 5). Open-graded and dense-graded material were compared by down-scaling the field materials from 0–100 mm/20–100 mm to 0–63 mm/20–63 mm. The testing was performed at stress levels equivalent to the sub-base conditions in field (on a road with heavy traffic). 1180

Figure 7. Large-scale triaxial test apparatus with mounted specimen of crushed concrete aggregate from E6 Melhus.

OG: Open-graded (20–60 mm) DG: Dense-graded (0–60 mm) Askøy: Reference crushed stone mat. (high quality)

Figure 8.

Resistance to permanent deformations; crushed concrete E6 Melhus.

From repeated load triaxial tests both elastic stiffness and resistance to permanent deformations can be derived. The elastic stiffness is expressed by E-modulus for a given mean stress level, while the deformation properties are expressed by elastic and failure angles, see Figure 8. 4.2 Test results In short, the laboratory investigations led to the following conclusions: Mechanical strength: The material was of very good quality; both Los Angeles values (LA 25–27) and impact values satisfy the Norwegian requirements set up for base and sub-base materials of crushed stone. Water absorption tests showed that approximately 5% water might be absorbed due to the porosity. This should be compensated by abundant water addition to improve workability 1181

and compactability and also reduce crushing and disintegration during construction. (This was clearly demonstrated in field during laying of the test sections.) Fragmentation tests by use of gyratory compactor revealed that crushing mainly occured within the coarser particles, only minor increases in fines were detected. Shear strength: CBR tests were carried out on the 0–19 mm fraction of the 0–100 mm material. The results revealed good bearing capacity/shear strength; CBR 120–130. Triaxial tests: Elastic stiffness and deformation resistance was investigated by use of the large-scale dynamic triaxial test apparatus. Stiffness: The results revealed high elastic stiffness values compared to ordinary gravel or crushed rock materials; E 350–650 MPa, with highest values for the open-graded 20–60 mm material (OG in Figure 8). Deformation: Both elastic and failure angles were higher than for natural/ordinary materials. This implies that the crushed concrete materials should have very good properties regarding bearing capacity and stability (permanent deformation resistance). (Here also the open-graded specimens (OG in Figure 8) got higher initial values than the dense-graded (DG). This picture seems to change as time goes by, see 5.1–5.2). Relations to field: Sieve analyses showed that the triaxial test procedure gave a similar disintegration of the materials as the laying and compaction in field. Thus, with the same densities and water contents, the stiffness and deformation results from the lab testings should give a relevant picture of the in situ properties and hence an indication of the long term performance. The immediate expectations after these initial lab testings were therefore that these recycled concrete materials should perform well as sub-base layers, also with traffic levels as high as on E6 Melhus (Aurstad et al. 2006). But of course, many are anxious to see the real long term performance of the road.

5

FIELD INVESTIGATIONS, LONG-TERM PERFORMANCE

After construction of the E6 highway at Melhus in 2003, the road has been followed up with frequent field measurements and registrations. This Melhus project opened for (quite) extensive use of secondary materials. Thus both crushed asphalt, crushed concrete and lightweight foamglass materials have been utilised in the construction. Special emphasis however has been put on the test sections with recycled concrete aggregates. As described, these materials behaved very well in the construction phase. And the laboratory tests also indicated good material quality and engineering properties. However, before “new” materials can be included in design guides and material standards etc, some proven durability and long-term field performance has to be demonstrated and documented. The following measurements and registrations have been conducted on the test sections the past years: – – – – – –

Plate bearing tests (mainly as compaction control, during and right after construction) FWD measurements Calculated axle load capacities (based on FWD data) Backcalculated construction layer stiffnesses (based on FWD data) Rutting (transversal evenness), ALFRED high speed profilometer Longitudinal evenness (IRI), ALFRED high speed profilometer

5.1 Bearing capacity, axle loads Bearing capacity on Norwegian roads are often reported as “allowable axle loads” (in tons), a measure calculated from FWD data. Normally these registrations are done in spring (thawing period), that is in the weakest periods of the construction. Figure 9 shows the latest results from FWD measurements on the E6 Melhus road. Norwegian roads are normally designed for a bearing capacity of 10 tons. The results reveal substantial higher bearing capacity on the test sections with RCA, compared with the standard 1182

30 28

Bearing capacity (tons)

26 24 22 20 18 16

Reference constr (S)

RCA 0-100 mm

RCA 20-100 mm

Reference constr (N)

14 12

3,900

3,880

3,860

3,840

3,820

3,800

3,780

3,760

3,740

3,720

3,700

3,680

3,660

3,640

3,620

3,600

3,580

3,560

3,540

3,520

3,500

10

Km 28.03.2007

Figure 9.

03.04.2008

E6 Melhus; bearing capacity, thawing period (allowable axle loads, tons).

1600 1400 1200

MPa

1000 800 600 400 200 0 3450

3500

3550

3600

3650

3700

3750

3800

3850

3900

3950

Profile (meters) Spring 2005

Figure 10.

Spring 2008

Sub-base stiffnesses at E6 Melhus (backcalculated E-moduli from FWD measurements).

reference constructions (both north (N) and south (S) of the test site). The section with RCA sub-base material fraction 0–100 mm seems to have the highest values. 5.2 Bearing capacity, backcalculated sub-base moduli From the FWD registrations, the E-moduli of each construction layer on the road have been backcalculated from the recorded deflections using linear elastic models. Figure 10 shows some of the 2005 and 2008 results for the sub-base materials. The different sections/materials can be identified from the profiles (same as Figure 9). The average values are summerized in Table 1. The first results (based on FWD measurements performed on pavement surface immediate after construction) showed that the test sections with crushed concrete and the reference sections with crushed rock material were more or less equivalent (E = 150 MPa). Since then, as shown in Table 1 and Figure 10, the crushed concrete layers have developed substantially higher E-moduli than the crushed rock material, which still is at about the same level as after construction. Most evident are the results for the dense 0–100 mm concrete material that is the material containing fines. 1183

Table 1.

Sub-base stiffnesses at E6 Melhus (backcalculated E-moduli from FWD measurements). E-modulus (MPa) 2005

Section 1 (RCA 0–100 mm) Section 2 (RCA 20–100 mm) Reference sections (crushed rock 20‒200 mm)

2008

Left line

Right line

Average

Left line

Right line

Average

904

875

889

1339

1037

1188

344

275

310

437

270

354

158

133

145

151

172

161

Hardening effects in unbound crushed concrete layers have been reported in many projects the recent years, and then also clearly demonstrated here. A specific chemical study, for instance delayed hydration of the cement powder, has not been part of the project. 5.3 Road evenness The surface condition of the Norwegian road network is closely monitored. Both longitudinal and transversal evenness (rutting) is measured at least once a year (national and county roads), combined with photos for every 50 m (Ferne, 2008). These data are stored in a National Road Data Bank and are used for different purposes; statistics, overall and detailed budgeting, pavement management. Insufficient bearing capacity in the sub-base may lead to deformations, therefore monitoring of rutting and also longitudinal evenness (IRI) is of special interest on roads with alternative materials/technical solutions, such as E6 Melhus. Evenness data for E6 Melhus is shown in Figures 11 and 12. Threshold (“trigger”) rut depth value for maintanence/repaving on high volume pavements in Norway is 25 mm. Hence, no dramatic development can be observed on the test sections. The rutting on the alternative constructions is equal to the reference constructions. The major part of these ruts comes from the winter season (there is quite extensive pavement surface wear from studded winter tyres in Norway). Threshold (“trigger”) IRI value for maintanence/repaving on high volume pavements in Norway is IRI = 4.0. All values in Figure 12 are far below (better than) this level. And the sections with RCA are in fact the most even parts. 6

SUMMARY AND CONCLUSIONS

On a new highway E6 south of Trondheim, Norway, unbound crushed concrete has been tried out as alternative sub-base material. Two test sections were established in 2003 in order to compare the fractions 0–100 mm (dense-graded) and 20–100 mm (open-graded) RCA. Both materials came from the same source; a stockpile of discarded new element concrete. During construction the material properties in situ were studied by different kinds of measurements; levelling, plate bearing tests and FWD tests. One of the objectives was to gain more practical experience with these materials (handling, workability, compaction etc.). It was demonstrated that these materials can behave very well during construction, given that some precautions are taken (good separation from reinforcement, sufficient water addition, careful laying and compaction etc.). Another objective was to link field and laboratory behaviour. An extensive laboratory program was carried out including both empirical and performance-based tests. The performance-based laboratory investigations showed very promising values, especially the stiffness and deformation results from the large-scale triaxial device were positive. 1184

20 18

Rut depth (mm)

16 14 Ref south

12

RCA 0 –100

10

RCA 20 –100

8

Ref north

6 4 2 0 Nov 2004

Figure 11.

July 2005

Oct 2005

May 2006

Sept 2006

May 2007

Aug 2007

May 2008

July 2008

Rutting (transversal evenness), measured by ALFRED device.

IRI (Intern. Roughness Index) m/km

1,50 1,25 1,00

Ref south RCA 0 –100

0,75

RCA 20 –100 Ref north

0,50 0,25 0,00 Nov 2004

July 2005

Oct 2005

May 2006

Sept 2006

May 2007

Aug 2007

May 2008

July 2008

Figure 12.

Longitudenal evenness (IRI), measured by ALFRED device.

Figure 13.

New E6 Melhus, autumn 2003 and summer 2008.

1185

During the years after construction, field measurements have been repeated frequently to monitor the long-term behaviour of the constructions. Any detection of hardening effects in the crushed concrete layers has been of special interest for the follow-up programme. The main conclusions are as follows (after 5 years of field monitoring): Bearing capacity: FWD measurements after construction have shown substantial increase in bearing capacity and stiffness on the crushed concrete sections. This is most evident on the section with 0–100 mm material, where backcalculations give crushed concrete E-moduli in the order of 900–1400 MPa. Evenness: Ultrasonic and laser measurements on the road have so far revealed very satisfying surface conditions. IRI measurements show a very smooth and high quality surface over the test sections; IRI = 0,5–1,0. Also regarding rutting no differences can be observed between the RCA sections and the reference sections. (NB! The major contributor to the rutting on these pavements is studded winter tyre wear, which is a surface mechanism.) These measurements will be repeated frequently to monitor the long-term behaviour of the constructions. Any further hardening effects will hopefully be detected by the follow-up programme. To be a “waste material” this concrete was of very good quality (structural elements, clean recycling stream). Thus, the results may not be transferable to all projects. But, according to the results from this project, recycled crushed concrete material can perform excellent as unbound sub-base layer in roads, even with traffic levels as high as on E6 Melhus. REFERENCES Aurstad J., Aksnes J., Berntsen G., Dahlhaug J., Petkovic G. & Uthus N. Unbound crushed concrete in high volume roads—a field and laboratory study, 5th International Conference on Research and Practical Applications Using Wastes and Secondary Materials in Pavement Engineering, 22–23 February 2006 John Moore University, Liverpool, UK. Aurstad, J. & Hoff, I. Crushed asphalt and concrete as unbound road materials—Comparisons of field measurements and laboratory investigations Proceedings of the 6th International Conference on the Bearing Capacity of Roads, Railways and Airfields, Lisbon, Portugal 2002. Ferne, B. et al. Managing Road Evenness PIARC Technical Committee C4.2 Vehicle/Road Interaction 2008. Hoff, I. GARAP—Evaluation of different laboratory compaction methods for preparation of cyclic triaxial samples, SINTEF Report STF22 A04339 2004. Norwegian Public Roads Administration: “Håndbok 018 Vegbygging”. Design guide for road construction 2005 (in Norwegian). Reid, J.M. The use of alternative materials in road construction International Symposium on Unbound Aggregates in Roads—UNBAR 5, Nottingham, England 2000. Skoglund, K.A. A Study of Some Factors in Mechanistic Railway Track Design Ph.D Thesis 2002: 54, NTNU Trondheim 2002.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Expansive characteristics of RAP materials for use as aggregates in the pavement substructure layers D. Deniz, E. Tutumluer & J.S. Popovics Department of Civil and Environmental Engineering, University of Illinois, Urbana, Illinois, USA

ABSTRACT: This paper is focused on the expansive properties of reclaimed asphalt pavement (RAP) that may be used as pavement base materials in the state of Illinois. Different recycled hot mix asphalt materials were evaluated for use as aggregates in unbound pavement layers by assessing the differences in expansion potentials between recycled and virgin aggregates. Significant expansion levels have been found for RAP materials containing high percent of steel slag aggregates. This expansion has been attributable to hydration of the calcium and magnesium oxides in the recycled steel slag aggregate when exposed to water. The results of the expansion tests suggested the use of RAP materials containing high percentages of steel slag aggregates may have to be avoided in the pavement substructure layers depending upon the level of expansion. 1

INTRODUCTION

The use of recycled materials in pavements has become an increasingly widespread practice. This is especially true for hot mix asphalt (HMA) and Portland cement concrete (PCC) materials that are milled off the existing road surfaces and recycled for reuse in pavement construction. A viable solution for deposing of these recycled materials is to incorporate them into base and subbase applications for highway construction. Potential savings in construction cost and time has made the use of such recycled HMA and PCC aggregates an attractive alternative to highway engineers. This practice has been studied by several researchers as well as many state highway agencies (e.g. O’Mahony et al., 1991; Senior et al., 1994; Hudson et al., 1996; Cross et al., 1996; Garg and Thompson, 1996; Maher et al., 1997; Simon, 1997; Taha et al., 1999, Bennert et al., 2000, Chini et al., 2001, Taha et al., 2002). Local recycling of construction and demolition debris has also been increasing at an elevated rate. Recycled materials have been tested with varying degrees of success. However, the most promising is the use of iron and steel slag since it is available, economical and it has some excellent aggregate properties. Steel slag, a by-product of steel making, has been available as an aggregate in granular base, embankments, engineered fill, highway shoulders, and HMA pavements since 1970s. Steel slag consisting of calcium carbonate is broken down to smaller sizes to be used as aggregates in pavement HMA and base layers. They are particularly useful in areas where high frictional properties are required, such as HMA surface courses, and good-quality aggregate is scarce. However, steel slag may contain free lime and magnesia, CaO and MgO, which may cause the slag to be expansive when reacted with water. Therefore, steel slag is not generally recommended for use in rigid confined applications. Reclaimed asphalt pavement (RAP) is the reprocessed HMA pavement material containing asphalt and aggregates. RAP can be obtained from central RAP processing facilities where asphalt pavements are crushed, screened, and stockpiled. Processed RAP consists of high quality, well-graded aggregates coated by asphalt cement. Currently, the use of RAP is not allowed in the pavement substructure layers according to Illinois Department of Transportation (IDOT) specifications. Whether or not this is a major concern for Illinois has been recently studied by first successfully identifying the expansive nature of RAP sources statewide and secondly by establishing guidelines for blending recycled and virgin aggregates 1187

for the pavement substructure use. This paper, therefore, describes findings from such an evaluation of the expansion potential of steel slag commonly found in RAP materials in the state of Illinois. 2

USE OF RAP AGGREGATE AS A GRANULAR BASE MATERIAL

RAP has been already used as granular base or subbase materials in pavement structures (e.g., Garg and Thompson, 1996; Maher et al., 1997; Bennert et al., 2000; Chini et al., 2001). Garg and Thompson (1996) conducted a field testing research program to investigate the potential of using RAP as a pavement base. This study demonstrated that the performance of the RAP base was comparable to that of a crushed stone base. A study by Taha et al., (1999) recommended blending granular RAP with virgin aggregates in order to attain the proper bearing strengths since the RAP bearing capacity is usually lower than that of conventional granular aggregate bases. As conventional granular aggregate content increased, dry density and California Bearing Ratio (CBR) values increased (Taha et al., 1999). Therefore, it is important to characterize and quantify the expected range of RAP properties prior to application. Recent experiences with base course volume changes of up to 10 percent or more has been attributable to hydration of the calcium and magnesium oxides in the recycled steel slag aggregate when water was encountered in the pavement base layer (Collins and Ciesielski, 1994). Depending upon the level of expansion and the material gradation, dense graded aggregate base applications under pavements and structures may have to be avoided. This is partly due to the fact that free calcium and magnesium oxides are not completely consumed in the steel slag during steel manufacturing, and there is general agreement in the technical literature that the hydration of unslaked lime (CaO) and magnesia (MgO) in contact with moisture is largely responsible for the expansive nature of most steel slags (Collins and Ciesielski, 1994). The free lime hydrates rapidly and can cause large volume changes over a relatively short period of time (weeks), while magnesia hydrates much more slowly and contributes to long-term expansion that may take years to develop. The potential expansion depends on the origin of the slag, grain size and gradation, and the age of the stockpile (Rohde et al., 2003). Therefore, steel slag aggregate (SSA) generally yields difficulties in confined construction applications containing steel slag aggregate due to its expansion tendency. On the other hand, steel slag aggregates have sufficient material properties including favorable frictional properties, high stability, and good durability with resistance to stripping and rutting. Therefore, they can be considered as a good performing base material. If the tendency to expand can be controlled by some stabilization techniques, the use of steel slag aggregates will be beneficial, particularly in the substructure layers of pavements. Previous research has proven that the steel slag can be safely used for road construction if it is sufficiently slaked. The conventional means of achieving this is to weather the material in stockpiles for a period of time sufficient to ensure the stabilization of potentially expansive systems (Rohde et al., 2003). The minimum stocking time depends on the expansive system content and climatic characteristics (the distributions of temperature and rainfall and the degree of air moisture saturation throughout the year) and ranges from 3 to 12 months (Machado, 2000). Most highway departments require that steel slags be aged or cured for at least 6 months before they are used (Gupta et al., 1994). In Brazil, 6 months of weathering in stockpiles has been adopted for exposing steel slag aggregates to moisture (Institute of Roads Research-Brazilian National Department of Roads, 1990). Three key steps recommended by Juckes (2003) for the effective use of SSA are: 1. some pre-treatment of the slag is usually necessary (such as weathering); 2. a test is necessary that reliably predicts the behavior in use, within a reasonable time. This is commonly an expansion test; 3. calibration of the test is necessary so that test results can provide a useful distinction between material which is suitable and that which is not; this is normally achieved by linking laboratory tests to road trials. 1188

3

TESTING OF ILLINOIS RAP MATERIALS FOR EXPANSIVE CHARACTERISTICS

3.1 Materials used in expansion tests The increasing proportions of RAP stockpiles found throughout Illinois make such uses of RAP materials in pavement base/subbase courses economical and worthwhile. Information was gathered on the types, sources, and properties of both virgin aggregates and RAP materials primarily used in Illinois. The research methodology considered evaluating through laboratory testing the differences in expansion characteristics between RAP materials and virgin aggregates. Such differences would affect the laboratory testing conditions and pavement performance. Accordingly, it was decided to use 7 RAP materials and 10 different virgin aggregates to conduct tests on and investigate expansion characteristics in this study. Table 1 gives the seventeen materials selected to be studied in the project for expansive characteristics. Each material was received in 40-lb. (178-N) bags. The SSA obtained from District 1, labeled as “Steel Slag Inland,” had two different porous structures. By visual inspection, they were separated as porous and nonporous steel slag aggregates, as appropriately referred to in Table 1. 3.2 Expansion testing procedure Both selected RAP materials and the virgin aggregates were tested for expansion potential in accordance with ASTM D4792-00, “Potential Expansion of Aggregates from Hydration Reactions.” The ASTM D4792-00 test method covers the determination of potential volume expansion of dense graded compacted aggregates that contain components susceptible to hydration and consequent volume increase, such as, free calcium and magnesium oxides that occur in steel slag and other materials. This test method consists of measuring the volume expansion of compacted specimens following the general procedures of ASTM D1883, the California Bearing Ratio (CBR) test procedure. According to the directions given in this expansion test method, the volume expansions of compacted specimens were therefore measured following the general procedures of ASTM D1883, the CBR test procedure. The compaction method suggested in ASTM D4792-00 is the standard Proctor test procedure (ASTM D698) as far as the applied compactive effort is concerned and the three layers used in the CBR mold. However, a modification related to compaction effort was made in the test procedure. Specimens prepared in the CBR molds were compacted in three layers with 56 blows per layer using a modified Proctor hammer with 4-in. (101-mm) contact surface. The compactive effort consistently used in all the expansion tests was therefore in between the standard Proctor (ASTM D698) and the modified Proctor (ASTM D1557) efforts. Considering that granular materials in unbound base/subbase layers are often compacted closer to modified Proctor compactive effort, the approach taken was deemed acceptable. Further, expansion test results

Table 1.

Materials studied for expansive characteristics.

RAP aggregates

Virgin aggregates

• • • • • • •

• • • • • • • • • •

Surface Binder RAP with 60% SSA Surface RAP with 92% SSA ACBF Slag RAP Gravel-Crushed Stone RAP (ALL-FRK) Gravel RAP (Cur-Cl) Steel Slag RAP SMA RAP from IDOT District 1

1189

Porous Steel Slag from IDOT District 1 Nonporous Steel Slag from District 1 Gravel-Dolomite (Meyer) Limestone from R27-1 Research Project Dolomite from R27-1 Research Project Siliceous Gravel from R27-1 Research Project Dolomite Crushed Concrete from District 1 Gravel Crushed Concrete from District 1 Steel Slag from District 4 ACBF Slag from District 8

obtained with both the standard Proctor and the higher compactive effort adopted in this study did not differ significantly for the steel slag RAP material. Expansion tests were conducted on 2 replicate specimens using the test setup consisting of 6 CBR mold assemblies submerged in a high alkali cement water solution (pH of 12) to accelerate expansion. Specimens prepared and compacted in the CBR mold would then be kept soaked in the high alkali water at 70 degrees Celsius in a large oven for up to 20–30 days or until the expansion curve flattens. The water level would be kept approximately at 0.5 to 1.0 in. (13 to 25 mm) above the CBR mold for complete soaking and for allowing minimum surcharge load. Since the amount of swelling or expansion depends on the reactivity of the aggregates, the alkalinity of the solution, and the ambient moisture conditions of the sample (Bellew and Mitchell, 2002), the use of high alkali solution was essential in this study to accelerate the hydration reaction to determine the worst case of expansion. The high alkali solution was prepared by mixing high alkali cement with water at a cement to water ratio of w/c = 1/7 to 1/8 to provide a solution pH value of around 13 at room temperature. The high alkali cement used was high alkali Type I Portland cement with an alkali percentage between 1.1 and 1.2. 4

EXPANSION TEST RESULTS

To establish the expansion characteristics of Illinois RAP materials for use as base/subbase courses in unbound pavement layers, expansion tests were conducted on both the selected RAP materials and virgin aggregates using the test procedure described in detail in Section 3. The test results are presented and evaluated in this section for assessing the differences between the RAP materials and virgin aggregates in order to identify certain trends in the expansion behavior as observed from the laboratory testing and how that would affect pavement performance. 4.1 Sieve analysis results The samples were passed through the 75-mm (3-in.), 19.-mm (3⁄4-in.) and 4.75-mm (No. 4) sieves according to ASTM D4792. Oversize correction was made only for dolomite crushed concrete, gravel crushed concrete and steel slag RAP. Note that the 4.75-mm (No. 4) sieve is the separator between the coarse and fine aggregates. Figure 1 shows the cumulative percent passing results of all the 17 materials tested. Note that all the virgin steel slag aggregates, i.e., “nonporous steel slag”, “porous steel slag” and

90 80 70 60 50 40 30 20 10

Materials used in the expansion test

Figure 1.

Sieve analysis results of all the materials tested according to ASTM D4792.

1190

SMA RAP

Steel Slag RAP

ACBF Slag RAP

ACBF Slag

Steel Slag

Gravel Crushed Concrete

Dolomite Crushed Concrete

Siliceous Gravel from R27-1

Dolomite from R27-1

Limestone from R27-1

Surface (%92 surface steel slag)

Gravel-Crushed Stone RAP (ALL-FRK)

Gravel Rap (Cur-Cl)

Gravel-Dolomite (Meyer)

Nonporous Steel Slag

Porous Steel Slag

0 Surface Binder (60%steel slag)

Cumulative Passing Amount%

100

Sieve 75 mm Sieve 19 mm Sieve 4.75 mm

“steel slag,” typically have low percentages of material passing the 4.75-mm (No. 4) sieve ranging from 4% to 18%. Therefore, virgin steel slag aggregates were generally coarser compared to other materials. On the other hand, “surface binder RAP with 60% steel slag aggregates” has the largest 67% of fine material followed by the other “surface RAP with 92% steel slag aggregates.” This concludes that the steel slag aggregates found in RAP were typically finer than the corresponding virgin steel slag aggregates. The percentages of the fine aggregate for the rest of the materials, except for gravel-dolomite (Meyer) aggregate, were generally at around 45%. 4.2 Dry density and moisture content The moisture content measured for each material replicate sample was mostly less than 1% except for the gravel crushed concrete and dolomite crushed concrete materials, which had moisture content values above 2%. This is mainly due to the fact crushed concrete may have trapped water within the concrete paste due to unfinished hydration. The virgin steel slag aggregates had dry densities typically around 2.1 g/cm3 (131 lb/ft3), which is consistent with the properties given for steel slag aggregates in the literature. On the other hand, steel slag aggregates found in RAP have a unit weight of approximately 1.9 g/cm3 (119 lb/ft3). This is in fact expected since RAP materials are commonly lighter than virgin aggregates. 4.3 Expansion test results (ASTM D4792) Seven-day minimum testing is specified by ASTM D4792 to be usually adequate to evaluate probable expansive behavior. Nevertheless, the expansion tests were generally continued for much longer than 7 days, based on the previous experience from preliminary expansion tests, to fully assess the expansion trends for longer durations, in one instance for up to 60 days, until a pronounced decrease in the expansion rate was observed. Figure 2 shows the evolution of net expansion with immersion time for samples. The results for the two replicate samples of each material are indicated by #1 and #2 in Figure 2. A marked increase in expansion rate was commonly observed when specimens were first immersed in the solution, and further increasing the immersion time resulted in increased expansion with smaller rates. During the expansion tests, especially the RAP materials were observed to undergo some initial settlements before any indication of expansion. This is most probably due to their more porous nature with lower dry densities; they simply could not tolerate their self weight added on top of the surcharge weight of 10 lbs (44.5 N), equal to the weight of the base material and pavement. This resulted in a contraction instead of expansion as clearly shown with negative percentages in Figure 2. For gravel RAP replicate samples, the highest contraction of over 3% was recorded (see Figure 2). Rohde et al. (2003) stated that this anomaly could be due to deficient compaction because of the lack of fines. Their study suggested using a corrected gradation to receive accurate results for the expansive nature of the materials. The upper expansion part of the graph in Figure 2 clearly indicates that the virgin steel slag aggregates show a higher potential of expansion in comparison with other aggregates which have very small or almost no expansion. If one considers the total expansion by ignoring the initial settlements as a means to quantify expansion, nonporous steel slag aggregate gives the maximum expansion as 6.18%, average of the two replicate sample results. It is followed by porous steel slag aggregate with an average expansion amount of 4.14% and Steel Slag from District 4 with an average amount of 0.28%. The variation in these expansion values of steel slag aggregates may depend on steel grade, the steel-making plant (source), specific furnace, steel slag processing (such as cooling method, crushing, etc.), and storage conditions. Since free lime hydrates rapidly seen in weeks while free magnesia takes years to develop expansion, this volume instability observed in the steel slag aggregates in Figure 2 should correspond to free lime expansion. Since an effective asphalt coating around the aggregate particles prevents any significant ingress of water into the aggregate, RAP materials are expected to have a less tendency to 1191

Expansion Graph for All Aggregates 0

5

10

15

20

25

30

35

40

Day 45

50

55

60

7.0 6.0 5.0 4.0 3.0

Expansion %

2.0 1.0 0.0 –1.0 –2.0 –3.0 –4.0 ACBF Slag #1 Dolomite Crushed Concrete #1 Gravel-Dolomite (Meyer) #1 Nonporous Steel Slag #1 Siliceous Gravel from R27-1 #1 Steel Slag RAP #1 Surface Binder (%60) #1

Figure 2.

ACBF Slag #2 Dolomite Crushed Concrete #2 Gravel-Dolomite (Meyer) #2 Nonporous Steel Slag #2 Siliceous Gravel from R27-1 #2 Steel Slag RAP #2 Surface Binder (%60) #2

ACBF RAP Slag #1 Gravel Crushed Concrete #1 Gravel RAP (CUR-CL) #1 Nonporous Steel Slag Repeat #1 MA RAP #1 Steel Slag RAP Standard Comp. #1

ACBF RAP Slag #2a Gravel Crushed Concrete #2 Gravel RAP (CUR-CL) #2 Nonporous Steel Slag Repeat #2 SMA RAP #2 Steel Slag RAP Standard Comp. #2

Dolomite from R27-1 #1

Gravel- Crushed Stone RAP (ALL-FRK) #1

Limestone from R27-1 #1

Porous Steel Slag #1 Steel Slag Dist.4 #1

Surface (%92) #1

Dolomite from R27-1 #2 Gravel- Crushed Stone RAP (ALL-FRK) #2 Limestone from R27-1 #2 Porous Steel Slag #2 Steel Slag Dist.4 #2 Surface (%92) #2

Net expansion values, computed based on first day reading, for all the specimens tested.

expand compared with the virgin aggregates. For example, gravel RAP (CUR-CL), gravelcombined stone RAP (ALL-FRK) and ACBF RAP slag show no expansion over the testing period in Figure 2. The effect of asphalt coating can be more significant for RAP materials with steel slag aggregates in terms of expansion behavior. Xue et al. (2006) states that steel slags show differences in texture and morphology from natural aggregates, especially in porosity characteristics. Such differences make slag surface texture rougher than those of other natural aggregates, and obviously, this is a major factor that will affect their adhesion ability with asphalt binder. Kandhal and Hoffman (1997) confirm that an effective asphalt coating may seal off the hydration of free calcium and magnesium oxides when steel slag aggregate is used in hot-mix asphalt mixtures. Moreover, a study by Wu et al. (2006) implies that the higher alkali value of steel slag improves the adhesion performance between aggregate and bitumen. In the light of these findings, Figure 3 shows RAP materials with steel slag aggregates to exhibit a great decrease in expansion behavior when compared to the corresponding virgin steel slag aggregates because of high absorption of bitumen and higher alkali value of steel slag aggregates. For example, nonporous and porous steel slag aggregates exhibit quite high average swell amounts of 6.18% and 4.14%, respectively. However, surface RAP with 92% steel slag aggregates shows an average total expansion amount of only 1.69% after the first day settlement. This value happens to be the highest expansion recorded from all 1192

Total Expansion Graph for Aggregates 7.0 6.5 6.0 5.5

Expansion%

5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 0

5

10

15

20

25

30

35

40

45

50

55

Surface (%92) #1

Surface (%92) #2

Steel Slag Dist.4 #1

Steel Slag Dist.4 #2

Nonporous Steel Slag #1

Nonporous Steel Slag #2

Nonporous Steel Slag Repeat #1

Nonporous Steel Slag Repeat #2

Porous Steel Slag #1

Porous Steel Slag #2

Surface Binder (%60) #1

Surface Binder (%60) #2

Steel Slag RAP Standard Comp. #1

Steel Slag RAP Standard Comp. #2

Steel Slag RAP #1

Steel Slag RAP #2

SMA RAP #1

SMA RAP #2

60

Day

Figure 3. Application of the criterion specified by ASTM D2940 to the total expansion curves of the laboratory tested materials (computed by ignoring initial settlements until the first indication of expansion). Table 2.

Summary of average total expansion values for all the materials. Average total expansion1 (%)

Duration of expansion test (days)

6.18 5.82 4.14 0.28

49 28 49 60

Surface (92%) Steel Slag RAP Standard Comp. Steel Slag RAP Surface Binder (60%)

1.69 1.46 1.13 0.24

44 45 45 49

SMA RAP

0.93

45

Material Virgin Steel Slag Aggregates Nonporous Steel Slag Repeat Nonpo Porous Steel Slag Steel Slag District 4 RAP with Steel Slag Aggregates

1

Computed by ignoring initial settlements until the first indication of expansion.

the experiments conducted on RAP materials. Next, SMA RAP also exhibits a significant average total expansion of 0.93% when compared to other aggregates, which have minor (less than 0.04%) or no expansion. Table 2 gives a summary of average total expansion values recorded for all the materials which show noteworthy expansion behavior. Note that ACBF slag aggregates are more stable volumetrically when compared to steel slag aggregates, therefore showing almost no expansion in Figure 3. A study by Billingslea (2001) indicates that ACBF is a non-abrasive, non-expansive material. It is primarily used as the binder, the asphalt substance laid on top soil or as a base for the road. The rough, irregular and angular particles tend to interlock when compacted, forming a very workable, stable surface with excellent traction. It provides a high resistance to lateral movement (Billingslea, 2001). Gupta et al. (1994) also states that steel slags exhibit a higher potential for producing tufa than ACBF slag. Therefore, the ACBF slag can be conveniently used in highway construction as an aggregate in contrast to steel slag. Table 3 evaluates the effects of compactive efforts for steel slag RAP, surface (92% steel slag aggregates) and surface binder (60% steel slag aggregates) RAP materials for soaking periods 1193

Table 3.

Evaluating effects of compactive efforts on expansion. Average total expansion (%)

Material

Soaking time (days)

Standard proctor

Between standard and modified proctor— used in this study

Steel Slag RAP Steel Slag RAP Surface (92%) Surface Binder (60%)

27 45 44 49

1.16 1.46 1.50 (from IDOT) 0.30 (from IDOT)

0.61 1.13 1.69 0.24

Amount of fine aggregate (passing No. 4 or 4.75 mm sieve) 24.9 24.9 57 66.7

of 27 to 49 days. When comparing the results obtained for steel slag RAP, the compactive effort between the standard and modified Proctor efforts adopted in this study led to a somewhat lower expansion amount (see Table 3). Yet, Figure 3 shows the steel slag RAP expansion curves for each compactive effort to get closer to each other as the soaking period increases. For example, the difference between the total swell amounts for steel slag RAP conducted by the standard and between the standard and modified compactive efforts decreases from 0.55% to 0.33% at a soaking period of 27 and 45 days, respectively. This is because the standard Proctor compaction effort causes the RAP materials to expand more since the material is looser at a lower compactive effort. Furthermore, when comparing expansion values obtained for surface (92%) and surface binder (60%) RAP materials from the two compactive efforts, the results show good agreement in spite of the fact that the samples compacted with the standard Proctor effort were tested previously at the IDOT laboratory in Springfield, Illinois (see Table 3). The RAP materials tested are more sensitive to compactive effort when compared to virgin aggregates probably because they include somewhat higher amounts of fine aggregates as listed in Table 3. As the fine amount increases, it fills the voids of the sample, thus increases the density, and ultimately enhances the compactibility (Aiban, 2006). Accordingly, as the aggregate particles become coarser, the resulting differences between the different compactive efforts should decrease. No readily available relationships could be found between expansion test results and field performance. Moreover, according to ASTM D4792, the expansion test results obtained by this standard should not be correlated with field performance, and values obtained do not necessarily indicate expansion that may occur in service conditions. However, ASTM D2940 “Standard Specification for Graded Aggregate Material For Bases or Subbases for Highways or Airports,” states: “aggregates that contain components subject to hydration, such as steel slags, shall be obtained from sources approved by the engineer on the basis of either a satisfactory performance record, or of aging or other treatment known to reduce potential expansion to a satisfactory level, or of expansion values not greater than 0.50% at seven days when tested in accordance with Test Method D4792.” If the compaction effort applied in the current expansion tests conducted based on ASTM D4792 (between the standard and modified Proctor efforts used in this study) is more likely preferred in the field for constructing base/subbase courses, the criteria specified by ASTM D2940 can be conveniently applicable to the expansion test results. Accordingly, Figure 3 shows such a limiting 0.5% expansion criterion drawn as a horizontal line together with a vertical line also drawn at the 7-day evaluation period. Then, it may be concluded that steel slag from District 4, SMA RAP, steel slag RAP, surface binder RAP with 60% steel slag aggregates, and surface RAP with 92% steel slag aggregates (almost) may be used as pavement base course aggregates. On the other hand, porous and nonporous steel slag aggregates should never be used in the bases/subbases without proper curing that satisfies the limitation specified by ASTM D2940. 1194

5

CONCLUSIONS

Seventeen materials, both virgin aggregates and RAP materials, were identified from the commonly used aggregate and RAP sources in Illinois and selected for studying their expansive characteristics in the laboratory. ASTM D4792 “Potential Expansion of Aggregates from Hydration Reactions” was determined as the test method to investigate in the laboratory the maximum acceptable level of expansion for all the selected virgin aggregate and RAP material types. In accordance with the ASTM D4792, expansion tests were conducted in CBR molds with the specimens prepared by compacting in three layers, 56 blows in each layer, and using both the standard and modified Proctor hammers. The specimens in CBR molds were submerged into a high alkali cement water solution (pH of 12) and kept always soaked at 70°C to accelerate hydration reactions. The amount of expansion (in percent) for the CBR specimens and the temperature and pH levels of the solution were measured continuously on a daily basis during the soaking period for a minimum of 7 days and maximum 60 days until the expansion curve flattened or the expansion rate slowed down. The expansion test results indicate that some steel slag aggregates showed somewhat high expansion potentials due to the hydration of free lime when compared to other virgin aggregates, such as siliceous gravel and crushed dolomite, which had minor or almost no expansion. The RAP materials, which had often lower densities, exhibited more of an initial settlement or contraction before any kind of expansion with time. Accordingly, considering only the total expansion by ignoring the initial settlements until expansion started, nonporous steel slag aggregate gave the maximum expansion as 6.18% mainly due to free lime hydration and evidenced by tufa like precipitate formation observed in the test setup. It was followed by porous surfaced steel slag aggregate, surface RAP with 92% steel slag aggregates and steel slag RAP (compacted with standard Proctor hammer) with expansion amounts of 4.14%, 1.69% and 1.46%, respectively. A clear conclusion from the expansion test results was that RAP materials had much lower tendencies to expand when compared to high expansion potentials of especially the virgin steel slag aggregates. Since steel slag surface texture is often rougher than other natural aggregates, their friction properties are superior and they have significantly improved adhesion ability with asphalt binder. Therefore, the significant differences found between the expansion values of the virgin and RAP steel slag aggregates may depend on an effective asphalt coating around the aggregate which prevents any significant ingress of water into the aggregate. Based on ASTM D2940 which limits expansion values to be not greater than 0.50% at seven days when tested in accordance with Test Method D 4792, it may be concluded that steel slag from District 4, SMA RAP, steel slag RAP, surface binder RAP with 60% steel slag aggregates, and surface RAP with 92% steel slag aggregates (almost) may be used as pavement base course aggregates. On the other hand, porous and nonporous steel slag aggregates should never be used in the bases or subbases without any proper curing that satisfies the limitation specified by ASTM D2940. ACKNOWLEDGMENT/DISCLAIMER This paper is based on the results of R27-27, Expansive Characteristics of Reclaimed Asphalt Pavement Used as Base Materials. R27-27 was conducted in cooperation with the Illinois Center for Transportation; the Illinois Department of Transportation; and the U.S. Department of Transportation, Federal Highway Administration. The contents of this paper reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Illinois Department of Transportation or the Federal Highway Administration. This paper does not constitute a standard, specification, or regulation. 1195

REFERENCES Aiban, S.A., “Utilization of Steel Slag Aggregate for Road Bases,” Journal of Testing and Evaluation, Vol. 34, No. 1, 2006. Bellew, G. and Mitchell, L., “Preventing Concrete Deterioration Due to Alkali-Aggregate Reaction” NRC Institute for Research in Construction (NRC-IRC) Construction Technology Update No. 52, 2002. Bennert, T., Papp, W.J., Maher, A. and Gucunski, N. “Utilization of Construction and Demolition Debris Under Traffic-Type Loading in Base and Subbase Applications,” Transportation Research Record 1714, Journal of the Transportation Research Board, Washington, D.C., 2000, pp. 33–39. Billingslea, A., “Slag: Mother Nature’s By-Product, EIT, Construction and Materials Issues,” 2001, pp. 176–182. Chini, A., Kuo, S., Armaghani, J. and Duxbury, J. “Test for Recycled Concrete Aggregate in Accelerated Test Track,” Journal of Transportation Engineering, American Society of Civil Engineers, Vol. 127, No. 6, 2001, pp. 486–492. Collins, R.J. and Ciesielski, S.K. “Recycling and Use of Waste Materials and By-Products in Highway Construction,” National Cooperative Highway Research Program Synthesis of Highway Practice 199, Transportation Research Board, Washington, D.C. 1994. Cross, S., Abu-Zeid, M., Wojakowski, J.B. and Fager. “Long Term Performance of Recycled Portland Cement Concrete in Pavement,” In Transportation Research Record 1652, TRB, National Research Council, Washington, D.C., 1996, pp. 115–123. Garg, N. and Thompson, M.R. “Lincoln Avenue Reclaimed Asphalt Pavement Base Project,” In Transportation Research Record 1547, National Research Council, Washington, D.C., 1996, pp. 89–95. Gupta et al., “Characterization of Base and Subbase Iron and Steel Slag Aggregates Causing Deposition of Calcareous Tufa in Drains,” Transportation Research Record No.1434, 1994, pp. 8–16. Hudson, W.R. and Saeed, A. “Evaluation and the Use of Waste and Reclaimed Materials in Roadbase Construction,” CTR 1348-2F Final Report, FHWA/TX-97/1348- 2F, Research Report 1348-2F, 1996, 203 pages. Institute of Roads Research, Brazilian National Department of Roads, “Using Mineralogical and Industrial Wastes in Road Paving,” (in Portuguese), Rio de Janeiro, 1990. Juckes, L.M., “The Volume Stability of Modern Steelmaking Slags, Mineral Processing and Extractive Metallurgy,” Vol. 112, December, 2003. Kandahl, P.S. and Hoffman, G.L. “Evaluation of Steel Slag Fine Aggregate in Hot-Mix Asphalt Mixtures,” Transportation Research Record No. 1583, Transportation Research Board, National Research Council, Washington, D.C., 1997, pp. 18–36. Machado, A.T. “A Comparative Study of Test Methods for Evaluating Steel Slag Expansion,” (in Portuguese). M.Sc. Thesis. University of São Paulo, Brazil, 2000. Maher, M.H. and Popp, W. “Recycled Asphalt Pavement as a Base and Subbase Material,” ASTM STP 1275, American Society of Testing and Materials, New Orleans, 1997, pp. 42–53. O’Mahony, M.M. and Milligan G.W.E., “Use of Recycled Materials in Subbase Layers,” In Transportation Research Record 1310, National Research Council, Washington, D.C., 1991, pp. 73–80. Rohde et al., “Electric Arc Furnace Steel Slag Base Material for Low-Volume Roads,” Transportation Research Record, Vol. 2, No. 1819, 2003, pp. 201–207. Senior, S.A., Szoke, S.I. and. Rogers, C.A. “Ontario’s Experience with Reclaimed Materials for Use in Aggregates,” Presented at the International Road Federation Conference, Calgary, Alberta, 1994. Simon, M. “User Guidelines for Waste and By Product Materials in Pavement Construction,” TurnerFairbank Highway Research Center, Federal Highway Administration, FHWA-RD-97-148, McLean, VA, 1997. Taha, R., AI-Harthy, A., AI-Shamsi, K. and AI-Zubeidi, M. “Cement Stabilization of Reclaimed Asphalt Pavement Aggregate for Road Bases and Subbases,” Journal of Materials in Civil Engineering, American Society of Civil Engineers, Vol. 14, No. 3, 2002, pp. 239–245. Taha, R., Ali, G., Basma, A. and Al-Turk, O. “Evaluation of Reclaimed Asphalt Pavement Aggregate in Road Bases and Subbases,” In Transportation Research Record 1652, TRB, National Research Council, Washington, D.C., 1999, pp. 264–269. Wu, S., Xue, Y., Ye, Q. and Chen, Y., “Utilization of Steel Slag as Aggregates for Stone Mastic Asphalt (SMA) Mixtures,” Building and Environment, 2007, pp. 42: 2580–5. Xue, Y., Wu, S., Hou, H. and Zha, J., “Experimental Investigation of Basic Oxygen Furnace Slag Used as Aggregate in Asphalt Mixture,” Journal of Hazardous Materials B138, 2006, pp. 261–268.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Study on fully and highly efficiently recycling of waste concrete L. Lu School of Science, Wuhan University of Technology, Hubei, Wuhan, China

Y. He & S. Hu School of Materials Science and Engineering, Wuhan University of Technology, Hubei, Wuhan, China

ABSTRACT: The disposal of waste concrete has been a serious problem. In this paper, a new method of fully and highly efficiently recycling of waste concrete is proposed. The method is as follows: first the components of waste concrete are separated by crushing, heating, grinding, and powder selecting with wind power, then, the separated component of the hardened cement paste powder is calcined to prepare regenerated binding material, and the separated components of ground and calcined mortar are used to prepare high strength lime-silica material. Experiments were carried out to verify the validity of the proposed method. Experimental results indicate that highly reactive regenerated binding material containing the phase of cryptocrystalline β-C2S, can be prepared by burning the separated hardened cement paste powder at 650°C. And lime-silica material with the compressive strength of 97.2 MPa can be prepared by the mortar powder separated from waste concrete in the autoclaving curing. 1

INTRODUCTION

At the present time, Portland cement concrete is the most widely and maximally used man-made material. In the foreseeable future, it will still be one of the most important building materials. In fact, concrete has been the basis of modern society, and it is widely used in buildings, roads, bridges, hydraulic works, marine works, and substructure works. However, in the demolishment of old buildings and engineering structures, and in the processes of producing new concrete, enormous amounts of waste concrete is produced, which has been a troublesome problem to environmental protection. The discard of waste concrete not only occupies precious land resources, but also produces secondary pollution to ecological environments, which results in the deterioration of soil, groundwater, and worsening effect on the growth of plants. How to recycle the cement based solid waste has been a focus for many researchers around the world. 2

CURRENT RECYCLING UTILIZATION OF CEMENT-BASED MATERIALS

2.1 Research and application of recycled aggregates concrete At the present time, most of the research studies on the recycling utilization of cement-based materials are focused on Recycled Aggregates Concrete (RAC). The preparation of RAC usually includes the following steps: First, waste concrete is collected, and the impurities such as steel bar, wood and plastic are removed. Secondly, the waste concrete blocks are crushed for multi-levels, and particles of each level received are sieved. According to the sizes, they are classified as recycled coarse aggregate, recycled fine aggregate and powders. The recycled coarse aggregates are composed of the original coarse aggregates and their crushed pieces, particles blended with original coarse aggregates and mortar, and the mortar blocks. The recycled fine aggregates are composed of the original fine aggregate particles, particles blended with original fine aggregates and cement paste, and particles of crushed cement paste. Finally, the recycled aggregates are used to fully or

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partially replace the natural aggregates to prepare new concrete (e.g., Chen et al. 2003, Topcu et al. 1995). Using waste concrete to prepare RAC could be traced back to World War II (Olorunsogo et al. 2002). And in 1976, a concrete road in Lyon County, Iowa State, USA, which had been used for 42 years, was demolished; and the waste concrete blocks were crushed to small particles and then used as recycled aggregates. A new 1.6 km (1 mile) long, 25.4 cm (10 in.) thick road was paved with the RAC produced with these recycled aggregates. From then on, RAC was rapidly and widely applied in road engineering (Salem 1996). At present time, about 80%, 75% and 65% of the waste concrete was recycled to produce RAC in Denmark, Netherlands and Japan, respectively (Tam et al. 2005). In other countries, such as, Britain, France, Germany, Canada and South Africa, the recycling technology of waste concrete for preparing RAC has also been successfully applied (Olorunsogo et al. 2002). The performances of RAC have been widely studied by researchers around the world. For example, the compressive behavior of RAC was studied by Palmquist (2003). The assessment of recycling process induced damage sensitivity of recycled aggregates, and the freezing and thawing resistance of RAC were investigated by Nagataki et al. (2004). The mixture optimization of RAC was studied by Lin and his coworkers (Lin et al. 2004). The properties of concrete prepared with recycled aggregate from partially hydrated old concrete were investigated by Katz (2003). The porosity of recycled concrete with recycled aggregates was studied by Jose (2002). The microstructure of RAC prepared by two-stage mixing approach was analyzed by Tam et al. (2005). And the properties of concrete with fine recycled aggregate were investigated by Khatib (2005). In short, the investigation and application of RAC involved many aspects, including macro mechanical properties and workability of RAC. Researchers nowadays study microstructure, durability, mechanism of fracture, system optimization and theoretical modeling of RAC. 2.2 The existing problem Although the production of RAC with waste concrete has been an effective way to recycle waste concrete, there are some inherent deficiencies for RAC. First, the compressive strength of recycled aggregates concrete is 15%~30% lower than natural aggregates concrete is prepared with the same raw materials except for aggregates, the flexural strength of which is also about 15% lower. An important reason for the lower strength of RAC is the micro-cracks existing in recycled aggregates, which is produced in the crushing process of production. These micro-cracks are disadvantageous for the strength of RAC, and when concrete bears loads, they will extend and induce the failure of RAC. At the same time, the mechanical properties of RAC are tightly related to the original waste concrete. Most of the recycled aggregates are composed of original coarse aggregates and adherent mortar, or just the mortar blocks, and so the strength of RAC at a high level will be determined by the strength of the interfacial zone and transitional zone between original coarse aggregates and mortar, and the strength of mortar. Secondly, the workability of RAC is obviously worse than normal concrete. Because of the porous structure of adherent mortar, the water absorption ratio of recycled aggregates is much higher than natural aggregates. And at the same time, the surfaces of recycled aggregates (especially recycled fine aggregates) are commonly harsh and multi-angular, which will worsen the workability of RAC. Although some researchers attempted to do pretreatment work on recycled aggregates, for example, using mineral admixture pastes or hydrophilic organic pastes to enwrap recycled aggregates and better their water absorption performances, these effects were limited. Thirdly, some of the research studies showed that the impermeability, freezing and thawing resistance, and carbonation resistance of RAC were commonly inferior to normal concrete, the more the recycled aggregates, the worse the durability (Olorunsogo et al. 2002, Katz 2003, Topçu et al. 2004, Gokce et al. 2004, José 2002). To acquire adequate workability, RAC needs much more mixing water than normal concrete, which increases its porosity and weakens its impermeability. And, on the other hand, the micro cracks in recycled aggregates and the interfacial zone between recycled aggregates and adherent mortar also bring the same problem. 1198

Because of these inherent deficiencies, the application of RAC technology was usually limited in low strength and nonstructural concretes. At the same time, the RAC technology is not a full and highly efficient approach for the recycling of waste concrete. Coarse aggregates and part of the fine aggregates could be used in RAC by current technology, but major parts of the remnant hardened cement paste was often ground into powders in the production process of recycled aggregates and thrown away as waste materials. However, cement paste is almost the maximum resource and energy consuming part in concrete and it is also almost the most costly component. With the development of concrete structures toward high rising, big span forms, the designed strength grade of concrete increases continually, and the content of cement used in concrete is also increasing gradually. So, it is necessary to study and develop new methods to achieve the full and highly efficient recycling of waste concrete. 3

NEW APPROACHES TO RECYCLE WASTE CONCRETE

3.1 The separation of waste concrete components Based on the research work of Shima and his coworkers (Shima et al. 2005), the method of separating the components of waste concrete was developed. The first step of the process is to detach coarse aggregates and mortar. The waste concrete pieces crushed under a size 40 mm were heated to 300~350°C and then cooled by electric fan in air. Due to the differences of thermal expansion coefficient between aggregates and cement paste, micro cracks were extended or newly produced in the interfacial transition zone between them during this process. The cooled concrete pieces were put into a tube mill and rubbed by small steel columns. Adjusting the rubbing time, the rolling speed of the tube mill and the size of the rubbing media, coarse aggregates and mortar could be detached and mortar would be crushed into small particles. The discharged materials from the mill were then fed into a vibrating screen to separate the coarse aggregates and mortar particles. The second step is to detach the hardened cement paste and fine aggregates. Mortar particles acquired in the first step were again put into a tube mill and rubbed by small steel columns for a suitable period of time. During rubbing process, most of the cement paste would be separated from fine aggregates and ground into fine powders. Because of the difference in their hardness, the particle size of hardened cement paste powder and quartz powder would differ a lot at the same rubbing time. And because of the lower density of hardened cement paste powder, it would float in the air of the tube mill and could be swept out by adjusting the air speed, and could be collected by a filter bag. The ground quartz fine aggregate particles would be discharged from the end part of the tube mill. So coarse aggregates, fine aggregates and hardened cement paste of waste concrete, would be separated rather thoroughly by the above two steps. 3.2 The utilization of the separated waste concrete components For different separated waste concrete components, different applications were designed. The separated coarse aggregates and fine aggregates could be used in preparing RAC, as most researchers used to do. But there is another valuable application for separated ground fine aggregates. It could be used to prepare high strength lime-silicate products by hydrothermal reaction in the autoclaving curing. Lime-silicate material is another important kind of silicate material besides Portland cement concrete. In 1880, researchers in Germany proposed the manufacture method of this kind of material. And in the following century, it was rapidly developed. The lime-silicate materials could satisfy almost all of the performances of concrete products except for cast-in-situ concrete. For the production of the lime-silicate material, Portland cement is not a necessary raw material, and there is little pollution. So compared to Portland cement concrete, its environmental burden is much lower. But the high quality quartz sand necessary for manufacturing lime-silicate products is more and more difficult to acquire, which limits the application and popularization of this material. However, waste concrete contains about 30% quartz sand, at the same time, there is about 20% Ca(OH)2 existing in the hardened cement paste, and much more CaO can be acquired by burning the hardened cement paste powder separated from waste concrete. So the raw materials needed for the manufacturing of 1199

lime-silicate materials can readily be acquired from waste concrete by treating it with certain processes, and it is possible to prepare lime-silicate materials with waste concrete. Furthermore, the separated hardened cement paste powder from waste concrete can be high efficiently recycled to prepare regenerated binding materials. Regenerated binding materials mean the materials prepared by treating the hydration products of original binding materials with calcination or other methods and acquired the binding ability again. There is about 60%~70% C-S-H gel existing in the cement hydration products. And many research studies showed that the dehydration phases of C-S-H gel had the rehydrating and binding ability. For example, C-S-H gel with amorphous silica and CaO can be prepared, and when it is burned at 800°C and 900°C, reactive belite phase could be acquired (Kurdowsk et al. 1997). Reactive belite cement was prepared with fly ash and CaO (Jiang et al. 1992, Guerrero et al. 2000, Zhong et al. 1994). The process involved two sequential steps. Firstly, fly ash, CaO, and de-ionized water were hydrothermal treated to form calcium silicate and aluminate hydrates. After the hydrothermal treatment, the hydrates were calcined between 700°C and 900°C. So it is possible to prepare regenerate binding material by burning the hardened cement paste powder to form reactive belite phase. And at the same time, according to the opinions of cement chemists Powers and Taylor, the lowest water to cement (W/C) ratio for the complete hydration of typical Portland cement is about 0.42~0.44 (Powers 1960, Taylor 1997). In fact, there are always some unreacted cement particles existing in the cement paste of waste concrete, the lower the ratio of water to cement, the higher the content of unreacted cement particle. For C50 or higher strength grade concrete, the content of unreacted cement particles is even higher than 25% of original cement used. These unreacted cement particles will still have the hydration ability and contribute to the strength of regenerated binding material. In the view of saving energy and resources, and protecting environment, it is significant to reuse this part of unreacted cement. 4

EXPERIMENTAL PROGRAM

4.1 Preparation and hydration of regenerated binding material The hardened cement paste powder (marked with R0) was separated from C50 strength grade waste concrete according to the method described in 3.1, and then it was put into a muffle furnace and heated to 650°C, keeping the temperature for 1 h. After that, the product was cooled to room temperature by an electric fan, and the cooled product was the regenerated binding material (marked with R650) (He 2006). The regenerated binding material R650 was mixed with deionized water to prepare 4 cm × 4 cm × 4 cm cubical specimens. The ratio of water to solid was 0.3. After the specimens were cured in the curing box of 20 ± 1°C and the relative humidity ≥95% for certain ages, their compressive strength and microstructure were tested. 4.2 Preparation of lime-silicate material According to the method described in 3.1, mortar particles were separated from C50 strength grade waste concrete. The particles were put into ball-mill and ground to fine powder with the Blaine specific surface area of 300 m2/kg. The content of ground quartz fine aggregate was tested based on a selective dissolution procedure using dilute hydrochloric acid solution and water. The principle of the procedure is that the hydration products of cement, and the unreacted cement components can be dissolved, and the quartz powder undissolved can be left remaining. And then, the content of the quartz powder in mortar could be calculated, and it was about 55%. The mortar powder was heated to 650°C, keeping the temperature for 1 h, and then cooled to room temperature by an electric fan. The product acquired was marked with S650. Cubical specimens were prepared with S650. The ratio of water to solid was 0.3, and after mixing, the admixture was molded into 4 cm × 4 cm × 4 cm molds and compacted under the stress of 20 MPa. The specimens were demolded after the ambient environmental curing of 1 day, and then were hydrothermally cured at 1.2 MPa saturated vapor pressure for 4 hours in autoclave. Both the temperature rising and cooling periods 1200

were 2 hours. The compressive strength of the specimens was tested after cooling, and their mineral phases were also determined by XRD. 4.3 Experimental results 4.3.1 Properties of regenerated binding material The chemical composition of R0, and the XRD patterns of R0 and R650 are shown in Table 1 and Figure 1, respectively. The compressive strengths of the specimens at 3, 7 and 28 days of aging are listed in Table 2. The results presented in Figure 2 indicate that honeycomb like C-S-H gel is the main hydration product of regenerated binding material R650. From Figure 1, it can be seen that cryptocrystalline β-C2S exists in R650. Not like β-C2S mineral phase in cement clinker, which is generated at the temperature higher than 1200°C, this kind of β-C2S is generated by the decomposition of C-S-H gel at much lower temperatures, and its crystallization level is not as high as β-C2S in cement clinker. But its hydration ability is relatively high, and it is the main source of hydration and binding ability of regenerated binding material. From Table 2, it can be concluded that good compressive strength can be acquired by the hydration of regenerated binding material. So, it is possible to use regenerated binding material as binder or admixture of concrete. Figure 2 shows the compact net structure formed by the hydration products of regenerated binding material. 4.3.2 Properties of lime-silica material The compressive strength of the lime-silica specimen is 97.2 MPa after autoclaving. The value is significant, because it is acquired using the waste concrete as raw material com-

Figure 1.

Table 1.

Chemical composition of R0 (% by weight).

SiO2

Fe2O3

Al2O3

TiO2

CaO

MgO

SO3

Loss

39.78

2.43

9.17

0.21

36.42

2.41

1.49

7.83

XRD pattern of R0 and R650 (Hu et al. 2007). Table 2.

Compressive strengths of regenerated binding material specimens.

Age (days)

3

7

28

Compressive strength/MPa

19.7

31.3

54.3

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(a) ×5 000

(b) ×10 000

Figure 2.

The SEM photomicrograph of 28-day regenerated binding material specimen.

Figure 3.

XRD pattern of lime-silicate material prepared with waste concrete.

(a) ×5 000

(b) ×5 000

Figure 4. The SEM photomicrograph of lime-silicate material prepared with waste concrete (He et al. 2008).

pletely. The SiO2 and CaO necessary for the hydrothermal reaction come from the separated fine quartz aggregate and the dehydration phases of Ca(OH)2 and C-S-H gel of waste concrete separately. In the autoclaving curing process, SiO2 and CaO react with each other to form tobermorite phase (see Figure 3). The strength of tobermorite crystals is relatively high, 1202

and they interweave with each other and form firmly three-dimensional structures. Figure 4 shows the microstructure of the lime-silica material; (a) shows the SEM photomicrograph of the main body of the specimen, and (b) shows the SEM photomicrograph of the tobermorite crystal in pores of the specimen. In this experiment, the hardened cement paste was ground and calcined together with quartz fine aggregate. But in the view of saving the energy for calcinations, these two kinds of components should be separated in industrial production. Regenerated binding material should be first prepared, and then it should be mixed with proper proportion of ground quartz fine aggregate and water to prepare lime-silicate material. If necessary, lime could be added into the admixture to acquire proper CaO/SiO2 ratio. 5

CONCLUSIONS

A new approach to fully and highly efficiently recycle waste concrete was proposed. The hardened cement paste separated from waste concrete could be used to prepare regenerated binding material by low temperature calcinations, and the separated mortar could be used to prepare high strength lime-silica materials. Compared to the traditional method of using the waste concrete to prepare recycled aggregate concrete, the new method realized the full utilization of almost all of the components of waste concrete. To verify the validity of the method, experiments were carried out. The results showed that regenerated binding materials could be prepared by burning the separated hardened cement paste powder at 650°C. It contained the phase of cryptocrystalline β-C2S and had high reactivity with water. Limesilica material with the compressive strength of 97.2 MPa was prepared with the ground and calcined mortar collected from waste concrete by hydrothermal synthesis, and its main produced mineral phase was tobermorite. REFERENCES Chen H.J., Yen T. & Chen K.H. 2003. Use of building rubbles as recycled aggregates, Cem. Concr. Res. 33(1): 125–132. Gokce A., Nagataki S., Saeki T. & Hisada M. 2004. Freezing and thawing resistance of air-entrained concrete incorporating recycled coarse aggregate: The role of air content in demolished concrete. Cem. Concr. Res. 34(5): 799–806. Guerrero A., Gonňi S., Macĭas A. & Luxán M.P. 2000. Effect of the starting fly ash on the microstructure and mechanical properties of fly ash-belite cement mortars, Cem. Concr. Res. 30(4): 553–559. He Y.J. 2006. Research on recycling utilization of cement-based solid waste (in Chinese, dissertation). Wuhan: Wuhan University of Technology. He Y.J., Lu L.N. & Hu S.G. 2008. Hydro-thermal hydration of regenerated binding materials and influences on properties of its hardened paste. Proceedings of International Conference on Microstructure Related Durability of Cementitious Composites, Nanjing: 1027–1034. Hu S.G. & He Y.J. 2007. Preparation of generated binding material using waste concrete, Journal of the Chinese ceramic society. 35(5): 593–599. Jiang W. & Roy D.M. 1992. Hydrothermal processing of new fly ash cement, Ceram Bull 71(4): 642. Jose´M.V.Go´mez S. 2002. Porosity of recycled concrete with substitution of recycled concrete aggregate An experimental study, Cem. Concr. Res. 2(8): 1301–1311. Jose´M.V.G. 2002. Porosity of recycled concrete with substitution of recycled concrete aggregate: An experimental study, Cem. Concr. Res. 2(8): 1301–1311. Katz A. 2003. Properties of concrete made with recycled aggregate from partially hydrated old concrete, Cem. Concr. Res. 33(5): 703–711. Khatib J.M. 2005. Properties of concrete incorporating fine recycled aggregate, Cem. Concr. Res. 35(4): 763–769. Kurdowski W., Duszak S. & Trybalska B. 1997. Belite produced by means of low-temperature synthesis, Cem. Concr. Res. 27(1): 51–62. Lin Y.H., Tyan Y.Y., Chang T.P. & Chang C.Y. 2004. An assessment of optimal mixture for concrete made with recycled concrete aggregates, Cem. Concr. Res. 34(8): 1373–1380. Nagatakia S., Gokceb A., Saekic T. & Hisada M. 2004. Assessment of recycling process induced damage sensitivity of recycled concrete aggregates, Cem. Concr. Res. 34(6): 965–971.

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Olorunsogo F.T. & PadayacheN. e. 2002. Performance of recycled aggregate concrete monitored by durability indexes, Cem. Concr. Res. 32(2): 179–185. Palmquist S.M. 2003. Compressive behavior of concrete with recycled aggregates, PhD thesis, Tufts University, Boston, MA, USA. Powers, T.C. 1960. Physical Properties of Cement Paste, Proceedings of The fourth International Symposium on The Chemistry o f Cement, Washington, 577–609. Salem R.M. 1996. Strength and Durability Characteristics of Recycled Aggregate Concrete, PhD thesis, The University of Tennessee, Knoxville, USA. Shima H., Tateyashiki H., Ryuji M. & Yoshid Y. 2005. An advanced concrete recycling technology and its applicability assessment through input-output analysis, Journal of Advanced Concrete Technologh, 3(1): 53–67. Tam V.W.Y., Gao X.F. & Tam C.M. 2005. Microstructural analysis of recycled aggregate concrete produced from two-stage mixing approach, Cem. Concr. Res. 35(6): 1195–1203. Topcu İ.B. & Güncan N.F. 1995. Using waste concrete as aggregate, Cem. Concr. Res. 25(7): 1385–1390. Topçu İ.B. & Şengel S. 2004. Properties of concretes produced with waste concrete aggregate, Cem. Concr. Res. 34(8): 1307–1312. Taylor. 1997. Cement Chemistry (2nd Edition). London, UK. Telford Publishing. Zhong B.Q., Yang N.R. & Yohihiko O. 1994. An investigation on the formation process of β-C2S from hydrothermally synthesized CSH by 29Si-NMR and TMS-GC, Journal of the Chinese ceramic society, 22(6): 566–572.

1204

Railroad track structures

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of roadbed stiffness on bearing capacity of railroad ballast with discontinuous analysis T. Ishikawa & T. Kamei Hokkaido University, Sapporo, Japan

E. Sekine Railway Technical Research Institute, Tokyo, Japan

Y. Ohnishi Kyoto University, Kyoto, Japan

ABSTRACT: The paper proposes a new analytical procedure that involves discontinuous analysis to estimate the bearing capacity of granular roadbed used in ballasted track, namely “railroad ballast.” To examine the applicability of the procedure, a series of numerical simulation bearing capacity tests for a 1/5 scale model of a real ballasted track were performed by employing discontinuous deformation analysis (DDA) that regards a particle of crushed stone as an irregular polygon. By comparing the analytical results and experimental results, the effect of roadbed stiffness on the bearing capacity of railroad ballast was examined. As the result, it was revealed that the roadbed stiffness has significant influence on the bearing capacity of railroad ballast, and that discontinuous analysis is an effective method to simulate the mechanical behavior of railroad ballast if the roadbed, which has been often modeled as a continuum, can be approximated with discontinuous modeling well. 1

INTRODUCTION

The study of “track deterioration” is one of the principal assignments in railway engineering, particularly for ballasted track, because track deterioration has serious consequences on the safety of train operation. Track deterioration, which is observed mainly on ballasted tracks (see Figure 1), is a phenomenon by which the rail level at train passages becomes irregular toward the longitudinal direction of the railway track with repeated train passages. In general, a dominant factor of track deterioration is supposed to be the uneven subsidence of railroad ballast, which comprises a pile of well-compacted crushed stones, caused by cyclic wheel loading. Accordingly, on ballasted tracks, the railroad ballast is expected to have sufficient bearing capacity that it can sustain train loads without losing the evenness of the rail level and spread the applied pressure before transmitting it to the roadbed and subgrade. Moreover, angular and hard crushed stones that are uniformly graded and free of dust and dirt have been considered to be good ballast materials because such ballast can bear high contact pressures from a sleeper during train passages over a long period of time. However, in case the bearing capacity of roadbed drops due to rainfall, increase in ground water level and freeze-thawing, even if the railroad ballast itself possesses high strength and stiffness, the uneven settlement of rail level may increase with the deformation of the roadbed, which is assumed to be a load bearing layer of a ballasted track; this phenomenon can be attributed to the variations in the mobility of individual ballast particles, which determines the deformation-strength characteristics of railroad ballast, with the deformability of roadbed fluctuating. In fact, according to previous researches conducted on the basis of experimental results obtained from model tests and field measurements, it has been shown that the track deterioration of ballasted tracks increases at soft roadbeds in comparison to that at hard 1207

Vertical Load Rail Sleeper

Railroad Ballast Roadbed Subgrade

Figure 1.

Ballasted track structure.

roadbeds. Therefore, it is necessary for rationalizing a present design method for ballasted tracks and reducing maintenance costs to elucidate the bearing capacity characteristics of not only railroad ballast but also railroad ballast as a component of a multi-layer system. Thus far, a number of studies have been conducted on the application of discontinuous analysis, which can be used to evaluate the mobility of individual ballast particles directly, to the mechanical behavior of railroad ballast subjected to wheel loads, and as a result it has been shown that discontinuous analysis is an effective technique for simulation of the mechanical behavior of railroad ballast (Saussine et al. 2004, Aikawa et al. 2007, Kono & Matsushima 2008). These research studies have mainly focused on the technique to model inhomogeneous granular assemblage such as railroad ballast in terms of both the particle properties of ballast like particle shape and their in-situ laminated state of railroad ballast like particle alignment for the purpose of realizing numerical simulations that are highly realistic. However, as mentioned above, the precision of numerical simulations conducted for ballasted tracks appears to depend on not only the modeling method used for the railroad ballast as granular assemblage but also the modeling method employed for the ballasted track as a multi-layer system. Unfortunately, little is known about the effects of the interactions between ballast particles and other components of a ballasted track, particularly the roadbed, on the mechanical behavior of ballasted track from the viewpoint of the mechanics of granular materials. This paper examines the effects of roadbed stiffness on the bearing capacity of railroad ballast in order to improve the prediction accuracy of numerical simulations by employing discontinuous analysis. In this study, numerical simulations of bearing capacity tests for a 1/5 scale model of an actual ballasted track at the longitudinal section are performed by means of discontinuous deformation analysis (DDA) (Shi & Goodman 1985) which regards a ballast particle as an irregular polygon block, and it is assumed that a roadbed is composed of some discontinuous blocks. Three different types of roadbed materials, namely steel, hard rubber, and soft rubber, are adopted to examine the effect of roadbed stiffness. For comparison, FE simulations are performed under the same conditions as those employed for the DDA simulations. By comparing the experimental results of model tests with the analytical results of DDA simulations, the validity of the modeling methods of ballasted tracks considered for the discontinuous analyses is examined under various types of roadbed conditions. Moreover, the effects of roadbed stiffness on the bearing capacity of railroad ballast are evaluated on the basis of numerical simulations. 2

ANALYTICAL METHOD

2.1 DDA simulations 2.1.1 Modeling Numerical simulations of bearing capacity tests for model ballasted track (Ishikawa & Sekine, 2002) were performed with two-dimensional DDA models. As DDA is a kind of discontinuous analysis, each DDA block is separated by its boundaries and moves individually. Figure 2 1208

shows the size, dimension, and boundary condition of DDA models, which simulates a onefifth scale model of a full-scale track. However, for bearing capacity tests, both the analytical model and the real model tracks have a single aluminum sleeper and no rail. The analytical model, which simulates a longitudinal section of model ballasted track, is in the plane strain state with the longitudinal section assumed to infinitely continue like the real model track. Figure 3 shows element meshes of DDA models before loading. A DDA model is composed of some polygon blocks, namely “ballast blocks” which represent andesite ballast particles, “a sleeper block” which represents an aluminum sleeper, “roadbed block(s)” which represents various types of roadbed, “a subgrade block” which represents steel subgrade and “side blocks” which represent a rigid soil container. Especially in this study, to examine the effect of modeling method for roadbed on the numerical simulation, two types of DDA models which differ in element discretization for roadbed were employed as shown in Figure 3. Here, the term “Model A” is used to refer to DDA model which roadbed is divided into three blocks in height and ten blocks in width, and the term “Model B” is used to refer to the other. Ishikawa et al. (2006) revealed that a DDA model using expanded hexagon blocks can simulate the load-displacement relation in bearing capacity tests for model ballasted track well. Accordingly, an expanded hexagon, which was made by extending a regular hexagon in consideration for the aspect ratio (Zingg 1935) of real ballast particles as shown in Figure 4, was adopted as a shape of all ballast blocks. Here, the gradation curve of ballast blocks in DDA models, which is equivalent to the gradation curve of railroad ballast employed in real bearing capacity tests of the one-fifth scale model ballasted track, is shown in Figure 5 together with its mean grain size D50 and uniformity coefficient Uc. With regards to preparation method of DDA models (Fig. 3), Ishikawa et al. (2005) is available for reference. Table 1 shows the feature of railroad ballast in DDA models in comparison with experimental conditions. Here, the porosity of DDA models is much smaller than that of experiments. This phenomenon seems to be mainly caused by the reason that DDA models used in this study are two-dimensional while the laminated state of real railroad ballast is three-dimensional.

250 mm

Vertical load Sleeper block

34.8 mm Side block

Ballast depth 50 mm

60 mm

48 mm

Ballast blocks

Roadbed block(s)

30 mm

Subgrade block

30 mm

500 mm

Figure 2.

Schematic section of the DDA model.

(a) Model A

(b) Model B Figure 3.

Element mesh (Expanded hexagon, Ballast depth 50 mm).

1209

Side block 60 mm

1.0 Elogation Ratio, Q (= b/a)

I: Discs

0.8 0.6

III: Blades

0.4

II: Equidimensionals

0.2 0.0 0.0

Figure 4.

Sieve mesh = 11.2 mm Sieve mesh = 9.5 mm Sieve mesh = 8.0 mm Sieve mesh = 6.7 mm Sieve mesh = 5.6 mm

IV: Rods

0.2 0.4 0.6 0.8 Flateness Ratio, P (= c/b)

1.0

Classification of ballast particle shapes. 100 Percentage Passing (%)

90 80

1/5 Scale Ballast D50 = 8.11 mm

70 60

UC = 1.50

Real Ballast D50 = 39.0 mm

50

UC = 1.50

40 30 20 10 0 1

Figure 5.

10 Grain size (mm)

100

Grain size distribution of ballast blocks.

Table 1.

Features of railroad ballast in DDA models. Density

Porosity

Number of blocks

Name

g/cm3

%

ballast blocks

DDA model Experiment (steel) Experiment (soft rubber) Experiment (hard rubber)

2.12 1.45 1.49 1.45

21.3 46.2 44.8 47.1

451 – – –

2.1.2 Analytical conditions DDA analyses were performed by using two-dimensional models along with linear elastic blocks under plane-strain conditions. Table 2 shows the material properties of blocks and the interface properties of block edges. When two DDA blocks come in contact with each other, springs and a frictional slider are created at the contact points, as shown in Figure 6. Accordingly, the analytical input parameters of the DDA blocks were characterized by the material properties of a block, namely unit mass (γ), Young’s modulus (E), and Poisson’s ratio (ν), and the interface properties of block edges, namely block friction angle (φμ) and cohesion of surface (Cμ). With regard to the material properties, the parameters were set by referring to the design values and previous experimental results (Ishikawa et al. 1997). With regard to the interface properties, the φμ between ballast blocks was set to 55º, and the φμ between a ballast block and other types of blocks was set to 37º by referring to other papers of the authors (Ishikawa et al. 1997, Ishikawa et al. 2005). Furthermore, the Cμ between a ballast block 1210

Table 2.

Material properties of DDA models. Unit mass ρ

Young’s modulus E

Name

g/cm3

GPa

Sleeper Ballast Steel roadbed Hard rubber roadbed Soft rubber roadbed Steel subgrade Side

2.70 2.70 7.80 0.94 0.94 7.80 7.80

70.0 0.02 210.0 0.004 0.001 210.0 210.0

Poisson’s ratio ν

0.30 0.10 0.30 0.48 0.48 0.30 0.30

Cohesion Cμ

Friction angle φμ

kPa

deg.

0 0 400.0 150.0 10.0 0 0

37.0 55.0 37.0 37.0 37.0 37.0 37.0

Ballast Particle

Figure 6.

Contact mechanism between DDA blocks.

and all other blocks and that between ballast blocks were set to zero by considering that the ballast was a coarse granular material; the Cμ between roadbed blocks was set to a specified value so that element discretized roadbed blocks could behave like a continuum body. The adjustment for the Cμ between roadbed blocks is discussed in detail at 2.3. A DDA simulation of tests on bearing capacity for the model ballasted track was performed as follows. First, a stability analysis was performed by applying a gravity force of 9.8 m/s2. The state of DDA models after stability analysis is called “the initial loading state.” Figure 3 shows the initial loading state of each DDA model. Second, a vertical load was applied to the DDA models in the initial loading state, and the gravity force was applied. The loading point was the center point of the sleeper block, as shown in Figure 2. The vertical load was gradually increased from 0 kN to 5 kN at a constant loading speed, which was regarded as static loading, similar to the actual experimental conditions. For the experiments, stage loading was adopted pursuant to a plate loading test, whereas for the analyses, monotonic loading was adopted for saving the time required for the calculations. However, in case of static loading, it may safely have been assumed that the difference in loading methods had little influence on the load-displacement relation.

2.2 FEM simulations In this study, numerical simulations of bearing capacity tests for a model ballasted track were performed by using a two-dimensional linear elastic FE model under plane-strain conditions. Figure 7 shows the size, dimension, and boundary condition, along with the element mesh. Joint elements were inserted between different components of the model ballasted track, such as a sleeper and railroad ballast, railroad ballast and roadbed, in order to model the discontinuity between them. The parameters of the FE model, such as unit mass (γ), Young’s modulus (E), and Poisson’s ratio (ν), were set to those of the DDA model, as shown in Table 2, and the parameters of joint elements were set such that the settlement of a sleeper in the FEM simulation may agree with the experimental results of the model ballasted track in case of steel roadbed. After stability analysis conducted by applying the gravity force, a compression vertical load of 5 kN was directly applied at the center of the sleeper surface, as shown in Figure 7. 1211

Vertical load

250 mm

Joint element

34.8 mm Horizontal direction: Fixed Vertical direction: Free

Figure 7.

Ballast depth 50 mm

Sleeper 48.0 mm

30 mm 30 mm

Ballast roadbed

Steel roadbed 500.0 mm Horizontal direction: Fixed Vertical direction: Fixed

Schematic section and element mesh of FEM model.

Vertical load 5 kN Plate

10 mm

60 mm 500 mm

Roadbed

Horizontal direction: Fixed Vertical direction: Free Steel subgrade 500 mm Horizontal direction: Fixed Vertical direction: Fixed 500 mm Figure 8.

Schematic diagram of plate loading test model.

2.3 Setting of cohesion between roadbed blocks In case of discontinuous analysis in which the roadbed was divided into some detached blocks, the assemblage of roadbed blocks which have no cohesion may not sustain the pressure from the railroad ballast with only friction between blocks, and as a result, the roadbed block may subside locally. Accordingly, this section examines whether or not the assemblage of roadbed blocks can behave like a continuum body by addition of adequate cohesion to the side boundaries of the roadbed blocks. Concretely, plate loading tests for three types of roadbed materials, namely steel, hard rubber and soft rubber, were performed as shown in Figure 8 by using both FEM and DDA under the same analytical conditions, except the Cμ between roadbed blocks in the DDA simulations (Table 2); by comparison of both the analytical results, an adequate Cμ between roadbed blocks in the DDA simulations was determined according to the type of material of the roadbed so that the settlement at the roadbed surface in the DDA simulation may agree well with that in the FEM simulation. 1212

Figure 9 shows the relationships between the vertical displacement at the surface of a hard rubber roadbed, and the distance from the loading point to the center of a roadbed block obtained from a comparison of DDA simulations, which employ various value of Cμ between roadbed blocks with FEM simulations. As the value of Cμ between roadbed blocks decreases, the settlement of DDA blocks close to the loading point increases and the roadbed surface around both the left and right ends swells further. In case of the hard rubber roadbed, the settlement at the roadbed surface analyzed from the DDA simulations for Cμ between roadbed blocks of 150 kPa is most similar to that analyzed from the FEM simulation. Figure 10 shows the relationships between the adequate Cμ between roadbed blocks and the roadbed stiffness. With increase in roadbed stiffness, the adequate Cμ between roadbed blocks increases. Therefore, in this study, the Cμ between roadbed blocks was set to a specified value according to the roadbed stiffness, as shown in Table 2. 3

RESULTS AND DISCUSSION

3.1 Bearing capacity of railroad ballast Figure 11 shows the relationships among every type of roadbed material with regard to the applied vertical load and vertical displacement at the center of gravity of the sleeper block, which are obtained from DDA simulations differing in the element discretization for the roadbed. These graphs also compare analytical results of DDA simulations with FEM simulations and experimental results under the same test conditions. Furthermore, in this study, the bearing capacity of railroad ballast can be defined as the vertical displacement at vertical Plate

Vertical displacement at P = 5 kN (mm)

–1.0 0.0 1.0 2.0 3.0 4.0

Figure 9.

FEM DDA 50kPa DDA 100kPa DDA 150kPa DDA 200kPa DDA 400kPa DDA 800kPa DDA 1600kPa

–0.2 –0.1 0.0 0.1 0.2 Distance from loading point (m)

Effect of cohesion on settlement of roadbed.

Cohesion between roadbed blocks (kPa)

400 300 200 100 0

Figure 10.

0

1

2

3

4

5

10 10 10 10 10 10 Young’s modulus of roadbed (MPa)

Relations between Cμ and E.

1213

6.0 FEM

Model A

3.0 2.0 1.0 0.0 0.0

Experiment

0.5 1.0 1.5 2.0 2.5 Vertical displacement (mm)

Figure 11.

5.0 4.0

Vertical load, P (kN)

Model B

Hard rubber roadbed, Ballast depth = 50 mm

Vertical load, P (kN)

Vertical load, P (kN)

4.0

6.0

6.0 Steel roadbed, Ballast depth = 50 mm

5.0

Model B FEM

3.0 Model A

2.0 1.0

5.0 4.0

3.0

0.5 1.0 1.5 2.0 2.5 Vertical displacement (mm)

3.0

Model B FEM

3.0 Model A

2.0 1.0

Experiment

0.0 0.0

Soft rubber roadbed, Ballast depth = 50 mm

0.0 0.0

Experiment

0.5 1.0 1.5 2.0 2.5 Vertical displacement (mm)

3.0

Load—displacement relations.

loads P of 2 kN and 5 kN. Accordingly, it is considered that a numerical model has stronger bearing capacity for smaller vertical displacements at a specified vertical load. Figure 12 shows the vertical displacement, which is obtained from DDA simulations differing in the element discretization for roadbed and the roadbed stiffness, at P = 2 kN and P = 5 kN, respectively. These graphs compare analytical results of DDA simulations with FEM simulations and experimental results under the same test conditions. The difference in the bearing capacity of railroad ballast due to the difference in the element discretization for roadbed and the roadbed stiffness is discussed. From Figure 11 and Figure 12, the following tendencies are recognized. With decrease in the roadbed stiffness, the vertical displacement at the same vertical load increases regardless of the element discretization for the roadbed. Moreover, for the specified vertical load the vertical displacement of Model A is larger than that of Model B, irrespective of the roadbed stiffness. A comparison between DDA simulations with experimental results under the same test conditions indicates that the analytical result of Model A resembles the experimental result for every level of roadbed stiffness, although the difference between both results increases for low levels of roadbed stiffness. These results indicate that Model A, which has an element discretized roadbed and with deformability as high as that of Model B, which has only one roadbed block, is a numerical analysis that is appropriate for conducting bearing capacity tests of ballasted tracks on soft roadbed in terms of the prediction accuracy of numerical simulations with discontinuous analysis. The applicability of DDA simulations to bearing capacity tests of ballasted track is examined in comparison to that of FEM simulations. In Figure 11(a), although FEM simulations are very similar to the experimental results of model tests in case of the steel roadbed, the difference between both the results gradually becomes clear with decrease in the roadbed stiffness; this can be attributed to the parameters of joint elements in FE analyses being set uniformly irrespective of the roadbed stiffness so that the FEM simulation may agree with the experimental results of the model ballasted track in case of the steel roadbed. Accordingly, the reproducibility of the mechanical behavior of the model ballasted track by FE models may decline with decrease in the roadbed stiffness. On the other hand, for DDA simulations, in the case of P = 2 kN (Fig. 12(a)), the DDA simulations that employ Model A is most similar to the experimental results, whereas in the case of P = 5 kN (Fig. 12(b)), the difference between the bearing capacities of Model A and the FE model cannot be discerned regardless of the roadbed stiffness due to the element discretization for roadbed in DDA models. For example, in Figure 12, although for the steel roadbed, the analytical results of Model A resemble not only the experimental results but also those of Model B, for the soft rubber roadbed, there exists some difference between the analytical results of Model A and the experimental results as compared with other types of roadbed materials. These results indicate that for low roadbed stiffness and/or large vertical load, namely under the analytical conditions in which the deformation of the roadbed can be distinguished, modeling methods such as the element discretization for the roadbed and the setting of Cμ between roadbed blocks seriously influence the analytical precision of DDA simulations. 1214

3.0

2.5 2.0

DDA Model A DDA Model B FEM Experiment

Vertical Displacement at P = 5.0 kN (mm)

Vertical Displacement at P = 2.0 kN (mm)

3.0

1.5 1.0 0.5 0.0

Steel Hard rubber Soft rubber Material type of roadbed

(a) P = 2.0 kN Figure 12.

2.5 2.0 1.5 1.0 0.5 0.0

DDA Model A DDA Model B FEM Experiment

Steel

Hard rubber Soft rubber Material type of roadbed

(b) P = 5.0 kN

Comparison of bearing capacity among models under different types of roadbed.

(a) Model A, Steel roadbed

(b) Model A, Hard rubber roadbed (c) Model A, Soft rubber roadbed

(d) Model B, Steel roadbed

(e) Model B, Hard rubber roadbed (f) Model B, Soft rubber roadbed

Figure 13. Deformation of the railroad ballast and distribution of principal stress in the DDA simulations.

3.2 Mechanical behavior of railroad ballast Figure 13 shows the distribution for the principal stress vectors of ballast blocks at P = 5 kN obtained from the DDA simulations for every type of roadbed material and every type of DDA model, respectively. Figure 14 shows the distribution for the displacement vectors of the ballast blocks at P = 5 kN, obtained from the DDA simulations under various analytical conditions such as those represented in Figure 13. A displacement vector is defined as the movement of a DDA block from the initial loading state to the state at P = 5 kN. The distribution of principal stress vectors and displacement vectors in the FEM simulations are shown in Figure 15 and Figure 16, respectively. The black vector shows the compression stress and the grey one shows the tensile stress. The influence of the element discretization for the roadbed on the mechanical behavior of the railroad ballast in the DDA simulations is discussed. From Figure 13, it is recognized that the analytical results of Model A differ from those of Model B in the distribution of princi1215

200

Depth from under-surface of sleeper (mm)

(a) Model A, Steel roadbed –40 –20 0 20 40 60 80 –100 0 100 Horizontal distance from loading point (mm)

200

Depth from under-surface of sleeper (mm)

(c) Model A, Hard rubber roadbed 1mm

–100 0 100 Horizontal distance from loading point (mm)

(e) Model A, Hard rubber roadbed Figure 14.

–200

–100 0 100 Horizontal distance from loading point (mm)

200

1mm –40 –20 0 20 40 60 80 –200

–100 0 100 Horizontal distance from loading point (mm)

200

(d) Model B, Hard rubber roadbed

–40 –20 0 20 40 60 80 –200

1mm –40 –20 0 20 40 60 80

(b) Model B, Steel roadbed

1mm

–200

Depth from under-surface of sleeper (mm)

–100 0 100 Horizontal distance from loading point (mm)

Depth from under-surface of sleeper (mm)

–200

200

Depth from under-surface of sleeper (mm)

Depth from under-surface of sleeper (mm)

1mm – 40 –20 0 20 40 60 80

1mm –40 –20 0 20 40 60 80 –200

–100 0 100 Horizontal distance from loading point (mm)

200

(f) Model B, Hard rubber roadbed

Distribution of displacement inside railroad ballast in DDA simulations.

(a) Steel roadbed

(b) Hard rubber roadbed

(c) Soft rubber roadbed Figure 15.

Distribution of principal stress in FEM simulations.

pal stress. For example, in the case of Model A, the principal stress of ballast blocks mainly turns toward the vertical direction, and high principal stress appears underneath the sleeper block. However, in the case of Model B, it can be observed that the principal stress vectors spread out toward the diagonal lower part of both sides from the undersurface of the sleeper block. Moreover, with decrease in the roadbed stiffness, the deformation of roadbed blocks increases in Model A, and the deformation of the roadbed block cannot be discerned in Model B. Furthermore, from Figure 14, it is recognized that the displacement vectors of ballast blocks underneath the sleeper block in Model B are smaller than those in Model A, and that with decrease in the roadbed stiffness, although the movement of ballast blocks increases 1216

(a) Steel roadbed

(b) Hard rubber roadbed

(c) Soft rubber roadbed Figure 16.

Distribution of displacement in FEM simulations.

in Model A, it hardly changes in Model B. These results indicate that in DDA simulations, the element discretization for the roadbed has a strong influence on the stress distribution inside the railroad ballast and the movement of ballast blocks. Consequently, it appears reasonable to conclude that the bearing capacity of railroad ballast has been different according to the modeling method of roadbed. The mechanical behavior of railroad ballast in DDA simulations is examined as compared to that in FEM simulations. Comparing Figure 13 with Figure 15, it is recognized that at the contact point between ballast blocks, the tensile stress cannot act in the direction of the normal to the block edges in the DDA simulations, and that the minimum principal stress at some elements close to the loading point is tensile in the FEM simulations. Moreover, the stress is hardly developed at the ballast blocks adjacent to the side of the sleeper block in the DDA simulations; the compression stress is developed in the horizontal direction, and the tensile stress is developed in the vertical direction at the same parts in the FEM simulations. This tendency becomes clear particularly in soft rubber roadbeds in which the deformability is high. From these results, the reason why analytical results of DDA models differ from those of FEM models in the case of soft roadbed appears to be associated with the difference in the stress distribution inside the railroad ballast, including the presence or absence of tensile stress inside the railroad ballast. 4

CONCLUSIONS

The following findings can be obtained; – In DDA simulations for bearing capacity tests of ballasted track, the roadbed stiffness has a strong influence on the bearing capacity of the railroad ballast. Accordingly, the precision of numerical simulations depends on the modeling method such as the element 1 for the roadbed and the setting of cohesion of surface (Cμ) between roadbed blocks. – In DDA simulations, the bearing capacity of railroad ballast differs according to the modeling method adopted for the roadbed, because it influences the stress distribution inside the railroad ballast and the movement of ballast blocks. The reason why DDA simulations 1217

differ from FEM simulations is due to the presence or absence of tensile stress inside the railroad ballast. – In DDA simulations, when a DDA model has the element discretized roadbed and employs the adequate Cμ between roadbed blocks according to the roadbed stiffness, it can simulate the mechanical behavior of the ballasted track without considering the interaction between the granular assemblage such as the ballast and a continuum body such as the roadbed. These findings lead to the conclusion that DDA is an effective method to simulate the mechanical behavior of a ballasted track if the roadbed, which behaves as a continuum, can be approximated with discontinuous modeling. ACKNOWLEDGMENT The authors would like to thank Prof. Seiichi Miura, Hokkaido University, for providing many invaluable discussions and suggestions. REFERENCES Aikawa, A., Namura, A., Ishida, M. & Takao, Y. 2007. Dynamic behavior and kinetic energies at the rail weld of ballasted track imparted by moving trains, Proc. Railway mechanics 11: 27–32. (in Japanese) Ishikawa, T., Ohnishi, Y. & Namura, A. 1997. DDA applied to deformation analysis of coarse granular materials (ballast). In Ohnishi, Y. (ed.), Analysis of Discontinuous Deformation; Proc. the 2nd intern. conf., Kyoto, 10–12 July 1997.: 253–262. Ishikawa, T. & Sekine, E. 2002. Effects of Moving Wheel Load on Cyclic Deformation of Railroad Ballast. In Forde, M.C. et. al. (eds), Railway Engineering-2002; Proc. the 5th intern. conf., London, 3–4 July 2002.: [1/1(CD-ROM)]. Ishikawa, T., Kobayashi, K., Sekine, E. & Ohnishi, Y. 2005. Evaluation of the effect of particle shape on the bearing capacity of railroad ballast with discontinuous analysis, In Horvli Ivar (ed.), Bearing Capacity of Roads, Railways and Airfields; Proc. the 7th intern. conf., Trondheim, 27–29 June 2005.: [1/1(CD-ROM)52]. Ishikawa, T., Kobayashi, K., Sekine, E. & Ohnishi, Y. 2006. Effect Evaluation of particle shape on mechanical behavior of railroad ballast with discontinuous analysis, In Hyodo, M. et. al. (eds), Geomechanics and geotechnics of particulate media, Proc intern. symp., Yamaguchi, 12–14 September 2006.: 389–396. Saussine, G., Chplet, C., Gautier, P.E., Duboris, F., Bohatier, C. & Moreau, J.J. 2004. Modeling ballast under cycle loading using discrete element method, In Triantafylidis (ed), Cycle behavior of soils and liquefaction phenomena, Proc. intern. symp., Bochum, 31 March–2 April 2004.: 649–658. Shi, G.H. & Goodman, R.E., 1985. Two dimensional discontinuous analysis. Int. J. Num. Anal. Methods. Geomech 9: 541–556. Kono, A. & Matsushima, T. 2008. Effect of loading frequency on the settlement of granular layer. In Yu, Ellis et. al. (eds), Advances in transportation geomechanics; Proc. the 1st intern. conf., Nottingham, 25–27 August 2008.: 601–606. Zingg, T., 1935. Beitrage zur Schotteranalyse. Schweiz. Miner. Petrog. Mitt. 15: 39–140.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Pressure measurements and structural performance of hot mixed asphalt railway trackbeds L.S. Bryson & J.G. Rose University of Kentucky, Lexington, KY, USA

ABSTRACT: In order to assess pressure distributions within the track and support structure, earth pressure cells have been installed in selected hot mix asphalt (HMA) trackbeds on a CSX Transportation heavy tonnage revenue freight line and at the TTCI heavy tonnage test track in Pueblo. The measured values of pressure distribution within each layer were used to establish a pressure index. This pressure index is the ratio of pressure at the interface of a layer, to the predicted bearing capacity of the layer. A pressure index value of one implies failure of the layer. The pressure index and other measures of structural performance such as track modulus and subgrade stiffness were assessed. From these assessments, relationships were established whereby the pressure distribution and deflection characteristics of the trackbed were quantified in terms of material type and layer thickness. Thus, allowing for a rational performance assessment of the overall trackbed system. 1

INTRODUCTION

The United States freight railroad industry is currently experiencing unprecedented growth in traffic volumes, revenue ton-miles, and wheel loadings. Railways have been a significant mode of transport for 175 years in the United States. During the late 1800s and early 1900s it was the dominant mode. In recent years train speeds, gross ton-miles, and axle loads have increased significantly on the freight railroads. This marked turn around began in the early 1980s as the industry was relieved by many of the regulations that had stemmed innovations and growth for approximately 50 years. The latest Association of American Railroads statistics (AAR, 2006) indicate that in 2005 an all-time record 1.7 trillion ton-miles of freight was carried over the nation’s nearly 227,000 km railroad network. The average freight car weight has increased to 117 metric tons with most new cars having gross weights of 130 metric tons. The importance of developing and specifying premium track structures and components to adequately carry the increased tonnage is a current reality of the industry. Failure of the track structure and components results in an inability to maintain track geometric features necessary for efficient and safe train operations. Maintenance costs and track outages increase due to frequent maintenance and renewal cycles. Advanced technologies are necessary to provide stronger and longer-lasting track and support structures to accommodate the record volumes. Conventional trackbeds are typically composed of all-granular materials consisting of layers of ballast and subballast over a prepared subgrade, as noted in Figure 1a. However, in recent years trackbeds containing a layer of hot mixed asphalt (HMA) are becoming more prevalent. Development of HMA trackbeds began in the early 1980s. Various tests and performance evaluations have shown numerous advantages over traditional all-granular (ballast) trackbeds (Rose and Lees, 2008; Anderson and Rose, 2008). The most common HMA trackbed, termed asphalt underlayment as shown in Figure 1b, incorporates a layer of HMA in lieu of the subballast. Ballast is used above the HMA layer in a similar manner as the conventional all-granular trackbed. The ballast provides a protective cover for the HMA by blocking the sunlight, protecting the surface from air and water, and maintaining a relatively constant temperature and environment. 1219

(a)

(b)

Figure 1. Typical trackbed cross sections: (a) all-granular ballast section; (b) hot mixed asphalt section.

HMA is used for new track construction and for rehabilitation/maintenance of existing lines. It has a wide range of applications including open track, special track work (switches or turnouts, crossing diamonds, etc.) bridge approaches, tunnel floors and approaches, and highway/rail crossings.

2

PREVAILING DESIGN PRACTICES

2.1 Design specifications Asphalt underlayment design and construction standards for railways typically follow recommendations set forth by the Asphalt Institute (Asphalt Institute, 1998; Asphalt Institute, 2007). The typical HMA layer is approximately 3.7 m wide and is approximately 125 to 150 mm thick. For poor trackbed support conditions and high impact areas, a 200 mm thickness is used. Thickness of the overlying ballast normally ranges from 200 to 300 mm. The typical HMA mixture specification is the prevailing dense-graded highway base mix in the area having a maximum aggregate size of 25 to 37.5 mm. This slight modification to the typical highway mix imparts ideal properties to the track structure. Normally the asphalt binder content is increased by 0.5% above that considered optimum for highway applications resulting in a low to medium modulus (plastic) mix, having a design air voids of 1 to 3%. This mix is easier to densify to less than 5% in-place air voids and therefore facilitates adequate strength and an impermeable mat. Rutting of the plastic mix is not a concern in the trackbed since the pressures are applied through the ballast over a wide area. Bleeding and flushing are also of little concern since the wheels do not come in direct contact with the HMA layer and the temperature extremes are minimized in the insulated trackbed environment. 2.2 Installation equipment and costs The equipment required for installing the HMA layer varies depending on the size of the installation. For short maintenance/rehabilitation projects, the HMA is normally backdumped on grade and spread with a trackhoe, small dozier, bobcat, etc. already on site, prior 1220

to compacting with a conventional vibratory roller. This process requires that the old track panel be removed. Thus the cost to place the HMA is minimal, basically no more than placing conventional granular subballast. The cost of the HMA material delivered to the job site adds a small percentage to the total track removal and replacement costs but is basically insignificant, since it replaces the granular subballast. The majority of the costs involve equipment, labor and track materials. The added time to the track outage to place HMA is insignificant, provided the track is to be removed and the underlying ballast/subballast replaced with new ballast. For larger out-of-face projects, mainly new construction with a prepared subgrade, the HMA is placed with conventional asphalt laydown (paving) equipment and compacted with large vibratory rollers. The procedure is similar to highway construction. The cost of the HMA may be less that the cost of granular subballast if quality granular subballast has to be transported long distances due to insufficient quality or quantity in the immediate area. Normally HMA is compatible with a wide variety of subballast aggregates. The thickness and width of the HMA is less than that of granular subballast, thus about one-half or less material is required, which is also a cost advantage for HMA. The HMA can be placed with highway paving equipment as rapidly as highway paving with much less hand-work and concerns of smoothness. 3

OBSERVED PERFORMANCE OF ASPHALT UNDERLAYMENTS

Rose and Lees (2008) reported on recent investigations that involved asphalt core drilling and, sampling and characterization of trackbed materials. These investigations were conducted on numerous in-service HMA trackbeds on CSXT and BNSF revenue lines in several states. These HMA trackbeds ranged from 12 to 26 years of service and were selected to include varying geographical and geological conditions. The investigations involved a wide variety of subgrades that ranged from low-strength, high plasticity (fat) clays to moisturesensitive silts to higher quality granular materials. The HMA cores and extracted/recovered asphalt binders were extensively evaluated at the National Center for Asphalt Technology at Auburn University. The primary purpose was to determine if any significant weathering or deterioration of the HMA was occurring in the trackbed environment, which could adversely affect long-term performance. A variety of HMA mixture compositions and mat thicknesses were evaluated. 3.1 Asphalt underlayment durability It was concluded that the various asphalt binders and HMA mixes did not exhibit any indication of excessive hardening (brittleness), weathering, or deterioration even after many years in the trackbed environment. This is primarily due to the insulative effects of the overlying ballast. This protects the HMA from sunlight and excessive temperature extremes, which significantly reduces oxidation and hardening of the asphalt binder. The mat remains slightly flexible, which contributes to a long fatigue life for the HMA layer. There is no indication that the HMA mats are experiencing any loss of fatigue life. These findings substantiated earlier findings (Rose et al., 2000). 3.2 Effects on structural performance It has been observed that mixes specifically designed to be more viscous (plastic) are conducive to the angular ballast particles slightly penetrating or imbedding into the top surface of the asphalt mat. This increases the interfacial shear strength and improves overall structural value of the track structure. Furthermore, the uniformly high level of support provided by the HMA mat maintains a high degree of ballast compaction which results in increased modulus, reduced wear, and increased life of the ballast. This is a primary contributor to the extended excellent track geometry indicators provided by the HMA mat and confined ballast 1221

layer. The combined supports provided by the HMA mat and the confined ballasts layer are believed to be primary contributors to the excellent track geometry indicators routinely measured over long periods of time. 3.3 Trackbed pressure measurements Two sites were selected for the trackbed pressure tests. One was on a heavy-tonnage CSXT revenue mainline in east-central Kentucky, near Conway, KY. The other was on the hightonnage test trackbed at TTCI in Pueblo, Colorado. Trackbed pressure measurements were obtained at prevailing speeds under heavy tonnage railroad loadings. Pressure measurements were recorded using (Geokon) hydraulic type earth pressure cells. These were imbedded in the track structure above and below the HMA mat (Rose et al., 2002; Anderson and Rose, 2008). 3.3.1 CSXT revenue line tests Figure 2 is a typical plot of the pressures exerted on top of the HMA mat for a CSXT empty coal train in the time domain (Rose et al., 2002). Vertical pressures imposed by typical 130-metric ton locomotives and loaded coal cars range from 90 to 120 kPa on top of the

HMA Compressive Stress (kPa)

(a) 200 Four 6-Axle Locos

20 cm ballast 13 cm HMA

160

Initial 5 Wagons

120 80 40 0 7

8

9

10

11

12

13

14

15

16

17

Time (s)

HMA Compressive Stress (kPa)

(b) 150 Four 6-Axle Locos

20 cm ballast 20 cm HMA

120 90

Initial 5 Wagons

60 30 0 4

5

6

7

8

9

10

11

12

13

14

15

Time (s) Figure 2. Representative dynamic compressive stress on HMA layer measured for empty coal train on CSXT mainline at Conway, KY: (a) 13 cm HMA layer; (b) 20 cm HMA layer.

1222

HMA mat. The average locomotive wheel load is 16 metric tons. Pressures are reduced to 15 to 30 kPa under the 29 metric ton empty cars, which have an average wheel load of 3.5 metric tons. Two cross sections were investigated. One cross section consisted of 130 mm of HMA overlain by 200 mm of ballast (Figure 2a) and the other section consisted of 200 mm of HMA overlain by 200 mm of ballast (Figure 2b). Figure 2 shows the beam action of the track, which distributes the concentrated wheel loadings over several ties and the confined, high modulus ballast layer, serves to effectively reduce the heavy wheel loadings. In general, trackbed vertical stress levels on top of the HMA mat are very low under heavy tonnage railroad loadings and are only a fraction of those imposed by high-pressure truck tires on highway pavements. By comparison, typical tire pressures imposed on highway asphalt surfaces under loaded trucks range from 700 kPa to over 1,050 kPa depending on the magnitude of loading and tire configurations. Thus, it is assumed the HMA mat will have an extremely long fatigue life at the load-induced pressure levels existing in the trackbed environment. 3.3.2 TTCI high tonnage trackbed Li et al. (2002) presented the results of testing performed at the TTCI High Tonnage trackbed. HMA underlayment sections were placed over a soft subgrade (low track modulus) and subjected to 36-metric ton axle loads. The use of HMA underlayment was intended to reduce load-induced stresses to the subgrade and to provide a waterproof layer over the underlying soil. In these tests, three different track structures were evaluated; (i) a conventional granular track structure; (ii) a 102 mm-thick HMA trackbed; and (iii) a 203 mm-thick HMA trackbed. The conventional track structure was representative of typical of mainline railroad tracks and was used as a point of reference. This track consisted of 305 mm of ballast and approximately 150 mm of subballast. The 102 mm-thick HMA trackbed consisted of 305 mm of ballast, 102 mm of asphalt, and 102 mm of subballast. The 203 mm-thick HMA trackbed consisted of 203 mm of ballast, 203 mm of asphalt, and 102 mm of subballast. All track structures were placed over a soft subgrade comprised of Vicksburg (Buckshot) clay. This clay is a high moisture content clay with an average liquid limit of 64 percent, an average plasticity index of 38 percent and an average natural moisture content of 34.6 percent. The average undrained shear strength was reported as approximately 90 kPa. Figure 3 gives the subgrade stresses obtained at 83 MGT under a static wheel load of 18 metric tons. As shown, the measured subgrade stresses were lower for the asphalt

90 80

Subgrade Stress (kPa)

70 60 50 40 30 20 10 0 450 mm Granular Track

Figure 3.

102 mm HMA

203 mm HMA

Test results for subgrade stress under 18 metric ton static wheel load.

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160 203 mm HMA Surface 140

Subgrade Surface

Stress (kPa)

120 100 80 60 40 20 0 2

3

4

5

6 Time (s)

7

8

9

10

Figure 4. Reduction of dynamic stresses from 203 mm HMA surface to subgrade surface under 36 metric ton axle cars.

25 Kr = 0.044(t) + 14.16 Track Modulus, Kr(kPa)

20

15

10

5 Data from Li et al. (2001) 0 0

50

100

150

200

250

Asphalt Thickness, t (mm)

Figure 5.

Track modulus as a function of thickness of the asphalt layer.

trackbeds than for the 450-mm granular track. Under the 18-metric ton static wheel load, only 49 to 55 kPa of subgrade stress was generated under the HMA underlayments, compared to approximately 83 kPa under the 450-mm granular track structure. Figure 4 shows the dynamic stress results under an actual train operating at 64 km/hr measured on the 203-mm HMA surface as well as on the subgrade surface. The data indicates that the dynamic peak pressures measured on the top of the HMA surface for the 15- to 18-metric ton wheel loads (39 metric ton axle load) range from 75 to 150 kPa. These measured stresses compare favorably with the 90- to 120-kPa dynamic pressures measured on top of the HMA mat at the CSXT Conway test site for the 16-metric ton wheel loads (cf. Figure 2). As illustrated in Figure 4, use of a 203-mm HMA underlayment reduced the subgrade stress by approximately one-half. At the subgrade surface, the measured peak 1224

stresses ranged between 39 to 66 kPa. This reduction is similar to that shown for the static wheel load (cf. Figure 3). The stress reduction behavior is most likely due to the HMA layer acting as an arching mechanism to the stress distribution. This seems logical given the HMA layer is much more rigid, relative to the ballast materials. With the reduction in the stress levels being transmitted to the subgrade, it can be concluded that HMA layers will reduce the cyclic load-induced strength loss to the subgrade soils. 3.4 Trackbed structural performance In addition to the subgrade stress (σmeas), the data presented by Li et al. (2001) also included track modulus (Kr) data. Figure 5 shows the track modulus as a function of asphalt thickness (t). The figure shows that the modulus increases linearly with increasing thickness of the HMA layer. The expression that represents this linear increase is given as K r = 0.44(t ) + 14.16

(1)

The increase in track modulus implies a decrease in track settlement, which translates into more durable tracks. Thus, asphalt underlayment will tend to produce a general reduction of required maintenance cycles. Improvement of the structural performance of the track structure offered by HMA underlayment can also be assed from the pressure index. The pressure index is the ratio of pressure at the interface of a layer, to the predicted bearing capacity (qult) of the layer. A pressure index value of unity implies failure of the layer. Figure 6 presents the pressure index at the top of the subgrade as a function of asphalt thickness. The bearing capacity used for the figure was obtained from a modified form of the Meyerhof and Hanna (1978) general bearing capacity equation for a stronger soil underlain by a weaker soil (the reader is referred to Selig and Waters, 1994 for further details on bearing capacity for track structures). The form of the equation used in this study is given as B⎞ B ⎞⎛ 2 D ⎞ ⎛ K p tan δ ⎞ ⎛ ⎛ qult = c′Nc ⎜1 + 0.2 ⎟ + γ H 2 ⎜1 + ⎟ ⎜1 + ⎟ −γH ⎟⎜ L L H ⎠⎝ B ⎝ ⎠ ⎝ ⎠⎝ ⎠

(2)

where c' = the effective cohesion intercept of the bearing soil; Nc= the bearing capacity factor = 5.12; B = the width of the tie = 229 mm; and L= the 1/3 length of the tie = 864 mm;

0.7

Pressure Index, σ meas/qult

0.6 0.5 0.4 0.3 0.2 0.1 0 0

50

100

150

200

Asphalt Thickness, t (mm)

Figure 6.

Pressure index as a function of thickness of the asphalt layer.

1225

250

Undrained Shear Strength,su(kPa)

120 100 su = 427.5 –11.71(ω) 80 60 40 20 Data from Li (2000) 0 25

27

29

31

33

35

Moisture Content, ω (%)

Figure 7.

Undrained shear strength as a function of moisture content.

y = the unit weight of the bearing soil = 18.85 kN/m3; D = the depth of embedment of the tie; H = the thickness of the granular layer; K = the passive earth pressure coefficient; δ = the p inclination of the passive earth force = 2φ′/3 ; φ′ = the effective phi angle of the soil. The shear strength parameters of the subgrade soil were taken from Miller et al. (2000). They performed isotropically consolidated undrained (CU) triaxial test on undisturbed samples of subgrade soil and reported that the effective stress Mohr-Coulomb failure envelope gave φ′ = 22.7˚and c′= 15.9 kPa. It is noted the Meyerhof and Hanna (1978) bearing capacity equation assumes a homogeneous bottom layer overlain by a homogeneous top layer. For the two case of asphalt underlayment, the thickness of the asphalt layers were added to the depth of embedment and it was assumed that the thickness of the granular layer was approximately 406 mm. Although this is a greatly simplified treatment of the HMA underlayment system, this provides a qualitative means by which the improvements to the structural performance can be evaluated. As seen in the figure, the asphalt underlayment significantly improves the pressure index. The factor of safety against punching shear failure increases by roughly 35 percent with 102 mm of HMA underlayment and by approximately 46 percent for 203 mm of HMA underlayment. Although Figure 6 shows the improved structural performance due to the HMA layers, it also highlights the need for additional studies to understand bearing capacity for these types of systems. 3.5 Benefit to the subgrade An additional benefit of asphalt underlayment is that subgrades tend to maintain their insitu moisture contents at or near the optimum moisture content. Rose and Lees (2008) investigated several HMA track systems and found this to be the case. This is of interest in that shear strength of compacted soils tends to decrease with increasing moisture content, greater that optimum moisture (Lambe and Whitman, 1969). This behavior was also observed at the TTCI test track. The Rose and Lees (2008) study found that the in-situ moisture contents were within one percent of the laboratory determined optimum values for maximum density of the respective materials. Figure 7 shows the undrained shear strength versus the insitu water content. The undrained shear strength was obtained from unconfined compression tests reported by Li (2000).

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Cyclic Shear Strength, τf (kPa)

40 Drained Undrained

35 30 25 20 15 10 5

Data from Miller et al. (2000)

0 0.32

Figure 8.

0.33

0.34 0.35 0.36 0.37 Moisture Content, ω (%)

0.38

0.39

Influence of moisture content on the cyclic shear.

The data shows a consistent linear relation between undrained shear strength and moisture content. For the clay subgrade, the relation is given by the following expression su = 427.5 − 11.71(ω )

(3)

The observation of a decrease in strength with increasing moisture content was also found for the case of cyclic loading. Miller et al. (2001) presented cyclic triaxial data for the Vicksburg clay. Figure 8 presents the cyclic shear strength(τf ) as a function of water content. A trend line is shown in the figure to emphasize that the general relation observed with the monotonic loading condition is the same with the cyclic loading condition. The undrained cyclic shear data is included for completeness. However, as is fundamental in the nature of the test, the moisture content does not change during shear. The data presented by Miller et al. (2001) was also used to evaluate the influence of the moisture content on the maximum shear modulus (Gmax) and moisture content. These data are shown in Figure 9. The shear modulus is typically used to reflect the stiffness of a material. As stiffness increases, the overall deflection of the material will decrease. Thus, the figure gives an indication of the influence of moisture content on the deflection response of subgrade soil. The maximum shear modulus values were obtained from the Hardin and Drnevich (1972) equation and is given by the following expression 3230 ( 2.97 − e ) (OCR )K (σ o )0.5 1+ e 2

Gmax =

(4)

where e = the void ratio; OCR = the over consolidation ratio; K = a constant = f ( plasticityindex, OCR); and σ o = mean normal stress = (σ 1′ + 2σ 3′ ) / 3; σ 1′ = maximum effective principal stress; and σ 3′ = minimum effective principal stress. As with Figure 8, a trend line has been included in Figure 9 to qualitatively show the influence on increasing moisture content. Although a unique expression cannot be obtained from the presented data, the figure clearly shows that increased deflection of the subgrade soil is associated with increased moisture content. It can be thus concluded that the use of HMA underlayment will yield stronger, more durable track structures and will resist excessive deflections. These factors imply safer and more economical tracks structures.

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Maximum Shear Modulus, Gmax (MPa)

50 Undrained 40 35 30 25 20 15 10 5 0 0.32

Figure 9.

4

Drained

45

Data from Miller et al. (2000) 0.33

0.34 0.35 0.36 0.37 Moisture Content, ω (%)

0.38

0.39

Influence of moisture content of the maximum shear modulus.

CONCLUSIONS

The primary purpose of this investigation was to assess the improvements to structural performance of trackbed structures provided by asphalt underlayment. For this study, two sites were selected for the trackbed pressure tests and structural performance assessments. The significant findings of this investigation include: − The overlying ballast acts as an insulator to the asphalt layer, protecting the HMA from sunlight and excessive temperature extremes. This significantly reduces oxidation and hardening of the asphalt binder and thus greatly increases the fatigue life of the HMA layer. − The combined supports provided by the HMA mat and the confined ballasts layer are believed to be primary contributors to the excellent track geometry indicators routinely measured over long periods of time. − The arching effects of HMA layer significantly reduces the level of stress transmitted to the subgrade soils. In particular, use of a 203 mm HMA underlayment reduced the subgrade stress by approximately one-half. Thus, it can be concluded that HMA layers will reduce the cyclic load-induced strength loss to the subgrade soils. − The track modulus tends to increase linearly with increasing asphalt thickness. The increase in track modulus implies a decrease in track settlement, which translates into more durable tracks. Thus, asphalt underlayment will tend to produce a general reduction of required maintenance cycles. − The asphalt underlayment significantly improves the pressure index. The factor of safety against punching shear failure increases by roughly 35 percent with 102 mm of HMA underlayment and by approximately 46 percent for 203 mm of HMA underlayment. − The in-situ moisture contents at the various asphalt underlayment sites were within one percent of the laboratory determined optimum values for maximum density of the respective materials. This implies that the strengths and load carrying capacities of the underlying materials remained uniformly high. All of these conclusions indicated that HMA underlayment will yield stronger, more durable track structures and will resist excessive deflections. These factors imply safer and more economical tracks structures. 1228

ACKNOWLEDGEMENTS The research was primarily supported by CSX Transportation and the BNSF Railway Company. The geotechnical laboratory testing was performed by the Geotechnical Branch of the Kentucky Department of Transportation. The asphalt laboratory testing was performed by the National Center for Asphalt Technology at Auburn University. William (Zach) Dombrow, BNSF Summer Intern from the University of Illinois, assisted with the sample collections and tests. REFERENCES Anderson, J.S. and Rose, J.G. 2008. In-situ test measurement techniques within railway track structures. Proceedings 2008 ASME/AIEE/ASCE Joint Rail Conference, Wilmington, DE, April, p. 21. Asphalt Institute. 1998. Hot mix asphalt for quality railroad and transit trackbeds. Informational Series IS-137, p. 10. Asphalt Institute. 2007. The Asphalt Handbook, MS-4, 7th Edition, Chapter 15.3 Railway Roadbeds, p. 832. Association of American Railroads. 2006. Railroad Facts, 2006 Edition, p. 84. Hardin B.O. and Drnevich V.P. 1972. Shear modulus and damping in soils: Design equations and curves. Journal of the Soil Mechanics and Foundations Division, ASCE, 98(7), pp. 667–692. Lambe, T.W. and Whitman, R.V. 1969. Soil Mechanics, John Wiley and Sons, NY. p. 553. Li, D. 2000. Deformations and remedies for soft railroad subgrades subjected to heavy axle loads. Geotechnical Special Publication No. 103 (GSP 103), ASCE, Denver, CO, pp. 307–321. Li, D., LoPresti, J. and Davis, D. 2002. Application and performance of hot-mix asphalt trackbed over soft subgrade. Railway Track & Structures, January, pp. 13–15. Li, D., Rose, J.G. and LoPresti, J. 2001. Test of hot-mix asphalt trackbed over soft subgrade under heavy axle loads. Technology Digest-01-009, Assoc. of American Railroads, April, p. 4. Meyerhof, G.G. and Hanna, A.M. 1978. Ultimate bearing capacity of foundations on layered soils under inclined load. Canadian Geotechnical Journal, 15(4), pp. 565–572. Miller, G.A., Teh, S.Y. and Li, Zaman, M.M. 2001. Cyclic shear strength of soft railroad subgrade. Journal of Geotechnical and Geoenvironmental Engineering, ASCE, 126(2), pp. 139–147. Rose, J., Brown, E. and Osborne, M. 2000. Asphalt Trackbed Technology Development: The First 20 Years. Transportation Research Record 1713, Transportation Research Board, pp. 1–9. Rose, J., Li, D. and Walker, L. 2002. Tests and evaluations of in-service asphalt trackbeds. Proceedings of the American Railway Engineering and Maintenance-of-Way Association, 2002 Annual Conference & Exposition, September, p. 30. Rose, J.G. and Lees, H.M. 2008. Long-term assessment of asphalt trackbed component materials’ properties and performance. American Railway Engineering and Maintenance-of-Way Assoc. 2008 Annual Conference PROCEEDINGS, Salt Lake City, UT, September, p. 50. Selig, E.T. and Waters, J.W. 1994. Track Geotechnology and Substructure Management, Thomas Telford Publishers, London, UK.

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Emerging trends for high-speed rail track superstructures— ballastless track as an alternative to the ballasted track A.M. Paixão, E.C. Fortunato & M.L. Antunes National Laboratory of Civil Engineering, Lisbon, Portugal

ABSTRACT: The rising demands placed on rail transportation and the need to make it more competitive have led to the development of new railway track solutions. With the objective to rationalize track costs, new railway superstructure systems have emerged. These new track solutions are technological innovations that differ from ballasted track in that they use other materials and construction methods. They are aimed to reduce the need for track maintenance and renewal, which in turn, leads to reduced operation costs as well as to higher track availability. In evidence of these advantages, there has been an increasing ballastless track construction, mainly in high-speed lines of some European and East Asian countries. Within this context, and bearing in mind that Portugal will be joining the European high-speed railway network, an overview aiming to address the emerging trends for high-speed railway superstructures and to compare them with the traditional ballasted track was developed. 1

INTRODUCTION

The White Paper presented by the European Commission in 2001 states that the European policy for the development of competitiveness and economic growth, supported by environmental and territorial social sustainability, is aimed at developing sustainable transport systems, emphasizing the railway transport. This has induced an increase on the development of European rail transport, both in terms of passenger and freight transportation. Regarding the technical aspects of rail track, recently there is a growing trend for the construction of ballastless superstructures, especially in new high-speed lines. These new track systems are technological innovations that differ from the traditional system (ballasted track) by using other materials and construction methods. Their main advantage is related with the optimisation of track costs, considering the infrastructure life cycle and the increasing demands imposed on railway operation, namely safety, service quality and environmental aspects. Although ballastless track has been adopted in Japan for many years, only recently other European and Asian countries have shown particular interest in such technologies. These new track systems are usually referred as “slab tracks” or “ballastless tracks”. The term “ballastless track” refers to the replacement of ballast with another element (such as reinforced concrete or asphalt layer). The term “slab track” is also used often to describe systems without ballast. In this paper the term “slab track” refers to a type of ballastless track with rails supported by a reinforced concrete slab. 2

TRENDS FOR HIGH-SPEED TRACK CONSTRUCTION

Nowadays, some ballastless tracks are being laid in European and East Asian high-speed lines. The change in track design is mainly due to the growing need to operate services for high-speed and freight with high quality standards and low maintenance costs. For some decades, new technologies and structural systems have been developed to meet those requirements. At present, these innovative systems are challenging the traditional solution.

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2.1 East Asian examples The Japanese Tokaido Shinkansen was the first high-speed line (Takatsu, 2007). Operations with the famous “bullet-train” started in 1964, linking Tokyo to Osaka, on a ballasted track. During its operation, it become clear to Japanese authorities that the ballasted track needed intensive maintenance and daily inspection to ensure a safe operation and to respond to the growing mobility demands of the Japanese economic expansion. Moreover, that track system presented reduced durability, demanding the renewal of ballast after only 12 years of operation. At that time, the Japanese context, particularly its high-rate economic growth, reduction in working hours, workforce shortage and limited interval time for track maintenance, led to the need for track systems that could provide higher durability and lower maintenance (Ando et al., 2001). After some years of research, a viable precast concrete slab solution was developed. This slab is placed on a concrete or asphalt roadbed with a bituminous cement mortar as interface. Due to ballasted track maintenance difficulties, in 1975, the Sanyo Shinkansen high-speed line between Osaka and Hakata (554 km) already included some slab track stretches, mostly between Okayama and Hakata (Takatsu, 2007). Since 1982, other Shinkansen lines, namely Tohoku, Joetsu, Horukiru, Kyushu, were built using mostly slab tracks. Currently, the total length of the Shinkansen lines is approximately 2100 km (Takatsu, 2007), of which about 58% is laid on slab track. Other Japanese highspeed lines currently under construction with slab track are the Hokkaido and Kyushu lines, as well as the extension of Tohoku and Hokuriku lines (Melis Maynar, 2006; Takatsu, 2007). In 2015, about 17% of the network length is expected to run on earthworks, 37% in tunnels, about 11% on bridges and 35% on viaducts. Such distribution promotes the construction of slab tracks. After the conclusion of these lines, the percentage of slab track in Japan is expected to exceed 65% of the total network length. In 2004, the first stretch of the South Korean high-speed line was put into operation between Seoul and Daegu (224 km). Much of the high-speed technology used in the first stretch came from France. When totally completed, the line will link Seoul to Pusan (412 km) with 189 km running in tunnel and 109 km on viaducts (Melis Maynar, 2006). Although almost half the line runs in tunnel, which generally favours slab track, ballasted track was installed in the first stretch. Recently, slab track was chosen for the second stretch between Daegu and Pusan, expected to be completed in 2010 (Chul, 2007). After some delays, only in 2007 did the first high-speed line in Taiwan go into operation. It connects Taipei to Kaohsiung on a 345 km slab track line. Similar to Japanese lines, most of its extension runs on viaducts or in tunnels, leaving about 10% of its length on earthworks (Shima, 2007). The high-speed technology used in this line was mainly imported from Japan. In response to its rapid growth, China is probably the country with the greatest expansion in high-speed rail. There are several lines under construction, as well as many others in planning stage. The high-speed railway Passenger Dedicated Lines project (PDL) consists of 4 major East-West axes and 4 South-North crossing eastern China. To illustrate the magnitude of such project, the total length of the network planned for 2020 exceeds 10,000 km (Okada, 2007; Huawu & Wenwei, 2006), which is about the length of high-speed lines in operation in the World and twice the length of the European network at present date (Barrón, 2008). In the process of choosing a track system for these Chinese lines, the advantages of ballastless track have been acknowledged and most lines will have slab tracks. The construction of these lines is a crucial turning point for the development of ballastless track systems and possibly an important milestone for such track solutions. Among the lines from the PDL project with slab track, reference is made to the recently opened line between Beijing and Tianjin (116 km) and the two lines under construction, between Zhengzhou and Xi’na (459 km) and between Wuhan and Guangzhou (1000 km). 2.2 European examples Nearly 20 years after the first Japanese high-speed line, France built the first European high-speed line, the LGV Sud-Est, connecting Paris to Lyon (538 km), which fully opened 1232

in 1983. Its unquestionable success changed the design of rail track in Europe. Mostly thanks to this event, currently rail transportation is a major competitor to shorter European air routes. Although the Japanese experience in Tokaido line showed that ballast had a short lifetime, the Sud-Est line was built with ballasted track. Furthermore, it was built several years after Japan had decided to use mostly slab track in the second section of Sanyo line in 1975 and after the construction of Tohoku and Joetsu lines with about 90% of slab track. The main reasons which led to the adoption of ballasted track in France were the fact that it provided a lower cost of construction and ensured easier track geometry corrections. Moreover, at that time there were no references to commercial speeds of 300 km/h on ballastless tracks. The lifetime of the ballast in Sud-Est line also came out to be short. That experience was not negative enough for the French railway administration to choose for another track system. The following high-speed lines in France were constructed using ballasted track. With the exception of some tunnels, in which slab track systems are used, the French high-speed network accounts for about 1800 km on ballasted track. The maintenance of such an extensive network is a huge economic weight. In order to evaluate new track solutions, SNCF has been testing sections of slab track and bituminous sub-ballast track for LGV Est (Dieleman et al., 2008; Gautier, 2006). The projection of ballast particles (“flying ballast” phenomenon) is also being investigated (Rail & Recherche, 2007). Germany seems to be the major driving force in Europe for the development of ballastless track solutions. Since the 70’s, many solutions were developed to respond to the needs of German rail network. Some have become quite successful and currently are also being installed in other countries. In 1994 it was decided that German lines with speeds greater than 200 km/h would include ballastless tracks. Since then, more than 800 km of ballastless tracks were installed in Germany. Among the examples of ballastless track application there are the high-speed lines Berlin— Hanover, Cologne—Frankfurt and Ingolstadt—Nuremberg. In the last two, the slab tracks allow Eddy-current braking technology to be used without restrictions (Schykowski, 2008). The existence of a vast rail network with standard gauge is an important aspect when analyzing the German case. Having in mind that eventual repair work on ballastless tracks can be more difficult and time consuming than on ballasted track, the possibility to deviate traffic locally, to a secondary line, may become quite useful if such maintenance work takes place. Another advantage of ballastless systems in Germany is the fact that allows more freight traffic to run during the night. Ballastless track offers maximum track availability because it does not require the same exhaustive maintenance work as ballasted track. Yet, other track systems have also been developed in Europe. The use of bituminous subballast tracks in Italian high-speed lines started with the Direttissima line in 1978, connecting Rome to Florence. The application of such system was quite positive and it was decided that the following Italian high-speed lines would adopt such solutions as well. Along with those developments, many ballastless track stretches were also tested in the end of the 80’s, mainly in tunnels and rail stations. Taking into account the success of slab track in Japan, Italy also developed its own precast concrete slab system. Starting from the Japanese concept, a new precast slab was designed to adapt to specific transalpine rail operations, particularly in the line from Udine to Tarvisio, completed in 1999. The line allows speeds up to 230 km/h running on a large number of viaducts and tunnels, near the Austrian border. At present date, the Italian highspeed network is expanding, namely with the construction of the new Turin—Milan—Naples line, with more than 600 km. Rehabilitation work on the Direttissima line is also underway, with a total of 253 km, and interventions are planned on Milan—Venice and Milan—Genoa lines, comprising 300 km. All these new lines include bituminous sub-ballast layers of 0.12 m thick. Recently, Spain has faced a considerable expansion of its high-speed rail network which started in 1992 with the opening of Madrid—Seville line. Other lines followed: the North corridor, connecting Madrid to Valladolid; the Northwest corridor, connecting Madrid to Barcelona; the Mediterranean corridor, from Barcelona to Valencia; and other lines, like the future connection to the Portuguese border. The Madrid—Seville line was built using ballasted track. This decision was partly influenced by the short timeframe available for the design, as well as due to the tight schedule to carry out all the construction work. Additionally, at that time, the European ballastless track solutions did not offer sufficient guarantees 1233

(Melis Maynar, 2006) and the cost of ballast was not as high as in other countries. It is also important to highlight that the existing network has Iberian gauge (Puebla Contreras et al., 1999) and, as the high-speed lines were being constructed with standard gauge, this would bring an additional risk in case of unexpected maintenance or repair work on this line, if ballastless track was installed instead. The Spanish experience with ballastless systems on high-speed lines is mainly focused in tunnels, particularly in the recent tunnels of Guadarrama, San Pedro and in a series of tunnels from the Atlantic corridor. Particular reference is made to a stretch between Las Palmas de Castellón and Oropesa del Mar, in the Mediterranean corridor, where six different ballastless track systems, of 432 m each, were put to test in 2002. These test stretches were installed to study specific aspects related with the construction methods and with the behaviour of such new track systems on earthworks (Peña, 2003). In The Netherlands, due to the widespread presence of soft soils, specific systems providing better answers to these circumstances have been studied. Particularly slab track systems with embedded rail have been developed since the 70’s. Some of these systems have been successfully applied in small trial stretches, obtaining good results in terms of reducing track maintenance. There are also cases of large-scale construction, like the new high-speed line HSL—Zuid (125 km), connecting Amsterdam to the southern border with Belgium. The poor bearing capacity of the soils led to the use of settlement free systems. Most of the line is set on slab tracks on top of piles or on viaducts or in tunnels. The soil poor bearing capacity and the 25-year contract between the Dutch State and Infraspeed consortium, were probably decisive factors for the selection of a ballastless track system.

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BALLASTLESS TRACK

The need to develop new track systems arouse from the fact that ballasted track requires frequent maintenance operations, resulting in maintenance costs and. reduced track availability. As referred to above, these track systems began to be used on a large scale in Japan. In many other countries its use was deferred due to improvements made to ballasted track, such as: more resistant rails, heavier sleepers, higher requirements for ballast and supporting layers. Other major causes were higher costs of new track systems and the development of new heavy maintenance machinery that considerably made operations faster and easier for ballasted track. However, other factors such as increased lifetime, lower life-cycle costs, greater track availability, higher speeds and high levels of passenger comfort became more and more important in the design of new rail lines which have recently pointed out to ballastless track systems. There are many ballastless track systems which, for example, can include concrete sleepers embedded or supported on a concrete slab or asphalt layer, or even systems with rails directly fastened or embedded in a concrete slab (see Figure 1). In comparison with the typical ballasted track cross section, the ballastless track generally comprises three supporting layers: – First, the top layer may consist of a Concrete Supportive Layer (CLS) or an Asphalt Supportive Layer (ASL) that supports the track panel and distributes the loads from vehicles to the underlying layers. Such layer needs to fulfil high durability requirements. In the case of a CLS, it must show a controlled cracking pattern and resist to frost and defrost cycles. Regarding the ASL and comparing to roadway construction, more demanding parameters apply. – The intermediate layer is usually referred to as Hydraulically-Bonded Layer (HBL). It is made of aggregates treated with hydraulic binder that rest beneath the CLS or ASL and distributes the loads to the underlying layers. In tunnels or bridges, this layer may be suppressed by an increased thickness of the upper concrete slab or by improvements on the foundation conditions. – Lastly, the Frost Protection Layer (FPL) is made of granular material, with properties similar to the sub-ballast as used on ballasted track. It supports the HBL and distributes 1234

the loads to the foundation. It must show a high resistance to frost-defrost cycles, as well as provide good drainage conditions to the track. In general, the construction of ballastless tracks is more expensive with the offset of considerably lower maintenance operations. Most efforts are put on reducing track maintenance and increasing track durability rather than on easier partial repair or renewal work (UIC, 2002). There is a variety of ballastless track systems which were developed to solve specific requirements, concerning geotechnical, environmental and operational issues. Ballastless systems with rails supported on discrete points are used more frequently. These points consist of fastenings on concrete sleepers or blocks that place the rail into a precise position. The track panel made of sleepers and rails can be laid on an ASL or embedded on a CSL (Figure 2a). Other systems comprise booted sleepers or blocks, in which an elastic layer separates the CSL from the concrete sleepers or blocks. Some systems comprise rails directly fastened to the CSL. Usually these systems consist of concrete precast slabs (Figure 2b) but there are also systems using concrete slabs cast in-situ or that directly fasten the rail to the bridge deck or to the tunnel base.

Figure 1. Most common ballastless track designs: (1) Rail with sleeper on CLS or ASL; (2) Rail without sleeper on CSL; (3) Rail embedded on CSL (Quante, 2001).

Figure 2.

(a) Installing Züblin system;

(b) Precast slabs by Max Bögl (Photos: DB AG).

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Ballastless tracks systems with continuously supported rails have also been used. Usually, two parallel grooves are left on the CSL. The rails are placed inside the grooves and filled with an elastic compound so that the rails become embedded in the CSL. The variety of ballastless track systems may be organized in groups or families that share the same basic design or main characteristics. In Tables 1 and 2, the main features of each family are summarized. Examples of most representative systems are also given.

Table 1.

Ballastless track systems with continuous rail support: examples and relevant aspects.

System family

Examples

Main features of the system family

Embedded rail

Edilon ERS BBest

Construction of concrete slab using slipform pavers. Better load distribution. Reduced dynamic effects transmitted to the track. Lower rail wear. Reduction of noise. Rail grinding and replacement operations more complex. No fastenings needed. Higher track durability and geometric maintenance. May lead to more expensive solutions.

Table 2.

Ballastless track systems with discrete rail support: examples and relevant aspects.

System family

Examples

Main features of the system family

Track panel on asphalt layer

ATD GETRAC

Track panel on concrete slab

BTD

Sleepers or blocks on embedded concrete slab

Rheda Züblin

Booted sleepers or blocks embedded on concrete slab

Stedef SATEBA S312 LVT— Sonneville

Double resilient fastenings

Vossloh DFF 300 Edilon EDF Pandrol VIPA

Precast concrete slabs

J-Slab ÖBB-Porr FF Bögl

In-situ concrete slabs

BES BTE

Bottom-up construction method using paving machines. Construction vehicles can circulate on asphalt layer shortly after paving. Rail cannot be directly fastened to asphalt layer. Possibility to reuse old ballast between sleepers to reduce noise and to protect asphalt layer. Noise emissions slightly lower. Easier repair and replacing operations. Lower durability and stability compared with concrete systems. Less frequent system. Construction of concrete slab using slipform pavers. Easier sleeper replacing, possible correction of geometry. German systems. Usual for track on earthworks. Generally features top-down construction method. Replacement and repair of elements more complex. Higher track durability and geometric maintenance. Often used in tunnels. Generally features top-down construction method. Reduced vibrations to the surroundings. Increased vertical resilience. Easier sleeper replacing and possible correction of track geometry. May lead to more expensive solutions. Usually used on viaducts or tunnels in urban areas. Higher resilience. Reduced emission of vibrations to the surroundings. Fastenings may also be used with in-situ or precast concrete slabs. Widely used in Japan. Better quality of the final product. Reduced work at the construction site. Laid on asphalt layer or on hydraulically bounded layer. Higher track durability and geometric maintenance. May lead to more expensive solutions. Less frequent system. Construction of concrete slab using slipform pavers. Replacement of elements more complex. May lead to economic solutions.

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4

BALLASTED TRACK AND BALLASTLESS TRACK COMPARISON

When describing ballastless track, the comparison with ballasted track is inevitable because it is still the most common track system, accounting for almost 80% of high-speed lines worldwide, which recently reached up to 10,000 km. It is important to highlight that conclusions from other studies, concerning the viability of ballastless tracks, when compared with ballasted tracks, are clearly not consensual. Nevertheless, the majority of ballasted track problems are well-known. They are related with the ballast contamination by fines, with its instability under vibrations produced by vehicles and with reduced lateral track resistance. Regarding high-speed lines, some specific downsides concerning ballasted track can be summarized as follows (Riessberger, 2008): – When the track is loaded, considerably high contact stresses occur between the sleeper’s underside and the ballast particles, which result in faster track deterioration. – In some situations, there is a rapid decrease of track geometric quality after tamping operations besides the fact that frequent operations to restore track position increase the rate or ballast deterioration. – Important plastic deformations associated with the track superstructure and substructure may require extensive maintenance work. – The reduced uniformity of track elasticity results in irregular elastic deformations, as well as in an increase of dynamic loads from vehicles. – The regular spacing between rail support points may transmit harmonic vibration to

the surrounding environment. – Limited lateral track resistance offered by the ballast makes the track vulnerable to buckling phenomenon when rails are subject to high variations of temperature or when braking systems are applied using frictional or Eddy-current systems. At a certain level, the above problems can be controlled by reducing speeds at critical points or by implementing frequent maintenance work. Technological solutions are also being developed to solve specific problems and to reduce maintenance work. Some solutions consist on increasing vertical track resiliency with base plate pads under the fastenings, with elastic pads under the sleepers, with ballast mats or by including bituminous sub-ballast layers. Another issue under discussion is the projection of ballast particles, also known as “flying ballast” phenomenon, which may eventually damage rails and vehicles. Regarding the design of ballasted tracks for high-speed lines, perhaps one of the most important constraints is the difficulty to design a structure that presents high longitudinal uniformity. The variation of track parameters in longitudinal development is related with the difficulty to obtain a regular vertical stiffness, due to the variable characteristics of the superstructure and substructure elements. The main advantage of ballastless track is that the problems mentioned above are reduced and because this system requires practically no maintenance. As a result, higher track availability is offered and maintenance work is strongly reduced. But there is a drawback: ballastless systems are generally more expensive. The difference of construction costs between the two systems may vary widely among countries and railway administrations. Esveld (2001) refers an increase of construction costs by 20%, but a reduction of 70–80% of maintenance costs. Ballastless installations in Germany revealed an increase of 20–50% of initial costs (Mörscher, 1999). On the other hand, Spanish authors suggest higher costs: 2 times (Fernández Gil & Fernández, 2006) to 4 times the ballasted track cost (Olza Galé, 2007). Regarding a study by UIC (Stalder, 1999), ballastless tracks are in average 2.6 times more expensive. In specific situations, in new Japanese lines, the construction of ballastless track was even less expensive than ballasted track. For the Hokuriku high-speed line, the average construction costs on excavations and embankments were respectively 18% and 24% higher, (Ando et al., 2001). It should be noted that the construction of small test sections, usually result in higher construction costs. The development of higher levels of mechanization to install long sections of ballastless tracks is essential to reduce construction costs and increase construction speeds. 1237

In Table 3, a summary with the comparison between ballasted track and ballastless track is presented, addressing some of the most relevant issues. The ballasted track superstructure is a less restrictive solution allowing settlements on the substructure, as long as frequent geometry corrections and maintenance works are carried out, namely tamping, alignment and levelling operations. On the contrary, ballastless track superstructure does not require systematic maintenance works and geometric corrections during its lifetime. However, due to its characteristics, especially high bending stiffness, the values for the parameters of the supporting layers need to be more demanding. While the post-constructive settlements in ballasted track can be corrected later, differential settlements on ballastless tracks need to be avoided due to displacement incompatibility between the ballastless track and the substructure. Moreover, the capability to make geometric adjustments on ballastless tracks is highly limited. Fastenings play a key role since all geometry corrections have to be made at that level. Therefore, settlements are limited by the capability of the fastenings to accommodate these vertical adjustments. Many fastening systems allow vertical adjustments up to 30 mm, though some new systems specify a vertical adjustment of 60 mm. As exposed above, it is clear that the construction of track substructures for ballastless tracks requires a tight control. Supporting layers need to be homogeneous and capable to withstand imposed loads without significant settlements. Ultimately, one of the main

Table 3.

Comparison between ballasted track and slab track (Estradé Panadés, 1998, adapted).

Issue

Ballasted track

Ballastless track (Slab track)

Construction costs

lower investment costs compared with slab track

Vertical stiffness

unevenness of vertical stiffness, but positive contribution of ballast

Track stability

limited lateral track stability due to ballast mechanical properties

Ballast projection Eddy-current brakes

projection at very high speeds limited use due to the possibility of track instability

Noise

good noise absorption

Safety

no access for road vehicles

considerably higher investment costs if no mechanized processes are implemented during construction Lifetime depending on the amount of traffic, expected 60-year of service life, may need renewal after 30 years but little experience with some systems Cross section deeper section and larger area in plan view reduction of structural height and lower dead loads on bridges Maintenance, renewal frequent and costly maintenance works; reduction of maintenance work; and rehabilitation may need replacement of some elements renewal and rehabilitation costs with shorter lifetime work is more complex Track availability conditioned by maintenance work nearly full availability Layout track alignment can be corrected corrections extremely limited but with the help of machinery maintains higher geometric quality

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higher control of stiffness; requires additional attention to transitions increased stability allowing smaller radii in curves and greater adaptation to field n/a allows the use of Eddy-current braking systems for high-speed vehicles higher noise levels; elements to reduce noise maybe needed most slab track systems allow access to emergency vehicles (e.g. in tunnels)

requirements of ballastless tracks is a settlement free support. Such requirement generally leads to greater costs due to higher geotechnical constraints. Along with the economic aspects, controlling settlements is probably one of the most restrictive factors for the construction of ballastless tracks. The cost to build a line with ballastless track may dependent greatly on initial geotechnical conditions. In order to minimize long term settlements, the height of embankments should be reduced and areas with soft soils should be avoided. Compaction of the underlying layers must follow rigorous planning. When constructing new embankments, it is crucial that great part of the long term settlements has already occurred before installing the track superstructure. If such circumstances are not met, the availability of the track for the desired levels of operation may become compromised. Therefore, it is crucial to carefully control long term settlements on supporting layers to ensure that the desired lifetime of the superstructure will not be influenced by problems resulting from differential settlements. In situations where it is not possible to achieve the necessary geotechnical parameters by means of compaction, specific soil treatments should be conducted. Alternatively, ways to avoid this problem include the use of gravel piles under the embankment or ballastless track systems with reinforced concrete slabs supported on drilled-piles (Frühauf et al., 2008). Ultimately, with the construction of track on viaducts or in tunnels, these problems become less relevant. Consequently, these geotechnical constraints lead to the design of ballastless lines avoiding earthworks, favouring long tunnels and viaducts, which seem to be the case of most Japanese high-speed lines. Thus, the construction of ballastless track may appeal for the revision of the design of new high-speed lines. This view is suggested by some authors (Melis Maynar, 2006) and is also evidenced in Japanese lines. To ensure good foundation conditions, as well as higher superstructure performance, there are some recommendations for the parameters of ballastless track supporting layers. For example, in new German high-speed lines, the minimum EV2 value (deformability modulus obtained in the 2nd cycle of the plate load test (UIC, 2008)) on top of the embankment and frost protection layers are 60 MPa and 120 MPa, respectively (Esveld, 2001). The analogy with ballasted track recommended values, as defined in the Code UIC 719 R (2008), is evident. The document specifies that the minimum value of EV2 on the upper surface of the embankment is 45 MPa, with fine soils, and 60 MPa, with sands or gravel. A minimum of 80 MPa on the capping layer is required and on top of the sub-ballast the minimum value is 120 MPa.

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CONCLUSIONS

In new high-speed lines, choosing a track system without ballast is often supported on the basis that larger initial investments will be counterbalanced with the reduction of maintenance operations and with greater track availability, which was the case of the Japanese network. Another situation relates with the need to run a great amount of freight traffic during the night, like in the German network. In these cases, maintenance operations are restrained by short periods of track availability. Moreover, the circulation of freight vehicles leads to faster track deterioration. This situation becomes more relevant if heavier axle loads are allowed. It may also be one of the reasons why France and Spain continue to build new high-speed lines with ballast, because in these countries there is almost a total segregation of the lines by traffic type. External constraints and specific technical considerations of each project influence the cost of high-speed lines, influencing the choice between ballasted and ballastless track. For example, as verified in Japanese lines, the cost to install ballastless track on bridges or in tunnels is almost equivalent to the cost of ballasted track. Consequently, in high-speed projects with greater extension of track running on viaducts or in tunnels, the construction of ballastless track will most certainly be more favourable. Though, aspects related with the availability of resources, mainly raw materials and manpower, may be decisive factors when choosing the track superstructure. The fact that leading countries on high-speed industry, such as France, continue to build railways on ballast is the evidence that the choice between ballasted and ballastless track 1239

is not consensual. The answer to that is not limited to a life-cycle costs analysis, but also requires the consideration of many other parameters and specific elements of each project. From the study of new track systems and from the application in different countries, some relevant aspects when selecting track systems can be summarized as follows: – Design parameters for the track, namely maximum design speed, minimum curve radius, maximum cant, track vertical stiffness, vehicle characteristics, among others. – Initial investments and maintenance costs during the lifetime of the structure. – Resources availability, mainly raw materials and manpower. – Experience gained from other railway administrations from different countries. – Homologation of new track systems from recognized entities. – Particular specifications for the construction in tunnels, bridges or earthworks. – Construction methods to achieve higher track construction rates and geometric quality. – System's capability for geometric corrections related with differential settlements on the foundations. – Integration with other systems (signalling, telecommunications and drainage). – System’s ability to adapt to accessibility and safety constraints. – Restrictions to noise and vibration emissions. – Possibility to easily replace worn or damaged elements. Complexity of renewal and repair operations after accidental situations. New business models, regarding projects of new railway lines, may also become a decisive factor in shaping the future of these new track systems. For example, the definition of a Design-Build-Operate contract with an extended concession period leads to a careful lifecycle cost analysis, probably bringing up the advantages of these new track systems. The future success of these systems will depend on the ability to adapt to high-speed railway economic and technical requirements. Its development is expected to continue, aimed to optimize design, constructive methods and operation performances. ACKNOWLEDGEMENTS The authors acknowledge the financial support of R&D project “PTDC/ECM/70571/2006— Optimisation of High-Speed Railway Track Using Bituminous Sub-ballast” funded by Fundação para a Ciência e a Tecnologia (FCT), from Portuguese Ministry of Science, Technology and Higher Education. REFERENCES Ando, K., Sunaga, M., Aoki, H. & Haga, O. 2001. Development of Slab Tracks for Hokuriku Shinkansen Line. Quaternary Report of RTRI 42(1): 35–41. Barrón, I. 2008. High Speed Lines in the World, UIC High Speed Department, Updated 04 June 2008. Chul, L.K. 2007. Launch of Korean High-Speed Railway and Efforts to Innovate Future Korean Railway, High-Speed Rails in Asia. Japan Railway & Transport Review 48: 30–35. August 2007. Dieleman, L., Fumey, M., Robinet, A., Ramondec, Ph. & Martin, D. (2008) Experimentation of a track section without ballast on the new line of East European TGV, 8th World Congress on Railway Research, 18–22 May 2008. Seul. Estradé Panadés, J.M. 1998. La superestructura de via en placa en las nuevas líneas de alta velocidad de nuestro pais. Revista de Obras Públicas 3372: 63–74. Esveld, C. 2001. Modern Railway Track. 2nd Edition. Zaltbommel: MRT-Productions. Fernández Gel, A. & Fernández, M.G. 2006. Track Performance on New High Speed Lines in Spain, Track for High-Speed Railways: 103–126, Workshop, 12–13 October 2006. Porto. Frühauf, W., Jungwirth, J., Schloz, M. & Stoiberer, H. 2008. Slab track systems on engineering structures—A holistic design approach. Railway Technical Review, Special (March 2008): 78–88. Gautier, J.L. (2006) Asphalt treated base material under ballast: an innovative experiment on the East European high speed track, Track for High-Speed Railways: 309–314, Workshop, 12–13 October 2006. Porto. Huawu, H. & Wenwei, H. 2006. Development of ballastless track technology on China Railways (CR). Railway Technical Review, Special (September 2006): 18–22.

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Melis Maynar, M. 2006. Terraplenes y balasto en Alta Velocidad Ferroviaria—Segunda parte: Los trazados de Alta Velocidad en otros países. Revista de Obras Públicas 3468: 7–26. Mörscher, J. 1999. Slab Track Roadbeds in Germany—Implementation and Experience. AREMA 1999 Annual Conference. 13–15 September 1999. Chicago. Okada, H. 2007. High-Speed Rails in China, High-Speed Rails in Asia. Japan Railway & Transport Review 48: 22–29. August 2007. Olza Galé, A.O. de. 2007. Nuevas tendencias en el diseño de vía, Jornadas Ténicas: Ingeniería para Alta Velocidad, Viente Años de Experiência en España: 281–301. 27–29 July 2007. Cordoba. Peña, P.M. 2003. Tramos de ensayo de vía en placa en la línea del corredor del Mediterráneo para su explotación a alta velocidad 1. Diseño y construcción, Revista de Obras Públicas 3431: 57–68. Quante, F. 2001. Innovative Track Systems—Technical Construction, ProMain. Rail & Recherche (2007) Does ballast fly at high speed, SNCF Rail & Recherche 42. Jan/Feb/Mar 2007. Riessberger, K. 2008. Ballasted Track for High Speed Operation, Railway Technical Review, Special (March 2008): 55–60. Shima, T. 2007. Taiwan High Speed Rail, High-Speed Rails in Asia. Japan Railway & Transport Review 48: 40–46. August 2007. Stalder, O. 1999. International Benchmarking of Track Cost. AREMA 1999 Annual Conference. 13–15 September 1999. Chicago. Schykowski, J. (2008) A long road to success, Eddy-current brakes—Research, Railway Gazette International, May 2008: 301–303. Takatsu, T. 2007. The History and Future of High-Speed Railways in Japan, High-Speed Rails in Asia. Japan Railway & Transport Review 48: 6–21. August 2007. UIC, 2002. Feasibility study “ballastless track”. Infrastructure Commission—Civil Engineering Support Group. 08 April 2002 version. UIC. 2008. Earthworks and track bed for railway lines, Code 719R. 3rd edition, February 2008.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

An innovative slab track test-line in China J. Ren School of Civil Engineering, Southwest JiaoTong University, Chengdu, Sichuan, China

R. Xiang School of Traffic and Transportation, Southwest JiaoTong University, Chengdu, Sichuan, China

B. Lechner Institute for Road, Railway and Airfield Construction, Munich University of Technology, Munich, Germany

ABSTRACT: This paper presents the innovative slab track technology that was implemented in 2004 by the Chinese Ministry of Railways (MOR). The railway test-line Suiyu was decided to carry out, on which innovative slab track technology would be applied. With a total length of 13.157 km, the new line stands in southwest of China, which is one part of the eight planned passenger dedicated lines (PDL) in China. It is expected to be loaded annually with 20 million tonne freight transportation and daily with 90 passenger train-couples. Its design speed amounts to 200 km/h for passenger trains and 120 km/h for freight trains, which is the first railway line built with such speed in southwest of China. Six slab track types have been installed on the test-line as a trial, which are introduced in details in this paper, such as reinforced concrete slab with lattice two-block sleepers or with pre-stressed monolithic sleepers, coupled or uncoupled prefabricated slabs-superstructure etc. Turnouts have been laid with embedded, monolithic sleepers for the first time. Special measures were applied for transition zones. Comprehensive measurements in respect of their qualities have been carried out, meanwhile train experiment has also implemented to test every component of slab track as well as substructure. 1

INTRODUCTION

In 2004 the Chinese Ministry of Railways (MOR) decided to carry out a railway test-line Suiyu (Suining City-Chongqing City), on which innovative slab track technology would be applied. With a total length of 13.157 km, the new line is shown in Figure 1 (highlighted part) together with other existing main lines and scheduled PDLs (Passenger Dedicated Lines). On this test-line six types of slab track were chosen to verify their suitability for high speed railway, which makes the scheduled powerful high-speed railway network possible in China. Besides, some particular boundary conditions should be adapted, such as the load bearing capacities of track on subsoil, on bridges, in tunnels or in turnout zones. In order to gain a systematic analysis and evaluate the applicability of the six slab track types, long-term observation on behaviors of slab track systems has been carried out and the first outcome was already on hand. The following particular challenges showed its importance: – Slab track system on a 450.7 m long bridge for the first time in China (crossing the Beibei-Jialing-River) – First turnouts in slab-track-construction; inside this test section there is a train station with 8 turnouts – Experiment of new construction methods for slab track, e.g. laying of 100 m long rails – Moreover, this first test section plays an exemplary role for the other planed high speed railway lines. 1243

Figure 1. Existing Chinese railway main lines with scheduled expansion constructions and new passenger dedicated line network (thicker lines).

In the future the track superstructure types in China should guarantee the required stability and durability both for upgrading of existent lines and for new building of PDLs. Slab track will be more and more of significance, for maintenance of superstructure will be complicated due to intensification of train schedules. 2

THE HISTORICAL DEVELOPMENT OF SLAB TRACK IN CHINA

In the last decades diverse types of slab track have been developed in many countries and are adaptive to roadbed, tunnels, bridges as well as viaducts. Especially Germany and Japan have already long term practical experiences of slab track on high-speed railway lines. In Japan the most parts of bridges and tunnels were built exclusively with slab track on the Shinkansen. The positive experiences with slab track on roadbed in German railway network gained many positive effects. Both are significative model for us. Slab track was taken into account because of the adjustability of high-speed railway. On one side it is distinguished from ballasted track through extension its service life until 60 years; on the other side it is possible to use sharper radii and correlative shorter alignment by enlargement of rail superelevation and the tolerable non-balanced lateral acceleration. Moreover, the lower structural height compared to ballasted track allows a reduction of tunnel cross-section. Investigations into slab track techniques began to be conducted in the sixties of the previous century in China. In the initial phase several slab track types have been applied on altogether 300 km sections for trial, and generally on short bridges, e.g. monolithic system with mono-block sleepers embedded in concrete as well as slab track system with asphalt base course. Figure 2 and Figure 3 show respectively the prefabricated panel system with bituminous bottom casting upon concrete substructure (on bridges or in tunnels) and upon an asphalt base course (on embankment). Since 1995 slab track was increasingly brought to the 1244

Concrete slab Rail Bituminous bottom casting Concrete substructure Figure 2.

Slab track at Pingguoyuan-station, Beijing 1967.

Concrete slab Bottom casting Asphalt base course Compacted embankment Figure 3.

Slab track at Chengdu-station, Chengdu 1978.

Figure 4. Monolithic system (with embedded monolithic sleepers).

Figure 5. Prefabricated slabs-superstructure Type A on the Gouhe bridge.

foreground in Chinese railway construction, in course of which top concern was firstly concentrated on three main types, namely prefabricated slab, monolithic sleeper system (“classical” Rheda system from Germany) and elastically supported two-block-sleepers. Figure 4 and Figure 5 show slab track systems in China, which were built on Qinhuangdao-Shenyang railway line in 1999. However the slab track sections here were only installed on short bridges and in tunnels for test. Taking a look at the development process of slat track lines in China, it could be concluded that existing slab track until 2006 were not yet implemented systematically, i.e. on continuous track sections inclusive of turnout. Therefore the first test-line has been constructed in China to gather experiences with design, construction or building of slab track in different fields. This first test-line of slab track acts as a prototype for the current existent or future high-speed railway lines. 3

OVERVIEW OF THE RAILWAY LINE SUINING-CHONGQING

The design speed of the railway line Suining-Chongqing amounted to 200 km/h for passenger trains and 120 km/h for freight trains. The line, which continues from Suining (city) across Tongnan (a district town) and Hechuan (city) towards Chongqing (a municipality), is the 1245

first railway line driven with such speed in southwest of China. A minimal curve radius of 1600 m and a maximal gradient of 6‰ were applied on it. This test section is situated on the new line from the new Beibei-Jialing-River-Bridge to the new JiangJiaQiao-Bridge. The characteristics of its segments are arranged in Table 1. 4

SLAB TRACK TYPES ON THIS TEST-LINE

The fulfilled six slab track types on this test-line are shown in Table 2. 4.1 Prefabricated slabs-superstructure Type A and Type VA Three prefabricated slabs-superstructure types came into operation on this line, namely type A, type VA (with rubber mats) and Prefabricated slabs-frame. Prefabricated slabs-superstructure consists of rail CN 60, elastic fastening system, track slab (supporting deck or supporting frame) above bitumen-cement-mortar, and possibly rubber mats (only for type VA for noise and vibration reasons). A circular concrete cylinder (Concrete mandrel), which is rigidly connected with the structure concrete of bearing plates, ensures the position of prefabricated slabs above the track concrete underlayer in longitudinal and lateral direction. With regard to the adaption of prefabricated slabs in different areas on test section, five types altogether have been put into use, which were respectively prestressed and no-prestressed slabs, prestressed and no-prestressed frames as well as prefabricated slabs with elastic mats. Representative cross sections of prefabricated slab construction are illustrated with Figure 6. Table 1.

Characteristics of substructure.

Substructure Embankment bridges

Tunnels

length (m)

number

Beibei-Jialing-River ZhangJiaYuanZi ZhiChangGou Total of bridges

5 398 450.70 101.1 159.92 711,7

1 1 1 3

LongFeng-Tunnel WanLiTou-Tunnel ErYan-Tunnel MuYuShan-Tunnel Total of Tunnels

5 217 207 987 569 6 980

1 1 1 1 4

Slab track turnouts Table 2.

8 suits

The lengths of different slab track types on the test-line. Test section length

Slab track types

m

Prefabricated slabs-superstructure Type A (comparable to Japanese slab track) Prefabricated slabs-superstructure Type VA (with rubber mat based on Type A) Prefabricated slabs-frame (individual slabs with frame-form) Prefabricated slabs, coupling at joins in longitudinal direction (comparable to German Bögl system) Reinforced concrete slab with lattice two-block sleepers (comparable to Rheda 2000-System) Reinforced concrete slab with pre-stressed monolithic sleeper (monolithic system) Total

2 291 320 4037 752 5 285 412 13 157

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Track concrete underlayers of 3.2 m width and 30 cm thickness have been applied on embankment. In tunnels track concrete underlayers with 20 cm thickness were directly located on tunnel bottom layer, on which transverse joints were set every 50–60 m according to the segment joints of tunnels. The 2.8 m wide, minimum 20 cm thick concrete base from concrete grade C40 (corresponding to Chinese standard: cube compressive strength 40 N/mm2) was settled on bridge, which is combined with protection concrete layer through tie bars. The concrete bases were respectively disconnected corresponding to structure joints and slab length (l = 4.856 m or 3.920 m), so as to restrict additional constraint in rail fastenings due to longitudinal extension and bending of bridge structure. 4.2 Concrete slab with lattice type two-block-sleepers This slab track type uses rail CN 60, high elastic fastening systems, two-block-sleepers with untensioned lattice truss reinforcement which is integrated into reinforced track slab, track concrete supporting layer and frost protection layer on embankment or concrete base on bridges alternatively. Figure 7 and Figure 8 show the design installed in tunnels.

Prefabricated slab Concrete underlayer

Fastening system

Concrete mandrel Figure 6.

Bitumen-cement-mortar

Detailed conformation of Type A.

Figure 7. Reinforced concrete slab with lattice two-block sleepers.

Figure 8. system.

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Prefabricated slabs-frame

On embankment a track concrete supporting layer of 3.6 m width and 30 cm thickness was executed, where notches were shaped in every 5 m. Track slabs of 4.98 m length, 2.8 m width and 25 cm till 35 cm thickness were cast in situ from concrete grade C40 on embankment or in tunnel. And they have been divided in every 4.856 m distance on bridges by setting 80 mm wide joints (sleeper distance 617 mm), whereas those joints between two bridge box girders are 120 mm wide. Upper and bottom reinforcement bars were disjoined from transverse reinforcement bars by isolation sleeves. The concrete base on bridges were likewise produced from concrete grade C40 into 2.8 m width and a minimum thickness of 170 mm, in which a embedded coupling reinforcement is perforated into the protection layer of bridge. Stopper interferences were arranged at both ends of every concrete base plate to provide sufficient fixation of track plates in longitudinal and transverse directions. A foil interface separated concrete slabs of track from concrete base plates of bridges. 4.3 Coupled prefabricated slabs on the Beibei-Jialing-river Bridge In 1977, the 4.76 m long, in cross section prestressed prefabricated slabs were built on a 430 m long test-line in Munich-Karlsfeld, which were coupled in longitudinal direction. Based on the hitherto excellent long-term behaviour in Karlsfeld, a slab track system with 20 cm thick and 6.45 m long prefabricated slabs was developed by the German firm Max Bögl, which has been carried out on a circa 35 km long section of Nürnberg-Ingolstadt route in 2006. A new innovative construction with separated bonding between the longitudinal continuous coupled prefabricated slabs and the long bridge structures has been brought to implementation and application for Beijing-Tianjing route, and these technologies have been put into operation before the Olympic Games in 2008. In this project a highly reinforced concrete base was disjoined from bridge structure by a slip membrane consisting of two geo-textile layers and a foil, so that only slight friction would arise and braking force could be purposefully transferred through an anchor point into the bridge superstructure. This slip membrane in cooperation with anchor points should guarantee that the bridge girder’s extension or shortening is independent of the concrete base. A deformable interface layer of 5 cm styrofoam pattern was fixed above bridge structure joints, between bridge protection layer and the continuous concrete base. Preliminary investigation should have been implemented in order to test the practical probation and long term behaviors of this new system for Beijing-Tianjing route (commissioning before the Olympiad 2008). The Beibei-Jialing-River-Bridge with a length of 450.70 m (maximum span of 168 m) has offered a good occasion for this purpose (segment from 125.75 km to 126.2 km). This bridge is composed of one 346 m long prestressed three-span-bridge and two 32 m long, one 24 m long single-span-bridges, where the highest pier reaches 49 m. It is located in a straight route with a gradient of 4‰. Until this project there were not any experiences in slab track construction on long bridges in China. Therefore this segment was planed originally as ballasted track. With regarding to the positive experiences in Bögl slab track system from Germany and the prefabricated slab track types from Japan, the railway planning agency of “China Railway Eryuan Engineering Group Co.LTD” (CREEGC) looked for possibilities for a new slab track system for this segment. A serious of theoretical calculations have been accomplished with the FEM-software ANSYS for static system of bridge structure including track superstructure. The following two principles were satisfied as a result of these calculations: – The end-tangent-rotation-angle of bridge girder would not exceed 1‰. – Deformations that are caused by creeping and shrinkage will be restricted within a value of f/l ≤ 1/5000 relating to the bridge length. On the basis of this outcome, the design of track system on Beibei-Jialing-River-Bridge has been changed and a new concept of coupled prefabricated slabs was generated. Characteristics of the continuously coupled prefabricated slabs on this bridge are: – Eight longitudinal reinforced bars were embedded in the prefabricated slabs, and the ends of slabs were arranged with a thread for later coupling. The sleeper distance was 62.5 cm and transverse notches of slabs were respectively arranged in the middle of sleeper interspaces. – The transversely subsequent prestressed, 4.93 m long, 2.4 m wide and 0.19 m thick slabs have been coupled with 6 screwed joints and turnbuckles in longitudinal direction (Fig. 9). 1248

Figure 9.

Screwed joints for coupling purpose.

Figure 10. Slab track on the Beibei-Jialing-River Bridge.

Every screwed joint activates a preload force of 94 kN. The coupling joints have been casted with bitumen-cement-mortar. – Under the prefabricated slabs, the thickness of bitumen-cement-mortar reached 40 mm, so that the slabs could be conjoined with the concrete base via the bond layer. By using of stoppers and lateral humps (see Figure 10), the prefabricated slab could be fixed in both longitudinal and transverse directions, thus the transverse and longitudinal forces resulting from train running would be transferred. – In the areas between the vertical screwed fastenings and the expanded plastic slab made of Styrodur 5000, the system of “geotextile-foil-geotextile” has been inserted between concrete base and bridge girder in order to uncouple the superstructure from the bridge girder. The expanded plastic slabs in the range of bridge structural joints on both sides have been blanketed with a foil, so as to avoid infiltration of concrete. Furthermore a modified slab track system “Bögl” was built with continuous coupling from km 132.01 to km 132.26 in the range of WanLiTou-tunnel and a 55 m long section on embankment. 4.4 Turnouts in slab-track-construction For the first time 8 high-speed-turnouts in slab-track-construction have been laid with embedded, monolithic sleepers at Caijia station on embankment, in which 4 turnouts were planned as type 18 (ratio of inclination is 1:18) and 4 as type 12 (ratio of inclination is 1:12). The 850 m long station zone was 4-tracked, two tracks of which were longitudinally continuously welded. Track distance amongst the 4 tracks was 5.0 m respectively. This station is located in curve zone with a radius of 2500 m and a longitudinal gradient of 1.5 ‰. The 2 turnouts of type 12 in continuously welded tracks would be run over with a maximum speed of 200 km/h, and the other 2 turnouts of type 18 with a maximum speed of 250 km/h. The branch speed was planned with 90 km/h. The slab track turnouts were executed as Rheda system. The turnout of type SC325 consisted of Chinese fastening type II, embedded turnout sleeper and a turnout concrete slab on concrete supporting layer and above earthwork. Turnout slabs were divided in 5 segments by 20 mm wide transverse joints respectively. These transverse joints were bituminously cast. In order to control the crack formation due to thermal shrinkage effect, additional 75 mm deep, 8 mm wide transverse joints were arranged on turnout slab at every 6 m distance and then backfilled with PU-material (polyurethane). Turnout slabs were produced from concrete grade C40 according to Chinese standard, on the upper side of which a transverse 1249

Figure 11.

The cross section of slab track for turnout.

Figure 12.

Reinforcement arrangement of turnout slab.

inclination of 1% was designed. The height of this configuration (exclusive of the 30 cm thick concrete supporting layer) amounted to 65 cm. A 30 cm thick concrete supporting layer has been positioned under the turnout slab for load transfer, in which 10 cm thick, 8 mm wide transverse joints were arranged at intervals of 30 m and backfilled with PU-material (polyurethane). These transverse joints in the supporting layer should be concordant with those in the turnout slabs. The lower layer of reinforcement in the turnout slabs was continuously set. Moreover, it should be pointed out that stirrup reinforcement (Φ16) was arranged at every 60 cm distance so as to conjoin the turnout slabs and the concrete supporting layer. Thus the both layers could be coupled with each other. The cross section of this system for turnout and the reinforcement arrangement of turnout slab are shown in Figure 11 and Figure 12. Based on the experiences in slab track turnout from Germany and the technical advancements of ballasted track turnout in the last decades in China, the new application of slab track turnout on this test-line was associated with many positive achievements. With increasing demands of high speed railway, further research and development demands of turnout structure will arise. 4.5 Transition zones Different ground deformations and underground characteristics were existent in the course of construction the test-line. Accordingly, certain structural methods were necessary to simulate transitions which mean areas between bridges, artificial and earth structures, between various slab track systems as well as between slab track and ballasted track. According to “Catalogues of requirements for the design of slab tracks”, the settlement of earth structures should be strictly controlled. In addition, different slab track types would be investigated in terms of stiffness differences along track-way. Special measures were applied for soil improvement purpose for earth structures. For instance, bearing of the concrete slabs was carried out with an inserted elastomer mat and/or additional rails for load distribution purpose were applied, therefore stiffness of superstructure could be uniformed in transition from ballasted track to slab track. Structural measures as well as stiffness adjustment were taken on the rail fastening system in transitions among different slab track types. A 34.8 m long stiffness-gradation-segment was set on rail fastening system for transition to turnout zones, where every step spanned 16 sleeper distances (i.e. 16 × 62.5 cm). The spring coefficient of rail fastening has been modified in the scope from 45 to 55 kN/mm. Using the experiences of slab track in Germany as reference, reinforcement were installed between concrete slabs and concrete supporting layer for combination’s safety in transitions to turnouts.

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5

MEASUREMENTS WITH REGARD TO QUALITY OF SLAB TRACK

At the beginning of 2007 many dynamic measurement were purposeful carried out on the test-line, like operation-tracks, roadbed below tracks, subgrade, bridges, tunnels, turnouts, signal system, electronic facilities etc. During the dynamic measurement the passenger train achieved a speed of 232 km/h, whereas the freight train was accelerated until 141 km/h. On 18th April, 2007 after the sixth round of large scale speed-up on the most Chinese railway lines, the 338 km long new route (T898 Chengdu-Chongqing) has been put into operation, on which this test-line is located. The length of a journey is reduced from 4 hours 39 minutes to 3 hours 49 minutes. The long-term behavior and performance of slab track was implemented. For concrete slab with lattice type two-block-sleeper shown in Figure 15, cracks appeared at the interface between sleeper and reinforced track slab, and they could propagate through the track slab. But after measuring the crack widths it was found that most crack widths do not exceed a level of 0.5 mm which means the rust risk of reinforcing steel bar wouldn’t happen to threaten structure bearing capacity. Long-term observation on behaviors of prefabricated slabs-superstructure Type A shows the potential local invalidation of bitumen-cement-mortar under the prefabricated track slab, which

Figure 13. Turnout structure used for slab track. Figure 14.

Figure 15.

Interfacial cracks of track slab.

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Turnout construction in situ.

Figure 16.

Bitumen eduction of prefabricated slabs-superstructure Type A.

are shown in Figure 16. That is mainly because bitumen eduction happened after temperature changes and the train loads’ iterative work. This damnification may not threaten structure bearing capacity, neither. But it is unfavorable for track system’s long behavior. The phenomenon appears in many areas built with Japanese prefabricated slab system. So it is recommended that the component of bitumen-cement-mortar should be improved for future application. 6

OVERVIEW

The design, calculations and evaluation of this superstructure project were implemented by “China Railway Eryuan Engineering Group Co.LTD” (CREEGC) in collaboration with the Institute for “Railway Track Design of Southwest Jiaotong University (Chengdu, Sichuan)” as well as “China Academy of Railway Sciences”. The construction was actualized by “The Eighth China Railway Group Corporation”, and the total investments accounted for 4.8 billion RMB. With the success of this test-line, the foundation stone was laid for further development of future Chinese PDLs (Passenger Dedicated Lines). The innovative slab track technology tested on the test-line will be applied on four further new-planed lines (Haerbin—Dalian, Wuhan— Guangzhou, Zhenzhou—Xian, Guangzhou—Shenzhen), which are all under construction now. Another example for a significant PDL is the line Peking—Shanghai, which was approved in written form in September 2007 and began to be built on January 2008 formally. With a length of 1318 km and a design speed of 350 km/h the capital investment will be estimated at 220 billion RMB (ca.32 billion US dollars). On schedule this line between the two biggest metropolises should be put into operation in 2010. Including the above-mentioned lines approx. 7000 km PDLs will be planed until 2010, so that a whole integrated railway connection network can be formed step by step among the biggest cities in China. REFERENCES Eisenmann, J & Leykauf, G. 2000. Ballastless Track Systems for Railways, Betonkalender (Concrete almanac). Berlin: Ernst & Sohn. Eisenmann, J & Leykauf, G. 2007. Verkehrsflächen aus Beton (Transport infrastructure from concrete). Betonkalender (Concrete almanac). Berlin: Ernst & Sohn. Hardt, D., Ablinger, P & Vogt, L. 2000. Innovative Feste Fahrbahn auf der NBS Nürnberg-Ingolstadt im Überblick, Eisenbahntechnische Rundschau (9): 584–593. He Huawu & Hou Wenwei. 2006. Development of ballastless track technology on China Railways, Railway Technical Review (Special) SLAB TRACK: 18–22. Ren Juanjuan & Lechner, B. 2008. Feste Fahrbahn-Versuchsstrecke Suining-Chongqing in China, Eisenbahningenieur (7): 39–45. Wu Kejian und Xin Xuezhong. 2007. Innovative Study and Practice on the Engineering Technologies of Ballastless Track on Suining-Chongqing Railway. Chinese Railways (3): 9–15. Züblin Company, 2006. Slab track- turnout. Report of German Züblin system for China.

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Performance improvement of railroads over soft subgrades with geocell reinforcement S. Saride & A.J. Puppala Department of Civil Engineering, The University of Texas at Arlington, Texas, USA

S. Pradhan & T.G. Sitharam Department of Civil Engineering, Indian Institute of Science, Bangalore, India

ABSTRACT: This paper presents the results of a series of model tests performed on a railroad supported by geocell reinforced aggregate/ballast overlying a soft subgrade. Geocells is one of the recently found applications of geosynthetics, which provides all-round confinement to the encased geo-material. Model tests were conducted in a fabricated steel tank using locally available silty clay. This clay was used as a soft subgrade. An aggregate layer was prepared on top of this soft subgrade to represent the ballast. The rail track was simulated using a plain-strain footing of width 250 mm. The undrained shear strength of the underlying clay was varied to verify its influence on the performance and behavior of railroads. An attempt has been made to simulate these model tests using a finite difference program. Both experimental and numerical results demonstrated that the geocell reinforcement has a significant effect on the ballast behavior and performance of the railroad in terms of increase in load carrying capacity and settlement reduction. 1

INTRODUCTION

The aggregate base layer or flexible base is a well known component of any transportation system including railroads, highways and runways. The main function of this flexible base is to support the pavement surface layers and to transfer the traffic loads uniformly on to the subgrade soils. The long term satisfactory performance of these pavement structures depends, in part, on the response of the granular material (aggregate) to the loading. Occasionally, the subgrade materials are highly compressible in nature and as a result unequal settlements occur on the pavement surface. In such a case, the thickness of base layer would go very high, as per the design, to avoid unequal settlements on the surface and to provide uniform load distribution. The alternative solution to reduce the thickness of these layers would be the reinforcement of aggregate layers to improve the performance of these structures. Extensive research has been carried out in small/large scale model tests on geogrid reinforced granular base materials to improve their performance (Miura et al., 1990; Indraratna and Salim, 2003; Giroud and Han, 2004). Research has been carried out in predicting the geogrid reinforced railroad settlements by Shin et al. (2002). Douglas and Valsangkar (1992) carried out large-scale cycled-load testing on pavement structures, consisting of granular bases provided with various geosynthetics placed on peat subgrades to find out the increased stiffness of pavement structures. Raymond (2002); Raymond and Ismail (2003) have studied the effect of geogrid reinforcement on the unbound aggregates through a series of model tests under static as well as repeated loading. They considered three different methods of construction viz. uniform deposit with a single layer of geogrid, uniform deposit with two layers of geogrids and a thin strong layer of aggregate overlying a weak layer of aggregate with a planar geogrid at the interface. Out of the three construction methods, they observed that the method; uniform deposit with two geogrid layers would give better results in terms of ultimate bearing capacity. Considerable work has 1253

been carried out on fresh and recycled ballast by Indraratna and Salim (2003) by introducing a layer of geogrid between sub-base and sub ballast to improve the performance of the railroad. Recently, soil reinforcement in the form of a geocells has been showing its efficacy in the fields of ground modification. Geocell is a three dimensional, polymeric, honeycomb like structure of cells interconnected at joints. The cell walls keep the encapsulated soil from being pushed away from the applied load and confine the soil. Because the filled cells are connected together, the panel acts like a large mat that spreads the applied load over an extended area, instead of directly at the point of contact, leading to an improvement in the overall performance. Several investigations have been reported highlighting the beneficial use of geocell reinforcement in the construction of foundations, embankments and retaining structures (Krishnaswamy et al., 2000, Dash et al., 2003, Sitharam & Sireesh, 2005). Li (2000) considered three different mitigating techniques to strengthen the soft subgrade section of a railroad test track under heavy axle wheel loads which include increased ballast thickness, geocell reinforced subballast and asphalt trackbed stabilization. Li (2000) reported that the most effective technique should reduce stresses on subgrade without replacement or improvement of the subgrade, minimize free water which tend to increase the subgrade soil’s degree of saturation that leads to the subgrade failure. Among the techniques considered, a granular layer with geocell improved the track performance. Raymond (2002) has reported the successful use of geocells to improve the performance of the gantry crane ballasted track. Though there are few field studies available in this subject area, there is a systematic research need to understand the behavior of geocell reinforced aggregates. In this research, an attempt has been made to understand the behavior of railroad (simulated through a plain strain footing) supported on geocell reinforced aggregate/ballast overlying compressible soft clay bed through a series of laboratory model tests as well as numerical simulations.

2

LABORATORY MODEL TESTS

2.1 Materials used A series of model tests was performed on unreinforced and geocell reinforced aggregate overlying soft subgrades. The ballast material used in this study was locally available crushed aggregate consisting of mainly angular-sub angular particles of size ranging between 20 mm and 75 mm. It has a coefficient of uniformity (Cu) of 1.9, coefficient of curvature (Cc) of 0.9 and specific gravity of 2.7. The aggregate is classified as poorly graded gravel with letter symbol GP according to Unified Soil Classification System (USCS). The maximum (emax) and minimum (emin) void ratios were found to be respectively 0.96 and 0.84. The peak friction angle obtained from large box shear tests is observed to be 55°. A natural silty clay soil which has 60% fines fraction smaller than 75 μm sieve size was used to prepare the clay subgrade for this study. The liquid limit, plastic limit and specific gravity of the soil were found to be 40%, 17% and 2.66 respectively. As per the USCS, the soil can be classified as clay with low plasticity (CL). The geocells were formed using a biaxial geogrid made of oriented polymers. The geogrid is having square shape aperture opening, of size 35 × 35 mm. The properties of the geogrid obtained from standard multi-rib tension test as per ASTM: D 6637-01 are presented elsewhere (Sitharam & Sireesh, 2005). 2.2 Test procedure A test tank was designed to simulate a section of railway track (see Figure 1) and tests were conducted under static loading in a simplified and controlled manner. Figure 2 shows the schematic of test bed-loading frame assembly which includes the test tank of 700 mm × 300 mm × 700 mm (length × width × height), reaction frame and a hydraulic jack fixed against the reaction frame. The rail track was simulated with a model footing which was made of steel and measures 300 mm × 250 mm × 8 mm (length × width × thickness). 1254

700 mm

Rail

Sleeper 300 mm

700 mm

Simulated area

Figure 1.

Schematic of the railroad and the area of simulation (plan view).

Figure 2.

Model test set-up.

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Table 1.

Properties of soft clay subgrade. Series I

Series II

Parameter

Quantity

Quantity

Moisture content Degree of saturation Unit weight Vane shear strength

24% 100% 20.47 kN/m3 6.25 kPa

19.7% 100% 20.68 kN/m3 16.5 kPa

The clayey soil was first pulverized and then mixed with predetermined amount of water to get the required consistency of clay. The moist soil was kept in airtight containers for about a week to achieve moisture equilibrium. To prepare the test bed, the moist soil was placed in the test box and compacted in 25 mm thick layers till the desired height was reached. To obtain the desired bulk density, the required amount of moist clay was weighted out for one particular layer, placed in the test box and compacted to a level corresponding to the depth markings. Through a series of trials the amount of soil, water content of soil, height of fall and number of blows of the drop hammer required to achieve the desired density for each lift were determined a priori. By carefully controlling the water content and compaction, a fairly uniform test condition was achieved throughout the test program. In order to verify the uniformity of the test bed undisturbed samples were collected from different locations in the test bed to determine the in situ unit weight, moisture content and vane shear strength of the clay soil. The values of these parameters of the compacted soil at different locations of the test tank were found to be almost the same. Table 1 presents the average properties of the compacted moist clay during the tests. In the case of unreinforced bed, the aggregate was placed in a 0.2 m thick layer across the tank manually over the prepared clay bed. Numerous trial fillings were performed to achieve a uniform placement density. In the case of geocell reinforced beds, first, the geocell mattress was formed on top of the compacted clay bed. The geocell layer was prepared by cutting the biaxial geogrids to required length and height from full rolls and placing them in transverse and diagonal directions with bodkin joints (plastic strips) inserted at the connections. All the geocell layers in the present investigation were prepared in a chevron pattern, as it gives better performance improvement in comparison to the diamond pattern (Dash et al., 2003). After formation of geocell layer the geocell pockets were filled with aggregate using hand packing technique. The densities achieved were monitored by calculating the weight of aggregate per a pre-calculated volume of each cell pocket. It is to be noted that the placement densities for both unreinforced and geocell reinforced beds were maintained same. Upon filling the tank up to the desired height, the fill surface was leveled and the footing was placed on a predetermined alignment such that the loads from the loading jack would be transferred concentrically to the footing. A groove was made into the footing plate at its centre to accommodate a plunger through which vertical loads were applied to the footing. The footing was pushed into the soil at a constant rate of nearly 2 mm per minute. The load transferred to the footing was measured through a pre-calibrated proving ring placed between the plunger and the loading jack. Footing settlements were measured through two dial gauges (Dg1 and Dg2; see Figure 2) placed on either side of the centre line of the footing. The footing settlement data reported here is the average values of the readings taken at the two different points. More details can be found in Pradhan (2006). 2.3 Test variables The geocell layers in all test cases were formed in squared shape. The pocket size (dc) of the geocell is taken as the diameter of an equivalent circular area of the geocell pocket opening and was kept constant at 0.8 B (B = width of footing) in all the tests. Height of geocell layer (h) was also kept constant keeping in mind the typical height of aggregate layers (ballast) adopted in railroads i.e. 200 mm (h/B = 0.8). The width of geocell mattress (b) was 1256

fixed based on the overall width of the tank with width of each pocket being fixed at 200 mm. A gap of 5–10 mm was maintained between the footing and the geocell mattress to avoid the buckling of geocell walls due to direct contact of the footing with geocell mattress. Two series of tests were conducted with and without geocell reinforcement by varying the undrained shear strength of underlying clay subgrade. 3

NUMERICAL SIMULATIONS

Many a times, the difficulties involved in simulating the complexities such as stress levels that are anticipated in the field, material non-homogeneity and non-linear behavior of materials, influence of boundary, scale effects and limitations of 1g model tests are resolved with numerical methods. Many researchers have simulated geogrid reinforced foundation systems using finite element methods (Yetimoglu et al., 1994; Peng et al., 2000; Boushehrian and Hataf, 2003). Limited literature is available on numerical simulation of the geocell reinforced foundation beds. The geocell soil layer has been modeled as an equivalent composite material having higher stiffness and shear strength (Bathurst & Knight, 1998). Bergado et al. (2000) have used finite element program, PLAXIS, to simulate the full-scale test embankment reinforced with hexagonal wire mesh. Madhavi Latha et al. (2001) have modeled the geocell reinforced sand beds supporting the strip footings by representing geocell reinforced bed as an equivalent continuum material using GEOFEM. In this paper, an attempt has been made to simulate the experimentally obtained responses of geocell reinforced aggregate overlying soft subgrades using a finite difference program (FLAC3D). Both aggregate/clay and the footing are discretized with primitive mesh shape ‘brick’ which, a graded mesh around the rectangular shaped footing is to maintain the compatibility between footing and the underlying material. The behavior of footing is assumed as elastic. The elastic-perfectly plastic Mohr-Coulomb model was used for studying the behavior of granular aggregates as well as clay. The geocell is modeled using the inbuilt structural elements called geogrids in this program. The geogrid material constitutive behavior is considered as isotropic elastic. The geocell mattress is simulated by placing the geogrid elements in transverse and lateral directions. These elements are connected at predetermined coordinates to maintain the nodal connectivity for representing the real laboratory geocell mattress that has been used in the model box tests. All material properties used in this numerical simulation are presented in Table 2. The elastic properties such as young’s modulus (E) of the geogrids were obtained from the ASTM standard wide-width tension test. The geogrid structural elements used in this study have a built in interface which allows for gripping/slippage between the soil and geogrid. The parameters required to supplement this behavior are aggregate-grid coupled stiffness (cs_ sk), coupled cohesion (cs_scoh) and coupled friction (cs_sfric). The aggregate-grid coupled Table 2.

Details of material properties used in FLAC3D simulation.

Material

Properties

Footing Clay, Cu = 6.25 kPa Clay, Cu = 16.5 kPa Aggregate

Young’s modulus, E = 2 × 105 MPa, Poisson’s ratio, μ = 0.2 Young’s modulus, E = 0.4 MPa, Poisson’s ratio, μ = 0.3 Young’s modulus, E = 0.55 MPa, Poisson’s ratio, μ = 0.3 Young’s modulus, E = 4.0 MPa, Poisson’s ratio, μ = 0.3 Angle of internal friction, φ = 55° Cohesion, c = 0

Geogrid

Thickness of the geogrid = 1 × 10–3 m Young’s modulus, E = 183 MPa Interface properties: Coupling spring stiffness per unit area, cs_sk = 1.33 × 104 kN/m3 Coupling spring cohesion, cs_coh = 0 kPa Coupling spring friction angle, cs_fric = 33°

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Figure 3.

Model with boundary conditions considered in the present study.

stiffness was computed from the slope of experimental stress-strain curves obtained from pull-out tests. The coupled cohesion component was taken as the two thirds value of cohesion component of the soil (2/3(c)) and the coupled friction component was calculated as two thirds of the value of friction angle of the corresponding soil (2/3(φ)). Boundary conditions similar to that of model test box have been simulated so as to make comparisons between numerical and experimental results. The displacements of the far x-, y- and z-boundaries are restricted in all directions. The model is discretized in to 40320 zones and 44175 grid points to represent the soil mass. The geocell has 12308 structural elements with 6840 nodes. A low downward velocity of magnitude in the range of 10–5 m/step was applied on the top of the footing in the z-direction to simulate loading of the footing. The boundary conditions applied to this domain are illustrated in Figure 3. 4

ANALYSIS OF RESULTS

Typical pressure settlement responses observed from both experimental and numerical simulations are presented in Figures 4 and 5. From both the figures, it can be said that the numerical results are in good agreement with the experimental results. It could be observed that in the case of unreinforced clay beds, where the entire height of test tank was compacted with soft clay, the slope of pressure settlement curves tend to become almost vertical beyond a footing deformation (s/B) of about 5% (see Figure 4). The deformations were reduced by introducing an aggregate layer as a simple form of reinforcement on top of soft subgrade layer. It is well understood that a thin layer of compacted granular fill can inprove the load carrying capacity of an underlying soft subgrade (Meyerhof, 1974). At higher footing deformations, the failure of the bed is attributed to the punching of aggregate material into the soft clay subgrade due to high footing contact pressures. This kind of failure could be minimized by introducing a reinforcing layer such as a geotextile or geosynthetic layer in between the soft clay subgrade and aggregate layer as reported by several authors (see section 1). However, in railroad applications, the form of reinforcement should also provide the confinement to the aggregate against lateral spreading which resulted from the dynamic moving loads (Li, 2000). In this research, a three dimensional geocell mattresses was introduced that could provide lateral confinement to the aggregate and assist in further improvement of the load carrying capacity of the footing/rail track. This increased performance of the footing is attributed to the confinement induced higher angle of internal friction of the aggregate and the interlocking between aggregate and reinforcement which resulted in a stiffer support to the footing/rail track. Hence, in the case of geocell reinforced aggregates overlying the clay beds, the load settlement curves show a linear response with no distinct failure at any footing deformation level (see Figure 5). 1258

Bearin g pressure (kPa) 0

10

20

30

40

0

Footing deformation, s/B (%)

10

20

30

Unreinforced bed cu = 6.25 kPa; Experiment cu = 6.25 kPa; Flac cu = 16.5 kPa; Experiment cu= 16.5 kPa; Flac

40

Figure 4.

Variation of bearing pressure with footing deformation for unreinforced soft clay subgrade.

Bearin g pressure (kPa) 0

200

400

600

0 cu = 6.25 kPa; Experiment cu = 6.25 kPa; Flac cu = 16.5 kPa; Experiment cu = 16.5 kPa; Flac Footing deformation, s/B (%)

10

20

30

Aggregate alone Aggregate + Geocell 40

Figure 5. Variation of bearing pressure with footing deformation for geocell reinforced aggregate overlying soft clay beds.

It is also evident from the pressure-deformation patterns presented in Figures 4 and 5 that the stiffness of the reinforced bed has increased significantly. This observation confirms that the footing deformations are reduced even at high footing contact pressures. From these observations, it can be concluded that the geocell reinforced aggregate layers can provide higher stiffness to the soft foundation soils by providing lateral confinement to the aggregate material and thus distributing the load uniformly over the soft subgrades soils. 1259

To further understand the behavior of geocell reinforced aggregate overlying soft clay beds, two performance factors called a non-dimensional ‘improvement factor’ and a ‘percentage reduction in footing deformation’ are introduced. These parameters are defined as follows. Improvement factor, IFcell =

qagg + cell qagg

@ same footing deformation.

⎛s −s ⎞ Percentage reduction in footing deformation, PRD = ⎜ o r ⎟ ×100 ⎝ so ⎠ where qagg = bearing pressure of footing on aggregate reinforced bed; qagg + cell = bearing pressure of footing on geocell reinforced aggregate overlying clay bed. so = settlement of unreinforced foundation bed corresponding to its ultimate bearing capacity which is found to be around 15% of the footing width. sr = settlement of reinforced foundation bed corresponding to so. Improvement factors were calculated at different footing deformation levels and presented in Figure 6. It is clear that the improvement factor increased with increase in the amount of reinforcement. That is, the reinforcement in the form of an aggregate layer alone improved the bearing pressure of the footing when compared to unreinforced clay bed. In addition, the geocell reinforcement further improved the load bearing capacity of the footing. This is attributed to the high angle of internal friction and interlocking effects as discussed earlier. Interestingly, the improvement factors, IFcell, decreased with increase in undrained strength of subgrade soil. It is to be noted that the decrease in improvement factors represent the decrease in the rate of improvement but not the actual reduction in load bearing capacity of the footing. The performance of the geocell reinforcement in reducing the rail track settlements can be evaluated from the percent reduction in footing deformations (PRD). The PRDs correspond to clay bed with cu = 6.25 kPa and cu = 16.5 kPa are 30.8% and 17.5% respectively. The high percentage reduction in footing deformation in the case of cu = 6.25 kPa is attributed to very low stiffness of the unreinforced bed. Figure 7 demonstrates the vertical stress distribution pattern observed in the geocell reinforced bed (for the case of cu = 16.5 kPa). Figure 7 also shows the corresponding displacement vectors in the geocell members at 30% footing settlement. The maximum vertical stress is concentrated right beneath the footing which is attributed to the existence of high footing contact pressure at this order of higher footing settlement. It is clearly seen that the maximum displacement vectors

2

Improvement factor, If

1.6

cu = 6.25 kPa, PRD = 30.8%

1.2 cu = 16.5 kPa, PRD = 17.5%

0.8

0.4

0 0

Figure 6.

5

10 15 Footing deformation, s/B (%)

20

Variation of improvement factor with footing deformation.

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25

Figure 7. Vertical stress distribution and displacement fields in geocell reinforced aggregate overlying aggregate (cu = 16.5 kPa, h/B = 0.8).

are concentrated below the loading region and their magnitudes are suppressed with depth form the surface. Besides, the displacement vectors are moving away from the region of high footing contact pressure that indicates the movement of the unbound aggregate particles. The movement of aggregate particles was arrested by the interconnected geocell that offer higher resistance against this lateral flow of the particles. These patterns demonstrate the load transferring mechanisms with in the geocell reinforced beds. In addition, the numerical simulations were performed to identify the influence of boundary on the test results and noticed that the effect of boundary on the test results is negligible. The details of which are not discussed here. The secondary advantages of geocell reinforced aggregate layer are many. The confinement effect of geocell increases the lateral resistance to the aggregate against lateral spreading under heavy rail traffic. This minimizes the abrasion between aggregate particles and hence reduces the frequent maintenance operations (i.e. reduction in maintenance cost). Increased maintenance period will result in reduced maintenance costs. Though the initial construction costs are moderately higher, the overall cost of the project over the design period would be low. However, the construction costs involved in geocell reinforced layers were half the cost of construction of conventional alternatives (Bull, 2004). In addition, geocell reinforced aggregate layers reduces the unequal track settlements and hence provide a smooth railroad (Li, 2000; Raymond, 2002). The present test results give an insight of the behavior of geocell reinforced ballast over soft subgrades under static loading conditions. Further investigations are necessary to understand the cyclic behavior of the geocell-aggregate matrix. However, extrapolation of the results from these small-scale model tests to full-scale cases can be done making use of suitable scaling laws.

5

SUMMARY AND CONCLUSIONS

This paper presents the results of geocell reinforced aggregate overlying soft clay subgrades. The undrained shear strength of the soft clay subgrade is varied to understand the influence 1261

of the same on the behavior of the railroad. An attempt is also made to simulate the experimental test data using a finite difference program. The pressure deformation behavior of model footing resting on clay bed and aggregate overlying clay bed shows non-linear trends; while the geocell reinforced aggregate overlying clay beds show a linear response with higher stiffness. The increased performance of the geocell reinforced bed is attributed to the all-round confinement, high angle of internal friction of the aggregate and associated interlocking of the aggregate with the reinforcement. The performance of the railroad on geocell reinforced aggregate bed is estimated through a non-dimensional improvement factor and percentage reduction in footing deformation. Increase in improvement factor is observed with decreased undrained shear strength of underlying soft clay. Secondary functions of geocell reinforced aggregate overlying soft clay subgrades are also highlighted. REFERENCES Bathurst, R.J. and Knight, M.A. (1998). Analysis of geocell reinforced-soil covers over large span conduits. Computers and Geotechnics, 22(3/4), 205–219. Bergado, D.T., Teerawattanasu, C., Youwai, W. and Vottipruex, P. (2000). Finite element modeling of hexagonal wire reinforced embankment on soft clay. Canadian Geotechnical Journal, 37, 1209–1226. Boushehrian, J.H. and Hataf, N. (2003). Experimental and numerical investigation of the bearing capacity of model circular and ring footings on reinforced sands. Geotextiles and Geomembranes, 21, No. 5, 241–256. Bull, J. (2004). Paving the way for geocells, Ground Engineering, 37(6): 21–22. Dash, S.K., Sireesh, S. and Sitharam, T.G. (2003). Model studies on circular footing supported on geocell reinforced sand underlain by soft clay. Geotextiles and Geomembranes, 21, 197–219. Douglas, R.A. and Valsangkar, A.J. (1992). Unpaved Stiffness Geosynthetic-Built Resource Access Roads: Rather than Rut Depth as the Key Design Criterion. Geotextiles and Geomembranes, 11: 45–59. Giroud, J.P. and Jie Han. (2004). Design Method for Geogrid-Reinforced Unpaved Roads. I. Development of Design Method. Jl of Geotech. and Geoenv Engrg, ASCE, 130(8): 775–786. Indraratna, B. and Salim, W. (2003). Deformation and degradation mechanics of recycled ballast stabilized with geosynthetics. Soils and Foundations, 43(4): 35–46. Krishnaswamy, N.R., Rajagopal, K. and Madhavi Latha, G. (2000). Model studies on geocell supported embankments constructed over soft clay foundation. Geotechnical Testing Journal, ASTM, 23, 45–54. Li, D. (2000). Deformations and remedies for soft railroad subgrade subjected to heavy axle loads. Advances in transportation and geoenvironmental systems using geosynthetics, ASCE, Reston, 307–321. Madhavi Latha, G., Sujit Kumar Dash, Rajagopal, K. and Krishnaswamy, N.R. (2001). Finite element analysis of strip footing supported on geocell reinforced sand beds. Indian Geotechnical Journal, 31, No. 4, 454–478. Meyerhof, G.G. (1974). Ultimate bearing capacity of footings on sand layer overlying clay. Canadian Geotechnical Journal, 11(2): 223–229. Miura, N., Sakai, A. and Taesiri, Y. (1990). Polymer grid reinforced pavement on soft clay grounds. Geotextiles and Geomembranes, 9: 99–123. Pradhan, S. (2006). Behavior of aggregate materials and mechanics of reinforced aggregate under static loading. A master’s thesis submitted to the Indian Institute of Science, Bangalore, India. Peng, F., Kotake, N., Tatsuoka, F., Hirakawa, D. and Tanaka, T. (2000). Plane strain compression behaviour of geogrid-reinforced sand and its numerical analysis. Soils and Foundations, 40, No. 3, 55–74. Raymond, G.P. (2002). Reinforced ballast behaviour subjected to repeated load. Geotextiles and Geomembranes, 20: 39–61. Raymond, G.P. and Issa Ismail. (2003). The effect of geogrid reinforcement on unbound aggregates. Geotextiles and Geomembranes, 21: 355–380. Shin, E.C., Kim, H.D. and Das, B.M. (2002). Geogrid reinforced rail road bed settlement due to cyclic load, Geotechnical and Geological Engineering, 20: 261–272. Sitharam, T.G. and Sireesh, S. (2005). Behavior of embedded footings supported on geocell reinforced foundation beds, Geotechnical testing Journal, ASTM, 28: 452–463. Yetimoglu, T., Wu, J.T.H. and Saglamer, A. (1994). Bearing capacity of rectangular footing on geogrid reinforced sand. Journal of Geotechnical Engineering, ASCE, 120 (12), 2083–2099.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Actions on railway track panel and ballast—behavior of the Hellenic limestone ballast K. Giannakos University of Thessaly, Volos, Greece

A. Loizos National Technical University of Athens, Greece

ABSTRACT: In this paper a new method is presented for the estimation of actions on sleepers and the pressures that develop under the seating surface of the sleeper and are transmitted on the ballast. Results from the tests performed on the ballast used in the Greek network are also presented. The tests were conducted in laboratories in France, Austria, and Greece, and resulted in the modification of the Greek technical specifications. Moreover, the need for a new method for the calculation of the actions on the railway superstructure is analyzed in terms of track maintenance and passenger’s comfort. Finally, the influence of the limestone ballast on the track response as derived from the tests and theoretical analysis and the need for new higher demands in the specifications are also discussed. 1

INTRODUCTION

The railway track is a vertical succession of various materials or layers of materials that define the final position of the rail running table as well as the properties of the track itself, as it “reacts” to the “action” that is created from the motion of the railway vehicle. Each material or layer that constitutes the line can be simulated by a combination of a spring with spring constant ki and a damper with damping coefficient ci. During the study for the dimensioning of a railway track and the selection of the individual materials constituting the track, it was found that the “weak links” are the ballast and the substructure underneath the superstructure. These are the elements of the track that develop residual deformations: deflections and lateral displacements directly connected to the deterioration of the geometry of the track, which can be described as quality of the track. When increasing the maximum speed and axle load, it is imperative to reduce primarily the deflection, as much as possible, and also the lateral displacements. In the Greek network, which is partly rehabilitated and partly newly constructed for maximum speed of 200 ÷ 250 km/h and axle load 22,5 t, during the 1970’s and the 1980’s, when the network was constructed for maximum speed of 120 ÷ 140 km/h, cracks appeared on twin-block concrete sleepers and an extended investigation program begun. The ballast usually consists of crushed materials, and, only by exception, of sand-gravel, debris and slag. The ballast must ensure damping of the larger part of the vibrations of the train, adequate load distribution, and prompt drainage of rainwater. As already mentioned above, during the study for the dimensioning of a railway track and the selection of the individual materials constituting the track it was found that the ballast and the substructure underneath the superstructure were the main reasons for the appearance of the cracks. These are the elements of the track that develop residual deformations: subsidences and lateral displacements directly connected to the deterioration of the geometry of the track, which can be more specifically described as quality of the track. The smaller the residual deformations and their increase over time the better the quality of the track. In the frame of this investigation, a new approach for the actions on sleepers and the ballast has been developed, by taking into account the real conditions of the track (maintenance etc.), which led to more strict specifications for railway ballast. In this paper the new method 1263

is described and the results of the tests performed on the ballast used in the Greek network are presented. The tests were conducted in Greece, Austria and France, and led to the modification of the Greek technical specifications for ballast. Moreover, the need for a new method for the calculation of the actions on the railway superstructure is analyzed in terms of track maintenance and passenger’s comfort. Finally, the influence of the limestone ballast on the track response and the need to incorporate ballast quality demands in the specifications are discussed.

2

LABORATORY TESTS ON BALLAST QUALITY

2.1 General In Greece until 1999, when the railway network superstructure between Paleofarsala and Kalambaka (see Figure 1) began to be constructed, only twin-block concrete sleepers were used, which were of French technology, type Vagneux U2, U3 and U31, with RN and Nabla fastenings. On the track between Paleofarsala and Kalambaka, monoblock German technology B70 type of pre-stressed concrete sleepers with Vossloh W-14 fastenings were laid. Up to the end of the investigation program, a part of which was for the ballast, only limestone ballast was laid on track-beds in Greece. The reason for this is that more than 65% of the mainland Greece is composed of limestone rocks. Thus, the supplying of nonlimestone ballast should be imported from abroad or from certain regions of Greece, both solutions of extremely high cost. After the appearance of cracks on approximately 60% of type U3 twin-block sleepers laid on the Greek network, it was necessary to investigate the issue further and determine its causes, given the fact that, up to that time, the available relevant bibliography did not give any satisfactory justification of the phenomenon. For this purpose a research program was initiated for the study of the “sleeper-ballast” system in Greek conditions (rolling stock, ballast quality, rail running table, level of maintenance,

Figure 1.

Map of Greece with the existing railway network (Giannopoulos & Giannakos, 2006).

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etc.). The research program (in which one of the authors, Dr. K. Giannakos, participated as head of the Hellenic railway scientific team and co-ordinator of the research) was conducted by OSE—Hellenic Railways Organization—in relation to specialised issues-sectors with the participation of: (a) the National Technical University of Athens (Ambakoumkin, Loizos et al., 1992–1993), (b) the Polytechnic School of the Aristotle University of Thessaloniki (Tsotsos et al., 1989), (c) the Hellenic Ministry of Environment, Land Planning and Public Works/Central Public Works Laboratory, (d) the Hellenic Institute of Geological and Mineral Research (IGME, 1986) (e) the cooperation of the “Track” Research Department of the French Railways (SNCF/OSE, 1988 & 1989), (f) the University of Graz (Riessberger 1992 & 1989) etc. It included investigation of the phenomena that occurred on the track, laboratory tests and experiments on each individual material, with a view to identify the reasons for the systematic appearance of cracks on the sleepers. The research programs in France, in Aristotle University, and in the University of Graz focused on the quality and mechanical properties of the ballast laid on the Hellenic railway network. 2.2 Laboratory tests in France In the frame of a technical cooperation between the French Railways (SNCF) and the Hellenic Railways Organization (OSE)/Track Directorate, a test program was performed in the Test Center of the “Direction de l’ Equipement” of the SNCF, to study the interaction between the ballast and different sleeper types. The scope of the experimental program was the simulation of the dynamic loads acting on the track in order to determine the influence of the sleeper’s type on the behaviour of the ballast (limestone at that era) used in the Hellenic network (Cervi, 1987). The granulometric curve of the samples was according to the Greek regulations. In railways (a) the track must be completely compliant to the interoperability specifications (TSI’s) as in the State-members of E.U. and (b) the rolling stock must be completely compliant to the rules of the International Union Of Railways (U.I.C.) and to the regulations for Interoperability as in all countries—members of E.U. 2.2.1 Pulse load tests Tests were performed in a cylindrical bucket from lamina (60 cm diameter, 250 cm height) with two different loading mechanisms: (i) using a steel plate with dimensions 31 × 31 cm2, and (ii) using a steel plate with dimensions 34.5 × 34.5 cm2, that is 1.25 × (31 × 31) cm2. The number of cycles of each test was 1.000.000 and the load was applied at a frequency of 4 Hz. The load was calculated so that the pressure under the plate would be correspondent to the Region R1 for the concrete sleepers strength (see also Giannakos & Loizos, 2007), i.e. 120 kN. For the U3 concrete twin-block sleepers there are three regions of “strength”: the R1 region begins on 125 ÷ 130 kN, the region R2 on 140 kN with the R3 region between 140 and 175 kN. The base of the bucket was replaced with a “pad” made of synthetic felt. Only the ballast particles not passing through the 25 mm sieve were chosen and the weight of the ballast, which was placed in the bucket, was measured. The subsidence was measured every 250.000 cycles, with the first measurement performed after 5.000 cycles. At the end of the tests, that is after 106 cycles of loading, measurements were performed on the ballast particles not passing through the 25 mm sieve as well as the ballast particles that passed through the 1,6 mm sieve. The results for the pulse load test are cited in Table 1 as it is presented in Giannakos & Loizos (2008). These tests were performed with the application of a pulse load in the laboratories of SNCF. Measurements of the mechanical properties of the ballast material, which came from different quarries in Greece, were performed. Quality tests were also performed on Vagneux U31 twin-block concrete sleepers (produced according to the technical specifications of the SNCF in Thessaloniki, Greece and sent from Greece to France), and two sleepers, one twinblock Vagneux U41 type and one monoblock, manufactured in France. The tests were performed under a cyclic load between 10 and 59 kN. The ballast abrasion (wear) appears to be directly connected to the pressure acting on the ballast—sleeper interface, without any influence from the nature of the seating surface. The subsidence measured at the seating surface of the sleeper block was smaller than the one measured at the steel support surface. This is 1265

possibly due to a notable difference of the rheological quality of the assembly for the test in relation to the imposed frequency of the load, producing different reactions during the test, since the quantities of the abraded ballast are almost equivalent, when they should not be. It should be noted that the behavior of much polluted and well compacted ballast is practically the same as that of a slab track, with the disadvantage that the polluted ballasted track does not maintain the track geometry. 2.2.2 Cyclic load tests The device used for this type of tests is a unidirectional vibrator, which applies cyclic load on the sleeper between +80 kN and 2.50 kN at a frequency of 50 Hz. The results for the cyclic load tests are cited in Table 2 as it is presented in Giannakos & Loizos (2008). The duration of each test was 50 hours and only the ballast particles not passing through the 25 mm sieve were tested. After staying 100 hours in the device the ballast was removed and the ballast particles not passing through the 25 mm sieve as well as the crushed ballast (during the test) that passed through the 1.6 mm sieve was weighed. Tests were also performed on: (a) 1 twin-block concrete sleeper type Vagneux U31 produced in Greece, (b) 1 twin-block concrete sleeper type Vagneux U41 produced in France, (c) 1 wooden sleeper, (d) 1 monoblock sleeper of prestressed concrete produced in France, (e) 1 twin-block concrete sleeper type Vagneux U2 produced in Greece. It must be noted that the sleepers produced in France presented an abrasion not exceeding 0.9%. The ballast wear seams to be of less importance in the case of the wooden sleeper, even though the amount of fractured ballast particles is almost the same as in the case of a U41 sleeper or a monoblock sleeper. As far as the abrasion is concerned, the U31 sleeper produced in Thessaloniki presented a worse behavior than the sleepers produced in France. Very similar to that is the behavior of the U2 sleeper with octagonal blocks produced in Greece. Table 1.

Pulse load test—Ballast from Domokos quarry (Cooperation OSE/SNCF 1989).

Dimensions of the plate (cm)

Weight of ballast Subsidence cycles × 103 before the 250 mm 500 mm 750 mm test (kg)

31 × 31 steel 112 34.5 × 34.5 steel 112 31 × 31 wood 112

Table 2.

3.95 6.00 3.30

7.80 7.50 4.40

10.00 8.20 4.80

Weight of ballast after the test (kg) 1000 mm

Sieve > 25 Sieve > 1.6 Rest

11.50 9.00 5.40

109.00 110.60 109.40

0.10 0.08 0.10

2.90 1.32 2.50

Cyclic load test—Ballast from Domokos quarry (Cooperation OSE/SNCF 1989).

Weight of ballast in kg

Loss of weight of the sleeper

Before test

After test

Before (kg)

Loss (kg)

Sleeper model

Sieve > 25

Sieve > 25

U31 OSE 68 cm block U41 84 cm block wooden sleeper monoblock sleeper U2 OSE block octagonal

1499.00 1413.00 1571.00 1560.50 1449.00

1423.00 95.0% 1377.00 97.5% 1528.50 97.0% 1500.60 96.2% 1365.00

Sieve < 1.6

Rest

After (kg)

%

19.00 1.3% 10.30 0.7% 3.50 0.2% 13.40 0.8% 19.10

57.00 3.7% 25.70 1.8% 39.50 2.8% 46.50 3.0% 65.00

206.50 202.80 262.00 261.10

3.70 1.8% 0.90 0.34%

240.30 239.50 184.30 180.70

0.80 0.33% 3.60 1.95%

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The U41 sleeper yielded very good results, although the deterioration of the ballast is worse than that of the monoblock sleeper. On the ballast abrasion we can also use Lecocq’s research (Lecocq, 1988), as SNCF proposed, as giving similar results. The ballast of a high Los Angeles (L.A.) coefficient (bad quality) does not improve its behavior when used with a wooden sleeper, in comparison with its use with a concrete twin block sleeper with grater blocks or a monoblock concrete sleeper. But the complete compaction of the support will be delayed with wooden sleepers if we take into consideration the fines that appeared in the test. The results for the cyclic load tests on Greek ballast from the Domokos quarry (DRi = 9) conducted in the SNCF laboratory of St Ouen are shown in Table 3 in the form of total deterioration of the ballast. As it can be seen, the fracture caused to the ballast in the case of the U41 is similar to that of the wooden sleeper. On the contrary, there is less powder on the wooden sleeper, which shows that the ballast will be rendered nonapt for tamping and will demand replacement after a longer period of time. For the above reasons, the fact that the wooden sleeper in the pulse tests produced a markedly lower value of subsidence than U31 and U41 was interpreted as a result of the rheology of the assembly of the test, which responds differently to the frequency that the load imposes, since the quantities of ballast deterioration are “equivalent” (Co-operation OSE/SNCF 1988, 1989). Moreover this can be seen in Table 4, which presents results from the pulsateur test. 2.3 Laboratory tests in Austria On 1991 the Hellenic Railways Organisation set into power an “Agreement on Research on Railway Ballast from Greece” with Professor Riessberger from the Technical University Graz, Austria. Accordingly, the ballast material and track components were sent to Graz where they were tested. The investigation included several tests, which are presented in the following paragraphs. 2.3.1 Test of ballast quality These tests were conducted according to (a) the regulations valid in Austria, i.e. conditions of ballast delivery, ÖBB, BH 700, petrographic evaluation ÖNORM B 3120, pressure strength ÖNORM B 3124, crushing resistance ÖNORM B 3127/A/Pkt 2 and (b) the regulations of the Hellenic Railways Organisation, Los-Angeles-Test NF P18-573, Oct. 1978, Deval-Test NF Pl8-577, April 1979, determination of DRi-vaIue, according to “Specification Technique 695E” of SNCF, 25-10-1984.

Table 3. Results of the ballast from Domokos quarry on the Vibrogir at St Ouen (SNCF). Type of sleeper

Fines < 1.6

Intermediate > 1.6 or < 2.5

Total

Wooden sleeper U31 sleeper U41 sleeper

0.2% 1.0% 0.7%

2.8% 4.0% 1.9%

3.0% 5.0% 2.6%

Table 4. Results of the ballast from Domokos quarry on the Pulsateur at St Ouen (SNCF). Type of sleeper

% Fines < 1.6

% Intermediate > 1.6 or < 2.5

% Total

Wooden sleeper U31 sleeper U41 sleeper

0.08% 0.08% 0.07%

2.23% 2.59% 1.18%

2.31% 2.67% 1.25%

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2.3.2 Repeated load test This test was executed in the “Ballast-bed—Simulator” of the Institute of Rail Transport, Technical University Graz. The set-up permitted to record: development of settlement, elastic properties, pressure on the soil level below ballast, ballast gradation underneath sleeper-center before and after the test procedure. The parameter variation was agreed as follows: ballast depth 25 and 35 cm, 3 types of sleeper: OSE twin-block concrete sleeper U31, OSE Azobe-timber sleeper, ÖBB monobloc concrete sleeper L1. The types of sleepers tested are summarized in Table 5. It was found appropriate to arrange the individual test per parameter combination as follows. 100.000 cycles 20 ÷ 60 kN per sleeper 1,5 · 106 cycles 20 ÷ 120 kN per sleeper 0,5 · 106 cycles 20 ÷ 180 kN per sleeper with a load-frequency of 7 Hz This arrangement of the load-range for the lab tests results from considerations on the real conditions of load application on track, as well as the possibility to simulate this situation to the laboratory tests (Riessberger, 1992). The results of the Deval tests are presented in Table 6. The results of the Los Angeles tests are presented in Table 7. From the Los Angeles and Deval tests the coefficient of durability DRi according to the French specifications that were in effect at that time, are cited in Table 8. 2.3.3 Repeated load-tests in the ballast-bed simulator The development of the permanent settlement was recorded at a number of intermediate stops during the Repeated-Load-Tests. The measurements were taken without vertical load and are therefore comparative with each other. For ballast depth of 25 cm, all sleepers display a loss of cross level by reasonable differential settlements of the sleeper-ends. For ballast depth of 35 cm, again the differential settlement is evident. Although no obvious difference in the Table 5.

Scheme for lab tests in Graz (Riessberger, 1992). Sleeper type

Ballast depth

Twinblock U31

Timber—Azobe

ÖBB—monoblock

25 cm 35 cm

1 (+1) 1

1 2

2 2

Table 6.

Table 7.

Deval—Tests (Riessberger, 1992).

Test no

Weight of material

Fines < 1,6 mm

Coeff. DEVAL

1 2 3 4 Mean value

7.000 g

198 g 188 g 180 g 182 g 187 g

14,14 14,89 15,55 15,38 14,99

Los Angeles—Tests (Riessberger, 1992).

Test no

Weight of material (without steel balls)

Fines < 1,6 mm

Coeff. LOS ANGELES

1 2 3 Mean value

5.000 g

1299,0 g 1213,0 g 1204,5 g 1239,0 g

25,98 24,26 24,09 24,78

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Table 8.

Coefficient of durability DRi (Riessberger, 1992).

Test no

Coeff. DEVAL SEC

Coeff. LOS ANGELES — LA

Coeff. durete — DRi

1 2 3 4 Mean value

14,14 14,89 15,55 15,38 14,99

25,98 24,26 24,09 – 24,78

13 14 15 – 14

bearing-conditions of the two sleeper-ends was visible, a more detailed investigation in the elastic response of the ballast-bed-simulator itself revealed a broken weld between the foundation and the ballast box. This led to a “softer” behaviour of the “soil” in the area of the more settling sleeper-end. It is estimated that in the case of an ordinary track a reduced stiffness of this order may also occur. This also means that the recorded difference in cross-level may not be taken as a strong indicator for sleeper behaviour. However, if softer soil conditions exist the settlement may be increased reasonably. In the case of the OSE twin-block sleeper, the test series were interrupted twice before the end of the test due to the rapid settlement of the sleeper. 2.4 Laboratory tests in Greece Four research programs funded by OSE, concerning ballast and sleepers, were executed in Greece also with coordinator (in these cases too) one of the authors of the present paper (Dr. Giannakos) regarding: (a) the mechanical behaviour of ballast in Aristotle’s University of Thessaloniki (Tsotsos, 1989), (b) concrete twin-block sleeper behaviour in the National Technical University of Athens (Tasios et al., 1989), (c) monoblock sleepers of prestressed concrete behaviour (Ambakoumkin, Loizos et al., 1992, 1993) and (d) ballast sources (IGME, 1986). The results of the research program for the mechanical behaviour of ballast (Tsotsos, 1992) are presented below. Table 9 presents the results of the durability of ballast from different sources (quarries) from all over Table 9.

Ballast types from Greece (Tsotsos, 1989).

No

Ballast source (quarry)

Los Angeles ASTM C131

Los Angeles NFP 18573

Deval

Dri

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

Larisa-Violatomiki Domokos—OSE Lamia—Enomena latomeia Koropoulis (kilom. 108) Orfana Ypato Veroia (Papadopoulos) Kozani (Pagounis) Kozani—Pontokomi (Melidis) Lefkothea (Moulakis) Strymonas (Tairis) Asvestohori (Kypseli) Filadelfeia Thessaloniki (Atlas) Alexandroupolis (Orfanidis) Lavara (Tsiligiannis) Litohoro Pierias (from river) Athens (Mousamas) Velestino (Kotopouleas) Volos (Ntaopoulos–Kazinakis)

35,4 25,3 ‒ ‒ 26,4 ‒ 30,5 26,6 22,2 26,8 29,2 25,6 24,6 27,4 34,7 26,4 26,8 36,4 29,2

41,9 30,8 28,1 38,2 30,8 35,1 38,0 30,3 25,4 38,5 34,0 35,7 27,1 37,6 40,6 37,6 34,0 47,4 38,0

10,8 15,3 20,6 7,14 9,7 11,7 13,7 – 21,2 14,5 11,3 19,4 20,7 19,0 11,2 20,0 13,8 13,0 15,6

‒ 10 12 ‒ 9 6 ‒ ‒ 14 ‒ 7 6 13 ‒ ‒ ‒ 7 ‒ ‒

This table gives information about the source and the strength of ballast, being used for railway track in the Hellenic railway network (on 1980’s).

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1.6 3

Cumulative permanent deformation (mm)

1.4

Stress P1 (MPa)

2.5

2

1.5

1

0.5

0 0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Deformation (mm)

1.2

1.0 0.8 0.6

0.4 0.2 0

5

10

15

20

Number of load cycles

Figure 2. (left) Correlation between maximum stress P1 and deformation in the test of cyclic biaxial loading in a ballast sample, (right) Cumulative change of permanent deformations and the number of load cycles, (Tsotsos, 1989).

Figure 3.

Ballast grains in the ballast bed and transmission of stresses and actions.

Greece. Figure 2 depicts the relation between maximum stress P1 and deformation in the test of cyclic biaxial loading in a ballast sample. After the first cycle of loading the behaviour presented a relative uniformity. The loading curves are almost linear while a non-linearity is observed after the phases of unloading due to hysteresis. After each load-cycle permanent deformations were observed, as well as an increase of the stiffness of the material with the number of cycles. After the 15th cycle a relative spacing out of the curves is observed. Figure 3 depicts the relation of the cumulative permanent deformation to the number of cycles. 3

BALLAST STRESS AND DEFORMATIONS

Regarding the issue of ballast fatigue, the existing bibliography assumes a uniform distribution of stresses under the sleeper and without further details uses the mean value of pressure. Nevertheless, various researchers (UIC, SNCF, OSE) have questioned whether the mean value of pressure is representative. Based on bibliography, the maximum moment measured actually on track results from parabolic stress distribution (ORE D71). But in reality, the seating of the sleepers is supported on discrete points (points of contact with the grains of the ballast as Figure 3 depicts, (see also Eisenmann et al., 1980) and the resulting necessity to calculate the stress per grain of ballast cannot give comparative results to the rest of the bibliography. So it is possible to use the mean value of pressure not as an absolute quantity, but comparatively and in combination with the possibility it covers (Giannakos et al., 1990 a & b). There is no uniform support of the sleeper on the ballast, or uniform compaction of the ballast and the ground and there are faults on the rail running table, imperfections on the wheels etc. Undeflected (stiff) seating (e.g. in the case of a concrete bridge, rock at the bottom of a tunnel as substructure) with great axial load (e.g. 225 kN) leads to faster deterioration of the ballast and therefore, to deterioration of the geometry of the track. In such 1270

cases, the phenomenon can be prevented by placing rubber sub-mats in order to smooth out the great differences in the stiffness of the substructure, during the transition from an embankment into a tunnel or a concrete bridge. In the bibliography, it is suggested (Eisenmann, 1988) that, regarding the substructure, as load should be taken the sum of the mean load +1 standard deviation, and regarding the ballast from 1 ÷ 3 (P = 68.3% ÷ 99.7%) standard deviations depending on the speed and the necessary maintenance work. The most important issue, though, is that since the publication (ORE D117, Rp2, Rp4) of ORE’s research, (Office des Recherches et Etudes of the U.I.C.), it has been established that the material of the sleepers (wood, concrete) gives almost identical values of settlement of the track. Furthermore, because the residual settlement is a percentage of the total subsidence during the passing of the loads (Hay, 1982), it can be extrapolated that we will have an almost identical performance in the deterioration of the geometry of the track. This fact is confirmed by a more recent publication (F.I.P. 1984, see also more recent F.I.B. 2006). This experimental confirmation, which has been also verified through calculations (Giannakos et al., 1990 a, b) means that in relation to the sustaining of the geometry of the track, the material of the sleeper has no significant influence. We will observe the same frequency of maintenance interventions, whether using a wooden sleeper or concrete sleeper, in relation to the sleeper-ballast contact surface. The above experimental data have been verified with analytical results, through the calculation of the reaction of the sleeper and that of the mean value of pressure pˉ and the subsidence y for four types of sleepers (Giannakos, 2004 and also Giannakos & Loizos, 2008). Until the investigation program there were two theories for the calculation of loads included in (a) the German bibliography (Eisenmann, 2004, Fastenrath, 1981) and (b) the French bibliography (Alias, 1984, p. 206–207, Prud’homme et al., 1976). Both of them are giving results for sporadic cracks in sleepers laid on track quite unsuccessfully since an extensive cracking was remarked in a percentage of 60%. One of the co-authors developed a method verifying these results derived from the experience on track (Giannakos, 2004). Indicative results (Giannakos, 2004 and also Giannakos & Loizos, 2008) are included in the following Table 10 (for V = 200 km/h, k1 = 12, ρ = 250 kN/mm, N.S.M. = 1.5 t). The actions on track panel are calculated with the following equation: R2′ = (Qwh + Qα ) ⋅ Adyn + ν ⋅ σ ( ΔRNSM ) + σ ( ΔRSM ) 2

2

(1)

where Qwh = the static wheel load, Qα= the load due to cant deficiency, Ādyn = dynamic coefficient of sleeper’s reaction, ν = coefficient of dynamic load (3 for a probability 99,7% and 5 for 99,9%), σ(ΔRNSM) = the standard deviation of the dynamic load due to non suspended masses, σ(ΔRSM) = the standard deviation of the dynamic load due to suspended masses. R2 region for concrete sleepers must be calculated by using 3 standard deviations, that is ν = 3 and for the stress on the seating surface of sleeper ν = 2 must be used (see Giannakos & Loizos, 2008). If the mean value of pressure is used as a criterion, it can be calculated that even though the surface of a wooden sleeper is about 13% greater than that of the U41, it bears about 3% higher pressure, evidently because of the different elastic pad, in undeflected seating. For soft substructure (ρsubgr. = 40 kN/mm) the U41 gives ytotal = 2.69 mm and pˉ = 0.343 MPa and the wooden one gives ytotal = 2.48 mm and pˉ = 0.307 MPa. Heavier concrete sleepers, in relation to the wooden ones, hinder the settlement of the track that is caused by vibrations (Giannakos et al., 2008). With those sleepers no peaks are observed, which characterize the amplitude of vibration in the resonance area, and whose creation leads to destabilization of the ballast. Moreover, the reduction of the participating Non Suspended Masses in the Table 10.

Results of the performance of 4 types of sleepers (Giannakos 2004).

Type of sleeper + fastening type

Region R2 (kN)

Average value of pressure (MPa)

Subsidence y (mm)

Surface mm2

Wooden sleeper + “K” Sleeper U3 + RN Sleeper U31 + Nabla Sleeper U41 + Nabla

261.9 264.7 228.3 228.3

0.505 0.751 0.598 0.503

1.166 1.044 1.468 1.468

275,000 185,800 197,200 243,600

1271

system’s motion and the use of a “more elastic” pad, i.e. pad with small ρ (ρ < 100 kN/mm and/or 80 kN/mm), leads to a reduction of the stressing of the ballast. The average pressure on the ballastbed as presented in Table 10 is much higher than the permissible stress 0,30 MPa. In some cases it is almost double. So the method foretells the degradation of ballast. 4

CONCLUSIONS

In this paper the method for the estimation of actions on sleepers (Giannakos, 2004, Giannakos et al., 2007) was applied to evaluate the pressures under the seating surface of sleeper that are transmitted on the ballast (Giannakos et al., 2008). Experiments verify that the track subsidence is independent of the sleeper material (wood, concrete). Since the calculated pressure at the “interface” between the sleeper and the ballast, that is the seating surface of the sleeper, agrees well with the average measured values, this method can safely be used as a criterion for the behaviour of the ballast-sleeper system. The method also provides a quantifying reasoning of the real situation observed on track. These results guided Hellenic Railways Organization to modify the technical specifications for ballast and, practically, to exclude limestone ballast from railway use. REFERENCES Abakoumkin K., Trezos K., Loizos A., and Lymberis K, 1992–1993, Normal gauge line monoblock sleepers made of pre-stressed concrete, NTUA/ Athens. Alias J., 1984, La voie ferree, IIeme edition, Eyrolles, Paris. Cervi G., 1987, Rapport de Mission effectuee aupres de CH (OSE), SNCF—Direction de l’ Equipement. Cooperation OSE/SNCF: 3/1989, Programme d’ essais realize au centre d’ essais de la Direction de l’ Equipement. Cooperation OSE/SNCF, 6/1998, Comportement des traverses en relation avec les charges dymaniques. Eisenmann J., 1988, Schotteroberbau—Moglichkeiten und Perspektiven fur dieModerne Bahn. Eisenmann J., 2004, Die Schiene als Tragbalken, Eisenbahningenieur. Eisenmann J., Kaess G., 1980. Das Verhalten des Schotters unter Belastung, ETR (29) 3, Darmstadt. Fastenrath F., 1981, Railroad Track—Theory and Practice, Frederic Ungar Pub. Co., New York, In: part 2, The Rail as support and Roadway, theoretical principles and practical examples, by J. Eisenmann. F.I.B. (Federation Internationale du beton), 2006, Precast concrete railway track systems. F.I.P. (Federation Internationale Precontrainte), 1987, Concrete railway sleepers, London. Giannakos K., 2004, Actions on the Railway Track, Papazissis publ. Giannakos K., Loizos A., 2007, Loads on railway superstructure—Influence of high-resilient fastenings on sleepers loading, Advanced Characterization of Pavement and Soil Eng. Materials, Athens, Greece, 20–22 June. Giannakos K., Loizos A., 2008, Ballast stressing on a railway track and the behavior of limestone ballast, 1st International Conference on Transportation Geotechnics, Notingham U.K., August 25–27. Giannakos K., Vlasopoulou I., 1990a, Investigation-Study of the system “sleeper-ballast”, OSE/Track Directorate. Giannakos K., Vlasopoulou I., 1990b, Investigation-Study of the fatigue of the ballast and the performance of the superstructure in relation to the type of sleepers used, OSE/Track Directorate. Giannopoulos G.A., Giannakos, K., 2006, Restructuring The Greek Railways: Current progress and evaluation of alternative schemes, Transport Reviews. Hay W., 1982, Railroad Engineering, John Wiley & Sons, Chapter 15—Track Analysis. IGME (Institute of Geological and Mineral Research), 1986, Tracking-down of resistant rocks, Athens. Lecocq C., 1988, La Degradation du Ballast”, Memoire, Conservatoire National des Arts et Metiers, Chaire de Contructions Civiles. ORE Question D117, Rp2, Rp4. ORE Question D71. Rp2, Rp4. Prud’ Homme A., Erieau J., 1976, Les nouvelles traverses en beton de la SNCF, RGCF—2/1976. Riessberger K., 1992, Research on Greece Railway Ballast, Univesität Graz, Austria. Riessberger K., 1989, Zweiblockschwellen aus Stahlbeton, Univesität Graz, Austria. Tasios Th. P., Trezos K. 1989, Laboratory tests and measurements on OSE sleepers, National Technical University of Athens (NTUA)/Reinforced Concrete Laboratory, Athens 20-10-1989. Tsotsos S., Mpantis S., March 1989, Research Program 2250—Mechanical Behaviour of Ballast as Construction Material of a Railway Track, Aristotle University of Thessaloniki, Civil Engineering Dpt, Geotechnical Sector—Hellenic Railways Organization, Thessaloniki.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Reducing track faults using polymer geocomposite technology P.K. Woodward & G. Medero Heriot-Watt University, Edinburgh, UK

D.V. Griffiths Colorado School of Mines, Golden, USA

ABSTRACT: In this paper the application of polymer geocomposite technology to the reduction/elimination of long standing railway track faults is presented. The polymers used are urethane cross linked polymers that are applied directly to the ballast matrix using on site mixing equipment. Application of the urethane cross linked polymers allows a high degree of visco-elasticity and hence polymer damping characteristics. The formed structure cures within seconds to form a resilient and very strong polymer/ballast geocomposite. The paper describes how the polymer improves the engineering properties of the in situ ballast and presents typical laboratory studies on engineering behaviour. Finite element simulations of railway track response before and after polymer application are included to show how the polymer geocomposite behaves under actual train loading. A typical application of the technique to a highspeed, high axle load switch and crossing on the UK West Coast Main Line is described. 1

INTRODUCTION

1.1 Track behavior and faults Typically the railway track superstructure is located on ballast, subballast, a formation and subgrade (the formation being described as the subgrade/subballast (or subgrade/ballast) interface). All of these geotechnical materials are liable to deflect and settle under repeated train loading (Frost et al. 2004 and Fryba, 1972). In order to provide a safe, reliable and cost effective network it is necessary to control the reversible deflections (elastic movements) and minimize irreversible deflections (plastic movement). The development of plastic deformation generates the necessary conditions for track misalignments, often referred to as geometry faults. Figure 1 shows a typical track fault, here near Newport in the UK. As heavy freight emerges from the turnout the locomotive starts to accelerate towards the main line speed. This acceleration in the locomotive increases the lateral force on the crossing (here a fixed diamond); the effect of which is to displace the main line rails, causing a geometry fault for the main line to develop. It should be noted that at this location the heavy use of rail anchors have been unable to prevent the fault from occurring. It is therefore desirable to look at alternate techniques that are able to stabilize the track and hence significantly reduce the likelihood of track faults from occurring. This paper examines such a technique using polymer reinforcement technology. 1.2 Desired track fault remedy attributes It can be argued that to provide complete ballast reinforcement and stabilization it is desirable that any technique adopted must satisfy the following attributes: 1. It must be capable of providing complete 3-dimensional reinforcement across the whole track area. 2. The technique must only generate a small amount of track disruption and be capable of returning the track back to operational use as soon as possible. 1273

Figure 1.

Development of a track fault on a diamond due to large lateral forces on the turnout.

3. 4. 5. 6.

It must remain free draining and allow future track maintenance. It must exhibit ductile properties to allow energy absorption. In the event of failure, the technique must be fail safe. The technique should be capable of providing both short-term and long-term solutions to track problems. 7. It must be environmentally safe. 8. It must be cost effective. The treatment of the ballast using visco-elastic polymers fulfills these basic requirements for track reinforcement and stabilization. Traditionally increasing ballast depths or using planar 2-D reinforcement has been used to try and improve track performance, but these often have had very varied results. The application of 3-d polymer reinforcement technique is now described. 2

DIMENSIONAL POLYMER REINFORCEMENT

2.1 The polymers used The polymers used are classified as a ‘urethane cross linked polymers’, comprising two components, a polyol and an isocyanate. These two components can be pumped through a mixing element, such as a ‘static mixer’, comprising spiral elements which promote intermixing; once intermixed the reaction is exothermic which aids the curing process. The polymer therefore exhibits rapid curing properties (it generally cures within seconds) and reaches a high degree of strength within minutes. The non-reacting polymer is environmentally safe and can be designed to allow a wide range of engineering properties, such as stiffness, strength, toughness, damping etc to be selected; depending on the rheology chosen. The polymers are also water tolerant and therefore can be applied in wet conditions. 2.2 Site application Since the polymer is only formed during the mixing stage site application can be relatively straight forward. The two components are kept separate until the control head (shown in Figure 2) at this point they are gradually combined until the mixing ‘wand’ is reached where the static mixers are located (the rod being held in Figure 2) whereby they are forcibly mixed together to form the polymer. The polymer pressure at this point is very low and hence the polymer is simply poured (i.e. it is not sprayed) to a set pattern. The amount of polymer applied to the track can be monitored by simply knowing the polymer flow rate and time of application. 1274

Figure 2.

Typical application of the polymer on site.

Since the flow rate of the pump is known the amount of polymer applied to the track can be carefully controlled. Therefore the level of track reinforcement and stabilization can be determined prior to treatment since the geocomposite properties are known and the amount required can be determined by analysis and/or simulation (Woodward et al. 2007). The pumps can be of positive displacement, or centrifugal type. Positive displacement pumps are often driven by air pressure, whereas centrifugal pumps tend to be electrically driven. Electrical pumps allow for the miniaturization of the installation process and thus provide an efficient means of polymer delivery. 2.3 The formed geocomposite Once the ballast has been compacted the polymer is typically applied to the ballast surface. As the polymer penetrates the ballast void structure it rapidly cures. By controlling the polymer rheology the depth of polymer penetration can be pre-determined and therefore a large variation in ballast penetration depths can be achieved. Experience has shown that a typical range would be in region of 100 mm to 700 mm (as desired). As the polymer flows through the ballast void structure it generates a 3-dimensional reinforcing cage, i.e. the polymer is linked together at every level in the ballast matrix as shown in Figure 3. The ballast is therefore completely stabilized throughout its required depth which greatly increases its strength and resiliency. Typically the polymer takes around 26% of the void structure, which still leaves the track totally free draining. Figure 4 shows a typical compression test on a specimen of the geocomposite in unconfined conditions. The stress and strain axes have been normalized for convenience (the strength of the geocomposite is controlled by the type and level of polymer reinforcement and hence a wide variation is possible). It should be noted that compression strengths approaching that of concrete are possible. The large area generated by the loading curve (i.e. the developing geocomposite hysteresis) clearly shows the ability of the system to absorb energy. This is particularly important in railway applications as the need to absorb rapid variations in dynamic train loading is of paramount importance (for example at switch and crossings). Polymers that exhibit brittle behavior should therefore not be used in railway track loading regimes. The range of possible treatment types is considerable, depending on the level of reinforcement required. For example, if the polymer is applied along the shoulders (at the tie ends) a lateral beam is formed which significantly increases lateral track stability. Treating the 1275

Normalised Stress

Figure 3. Typical cross section of the formed geocomposte showing interconnecting polymer reinforcement.

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0

0.1

0.2

0.3

0.4 0.5 0.6 Normalised Strain

0.7

0.8

0.9

1.0

Figure 4. Typical normalized results from unconfined compression testing of a geocomposite (absolute values depend on the geocomposite tested).

area between the ties dramatically increases vertical track stability. The technique can be set to allow all conventional forms of track maintenance to be performed post installation if required. The application of polymers to railway ballast for the purposes of track reinforcement is generally referred to as the XiTRACK technique. The system is considered to be failsafe since any breakdown of the polymer (for example after long term degradation) would mean that the track would revert back to a normal ballasted state. 3

NUMERICAL MODELLING OF RAILWAY TRACK BEHAVIOUR

3.1 The need to model railway track behavior In order to assess the performance of a variety of different track stabilization and reinforcement techniques it is highly desirable to be able to simulate the behavior of the railway track numerically (Chang & Selig, 1980). It would then be relatively easy to modify track properties in order to assess their impact on the overall dynamic track response before the reinforcement is installed. In this paper a 3-dimensional finite element program that uses 20-noded brick elements to simulate the track substructure (ballast, formation, subgrade etc) and 3-dimensional beam columns elements to simulate the rail (superstructure) is used. Details of the dynamic finite element program and its ability to model real track behavior can be found in Woodward et al. (2005). One of the main features of the program is the ability to model most train loading regimes and speeds, whilst simulating most of the track component structures (additional features can be programmed as appropriate). For example the program 1276

can model transeimic states, such critical track velocity phenomenon (Suiker & de Borst, 1999, Krylov et al. 2000 and Madshus & Kaynia, 2000) whereby the train speed approaches that of the subgrade Rayleigh wave velocity given by Equation 1. VR ≈

0.87 + 1.12ν VS 1+ν

(1)

where, Vs is the shear wave velocity, VR is the Rayleigh wave velocity, and V is Poisson’s ratio. The effect on the response of the track, interms of track displacement, velocity and acceleration profiles for a variety of train speeds, including critical track velocity, can be found in Banimahd & Woodward (2007a). An example of typical simulations is given in Section 4.2. 3.2 Example high-speed railway track simulation 3.2.1 Simulation of high-speed track over weak to stiff formations In this example a typical section of track (Figure 5) is simulated whereby the formation changes from a weak peat (Formation A) to relatively stiff boulder clay (Formation B). The site is part of track on the East Coast Main Line in the UK and the peat has been reinforced with geosynthetic reinforcement. In terms of this paper, what is of general interest is the ability of the program to simulate typical track deflection time histories at line speed on differing soils. Figure 6 shows the vertical time histories of a tie over the two track formations for a 17 tonne axle weight locomotive at a line speed of 105 mph. The two bogies are clearly

Vertical Displacement (mm)

Figure 5. Simulated section of track on the East Coast Main Line, UK (transition occurs at the signal post).

1 0 –1 –2 –3 –4 –5 –6 0.0

Formation A Formation B

0.2

0.4

0.6

0.8

1.0 Time (s)

1.2

1.4

1.6

1.8

2.0

Figure 6. Typical simulated vertical tie displacement time history for a high speed train locomotive travelling over two different subgrades.

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seen in the traces over the different track stiffness. The displacement levels are similar due to the modelling and performance of the track reinforcement located over the poor subgrade. Section 3.2.2 presents another numerical simulation, here for track approaching a fixed timber deck bridge. 3.2.2 Railway bridge transition fault geocomposite simulation At fixed timber deck bridges the track goes from a non-fixed geometry (ballast) to a fixed one, i.e. from a soil foundation substructure to that of a fixed timber or concrete. Due to the fixed nature of the track on the bridge it is very difficult to maintain the vertical track geometry at the transitions (changes in track stiffness, inability of the tamper to lift the track to correct geometry and so on). Figure 7 shows that the track is settling within the transition zone either side of the bridge (the bridge is shown in Figure 8); twist faults can also develop.

Figure 7.

Typical geometry fault at bridge transitions due to changes in track fixity and stiffness.

Figure 8.

Railway bridge with transition issues giving rise to geometry faults.

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Vertical Displacement (mm)

In the numerical program a 2 mm ballast void is assumed to exist within the transition zone prior to treatment with the polymer. Application of the polymer reinforcement to this zone would however significantly reduce the likelihood of the ballast void from forming as the ballast is stabilized throughout its entire depth. In addition the polymer increases the ballast stiffness which increases the overall track stiffness just before the bridge interface and hence helps to reduce induced dynamic forces (Banimahd & Woodward, 2007b). This also helps to control the dynamic forces imposed on the formation and subgrade as the geocomposite is very good at stress redistribution, i.e. it acts as an efficient geo-pavement. Figure 9 shows the simulated response of a tie in the transition zone before and after treatment for a train speed of 112 mph for a locomotive and 3 passenger coaches (the locomotive has a 17 tonne axle load and the coaches have a 12 tonne axle load). Note that in this simulation each axle can be identified in the displacement trace as well as the overall bogies. While the displacement response of the tie is of interest, what is arguably of more interest is the overall response of the simulated transition. This is shown in Figure 10. In Figure 10 the response of the transition is assessed by plotting the vertical response of the first axle of the locomotive with time as it passes over the transition. The large dip in the response for the untreated section (solid line) represents the transition void. This void would give rise to the poor rail profile shown in Figure 7 and the logging of a track fault requiring maintenance. The dashed line in Figures 9 and 10 represent the polymer reinforced bridge transition. Typically the track geometry would first be reinstated to the correct line and level. The polymer would then be applied to reinforce the ballast while the track ballast is in this preferred state and hence ‘capture’ the track geometry. The stiffness of the geocomposite can be increased as the bridge interface is approached and hence a gradual increase in the track stiffness is possible (or reduction of in the case of a bridge run-off transition).

1 0 −1 −2 Before Treatment After Treatment

−3 −4 0

1

2

3

Time (s)

Vertical Displacement (mm)

Figure 9.

Simulated response of a tie in the transition zone before and after polymer treatment.

2 1 0 −1 −2 −3 −4 −5 −6 −7 −8 0 .0

Approach

Transition

Before Treatment After Treatment

Abutment

Track fault

0 .1

Time (s)

0 .2

0 .3

Figure 10. Simulated displacement response of the front locomotive axle travelling over the transition.

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4

CASE STUDY

4.1 Typical sites treated using 3-dimensional geocomposite technology Trials of in situ ballast reinforcement have been taking place in the UK for a number of years and the technique has been shown to produce excellent results. The technique has been used to solve many different track related problems, for example, level crossings (Woodward et al. 2007), railway formations for embankments, curves, switch and crossings, poor formations for high speed track, replacement for concrete in tunnels and so on. In this paper the performance of a particular switch treated in March 2000 by the reinforcement technique is discussed. 4.2 Bletchley Points 215D One of the first trials of the 3-dimensional reinforcement technique was at Bletchley Points 215D on the West Coast Main Line, UK in March 2000 (Figure 11). The Points form part of a turn-out from the main line; the main line itself operates at 125 mph with axle loads up to 25 tonnes. The Points are critical to the operation of the West Coast Main Line in the Bletchley area and were well know to cause problems due to the development of track faults. The problems were similar to that described in Section 1.1 of this paper, namely the development of large lateral forces displacing the Points towards the Mainline side shoulder generating a lateral misalignment on the main line. This misalignment causes the trains to suddenly jolt towards the Mainline side shoulder causing severe discomfort for the passengers. The problem is self perpetuating; as the misalignment develops the lateral forces generated become larger, causing a larger misalignment and so on. If left untreated/unmaintained a potential derailment risk could develop. Prior to reinforcement by the polymer the Points required re-aligning (i.e. regular routine maintenance) every 3 months. The heavy use of tie restraints (i.e. tie end ballast plates) were unable to hold the lateral alignment. In March 2000 the site was treated with the polymer reinforcement technique under red zone conditions, i.e. the line was still operational while treatment took place. Just before treatment the line was re-aligned, this also provided a basis for future performance checking. For this particular site a ‘ladder’ type treatment was selected due to the operational nature of the Points (trains were running at full line speed during treatment). The ballast was excavated in stages down to the base of the tie and the polymer applied around the tie to form the ladder structure (i.e. the polymer was not applied under the tie). The polymer rheology was set so that the polymer penetrated down to 300 mm, which

Figure 11.

Application of the polymer reinforcement at Bletchley Points 215D in March 2000.

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Figure 12. Typical loading of the geocomposite at Bletchley Points 215D (photograph taken May 2003).

is the nominal depth of the ballast layer below tie bottom. Once this had been achieved the upper ballast (referred to as boxing ballast) was replaced. As shown in Figure 11 the upper Mainline side shoulder area was then treated to form a side beam up to the level of the top of the tie. The rheology of the polymer penetrated down into the bottom treated ballast layer to form a continuous 500 mm deep side beam connected to the reinforced ballast in the crib area. This particular treatment works by reinforcing and stabilizing both the vertical and lateral geometry. In the vertical direction the reinforced ballast effectively cages the unreinforced ballast under the ties to the full ballast depth. Provided that the ballast under the tie has good frictional properties then a strong reinforcing action is formed (as the ballast tries to deform and dilate under shear loading it is confined by the reinforced ballast in the crib area). In effect a large reinforced and stiffened geo-pavement is formed under the entire treated area. The Mainline side beam is 500 mm deep and therefore significantly increases the passive resistance of the track in the Main line side shoulder area (for untreated track only the passive resistance of the small tie end area is available). In addition, this beam is tied into the reinforced ballast between the ties which, in effect, acts like an anchor to the shoulder beam. Lateral movement of the loaded tie would therefore require overcoming not only the passive resistance of the side beam, but also the whole geo-pavement, upon which the train is located. The Points are therefore heavily stabilized in both the vertical and lateral direction simply by adding a liquid polymer to stabilize the track. Since the track at Bletchley was still fully operational during treatment the technique caused zero disturbance to oncoming trains. Since treatment no maintenance of the Points has been required, even though the line is one of the busiest in the UK. At the time of writing this paper the treatment has therefore saved in the order of 28 maintenance cycles. Since the longevity of the polymer is high the treatment is expected to last at least as long as the ballast life itself (however since the polymer reduces ballast attrition, the geocomposite longevity is likely to be much longer than this). Figure 12 shows the geocomposite at Bletchley Points under train loading. In December 2007 the geocomposite was checked to assess its condition after 7.5 years of continuous service at full line speeds and axle weights. No deterioration of the polymer was observed. Analysis of the track recording vehicle data (this data is not generally available to the public) reveals that the treated Points have retained their geometry since treatment even though similar Points in the area continue to require regular routine maintenance. This has prompted the network operator in 2008 to request further track reinforcement of other track assets in the area. 5

CONCLUSIONS

In this paper a new technique using high performance polymers was presented for the reinforcement and stabilization of railway track at all train speeds and axle weights. 1281

The paper presented the background to the technique, including the type of polymers used and the method of track application. The use of advanced 3-dimensional finite element techniques was presented in order to demonstrate how the polymer can be used to solve track related issues, such as bridge transition problems. The energy absorbing properties of the formed geocomposite was discussed through a typical geocomposite compression test profile, i.e. the developed hysteresis in Figure 4. The paper concluded by presenting a Case Study of the polymer application at a site near Bletchley Station (Points 215D) in the UK on the West Coast Main Line. Feedback from the network operator confirms that no maintenance of the Points has been required since reinforcement, now representing over 9 years maintenance free operation; previously the Points required maintenance every 3 months. The paper has therefore clearly shown the potential of the technique to reinforce railway track and prevent the formation of track faults. To date the technique (called XiTRACK) has been applied at a significant number of sites across the UK, including bridge transitions, bolted joints, tunnels, high-speed track over poor formations, level crossings, railway track over embankments, curves, complex multiple S&C sites, concrete slab-track transitions, lateral tolerance improvement and so on. The technique has been shown to be cost effective and the polymer is supplied and manufactured by The Dow Chemical Company. REFERENCES Banimahd, M. and Woodward, P.K. 2007a. Numerical study of train speed effect on railway track response, Proceedings, the 9th Railway Engineering Conference, London, 20–21 July 2007. Edinburgh: Edinburgh University. Banimahd, M. and Woodward, P.K. 2007b. 3-dimensional finite element modelling of railway transitions, Proceedings, the 9th Railway Engineering Conference, London, 20–21 July 2007. Edinburgh: Edinburgh University. Chang, S.C. and Selig, E.T. 1980. Geotrack model for railroad track performance, Journal of Geotechnical Engineering, ASCE, 106, 1201–1217. Frost, M.W., Fleming, P.R. and Rogers, C.D.F. 2004. Cyclic triaxial tests on clay subgrade for analytical pavement design, Journal of Transportation Engineering, ASCE, 130, 378–386. Fryba, L. 1972. Vibration of solids and structure under moving loads, Groningen, Noordhoof. Krylov, V.V., Dawson, A.R., Heelis, M.E. and Collop, A.C. 2000. Rail movement and ground waves caused by high-speed trains approaching track-soil critical velocities, Proceedings, Institution of Mechanical engineers, Part F: Journal of Rail and Rapid Transit, 214, 107–116. Madshus, C., and Kaynia, A.M. 2000. High-speed trains on soft ground: dynamic behavior at critical speed, Journal of Sound and Vibration, 231, 689–701. Suiker, A.S.J., and de Borst, R. 1999. Critical response of a granular railway track under high train velocities, Proceedings, 7th International Conference on Numerical Models in Geomechanics-Numog VII, Balkema, Rotterdam, 297–302. Woodward, P.K., Zettor, B., Kaddouri, A. and Banimahd, M. 2005. Advanced Non-linear Dynamic Finite Element Modelling of Railway Track Behavior, Proceedings, 8th International conference on Railway Engineering, London, 29–30 June 2005. Edinburgh: Edinburgh University Woodward, P.K., Thompson, D. and Banimahd, M. 2007. Geocomposite technology: reducing the railway maintenance cycle. Proceedings of the Institution of Civil Engineers, Transport Journal, Vol 160, Issue 3, 109–115.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Ballast evaluation and hot mix asphalt performance H.M. Lees Technical Research & Development, BNSF Railway, Topeka, Kansas, USA

ABSTRACT: BNSF Railway is one of the largest freight rail transportation companies in the United States. A major concern facing the company today is increasing maintenance costs due to heavier loadings and challenging track conditions. This paper focuses on coal dust fouling in the Powder River Basin of Wyoming, and the use of hot-mix asphalt (HMA) in lieu of granular sub-ballast on intermodal line between Chicago, Illinois and Los Angeles, California. It is believed ballast fouling decreases the track’s ability to carry load and is detrimental to its strength and stability. The challenge is recognizing the material causing the fouling condition and identifying areas with significant fouling levels where the structure may be compromised. Ground penetrating radar was used to aid in marking possible trouble areas and gradation analyses were performed to establish a condition rating for each location. As part of BNSF’s long term HMA evaluation, a field program to test the condition of several underlayment sites was undertaken and the overall quality and performance of HMA is discussed. 1

INTRODUCTION

In recent years heavy haul freight railroads have become increasingly interested in railroad track structure support. The track substructure includes ballast, sub-ballast, Hot Mix Asphalt (HMA) underlayment (in lieu of sub-ballast), and the subgrade. The importance of track support was emphasized in 2005 when two major derailments occurred on BNSFUP joint coal line in central Wyoming in the US. Track support was identified as a cause of the derailments, which resulted in extensive and expensive repairs and unacceptable service interruptions. Coal dust fouling from passing unit coal trains was believed to be a significant factor. Figure 1 shows a photo of such a derailment and the system map of BNSF railways as of January 2007. This paper describes recent efforts undertaken to investigate track support conditions in Wyoming, Oklahoma, and Texas. BNSF railway operates unit coal trains in the central United States. Coal train traffic typically involves 135 car unit trains with 113-tonnes (286,000-lb) cars operated at 80 km/hr (50 mph) maximum speed. Traffic on joint coal line in Wyoming has been reported as the highest tonnage in the world. Typical traffic on BNSF Chicago to Los Angeles line is primarily intermodal unit trains with cars weighing up to 125-tons operated at 112 km/hr (70 mph) maximum speed. Performance of HMA underlayment was investigated on this line in Oklahoma and Texas. A brief background of track design and maintenance issues is important. Figure 2 shows a typical cross-section for new track construction. Under the tie, 0.3 m (12 in.) of ballast is placed over a 0.3 m (12-in.) sub-ballast (or alternative 0.15 m of HMA) underlain by the compacted subgrade. Current coal-grain car loads of 113-tonnes are 60% larger than the typical 70-tonne cars operated in the 1970s. Intermodal cars weighing up to 125 tonnes apply even heavier loads on the track. Both loaded and empty unit trains subject the track to repeated cyclic loading. There is an increasing concern that this dynamic loading may cause instability problems in granular material resulting in reduced track strength and may lead to horizontal shear failure. Track design is based on static loading considerations of ballast and the underlying layers but do not consider dynamic train loading. Instead, effects of uniform dynamic loading should be investigated and included in track structure design considerations. 1283

The load transfer through the rail, ties, and ballast to the subgrade is shown in Figure 3. The largest vertical support is directly under the rail. The importance of the ballast layer is clearly evident when maintenance needs and expenditures are considered. Surfacing and ballast maintenance expense at BNSF railways over the past few years has been approximately 200 million US dollars annually, approximately 17% of the capital budget.

Figure 1. Derailment of 2005 on mainline with visible coal accumulation near Wright, Wyoming as indicated on the system map of BNSF Railways with a letter “w.”

C L

305 mm 305 mm

Ballast Sub-ballast Subgrade

Figure 2.

Typical cross-section of new construction.

Figure 3.

Load transfer—typical pressure distribution along a tie (AREA, 1980).

Undercut area: 203 to Ballast tamp area 305 mm below tie

C L

Shoulder clean area: 96 mm below tie, 762 mm wide

305 mm 305 mm

Ballast Sub-ballast Subgrade

Figure 4.

Ballast maintenance influence zones.

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Essentially all of this expense is devoted to new ballast and track maintenance in the upper 0.5 m (20 in.) of the ballast section (see Figure 4). Ballast performance is critical in design and track maintenance. While subgrade support can be an important issue, field sampling of ballast and subgrade in Wyoming showed that coal dust fouling of ballast could be a major problem comparable to ballast fouling due to aggregate breakdown and subgrade intrusion. Subgrade maintenance does not receive any significant portion of annual maintenance funding. 2

IDENTIFICATION AND ANALYSIS OF FOULED BALLAST

To identify fouled ballast locations on Wyoming coal line, several types of Ground Penetrating Radar (GPR) equipment were tested, see Figures 5 and Figure 6. To evaluate the effectiveness of the GPR equipment, locations were selected to collect ground truth samples. At these sites, samples of the ballast, sub-ballast, and subgrade materials were collected at varying depths. A few samples were taken at track centerline, while most samples were collected 1.5 m (5 feet) from centerline where GPR antennas collected data (see Figure 5). Sample locations were carefully selected to include sites with clean ballast that were recently undercut, and sites with severe ballast fouling-pumping to compare extremes. Ballast samples were collected from an exposed ballast face (see Figures 7a and 7b). At some locations core sampling equipment was used to collect the sub-ballast and subgrade samples. The samples were shipped to either BNSF physical test laboratory in Topeka, KS or to the University of Illinois at Urbana-Champaign for gradation sieve analysis. In cases where coal

C L GPR

Figure 5.

Diagram of Ground Penetrating Radar (GPR) antenna configuration.

Figure 6.

Photo showing GPR data collection in Wyoming.

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Figure 7a.

Photos showing ballast sampling at milepost (MP) 105.6 (left) & MP 106.95 (right).

Figure 7b.

Photos showing ballast sampling at MP 112.1 (left) & MP 114.99 (right).

Figure 7c.

Photo showing clean undercut ballast, fouled ballast below and sub-ballast.

was suspected as the fouling material, a laboratory analysis was undertaken to determine the amount of organic material in the fines. Table 1 shows the gain size analysis results for several samples with moisture contents determined. The ballast and soil samples revealed several interesting facts. Since the unique sub-ballast material with a particular red color was present at essentially all sampling locations in Wyoming, it was clear ballast pumping/fouling material did not come from the subgrade (Figure 7c). This fact was confirmed on the Wyoming samples when the organic test revealed very high percentages of coal in the fouled ballast. 1286

Table 1.

Ballast sample summary information.

Division: Track:

Powder river Main 3 Location:

Mile post

Depth (mm)

99 100 101 103 104 104.73 105.6 106.95 **106.95 109 112.1 **112.1 113.2 113.6 114.99 114.99

0–432 0–406 0–406 0–305 0–508 0–457 0–279 0–152 0–483 0–279 0–152 0–330 0–610 0–406 406–432

Ballast sample Orin sub. South 1.2 m (5 ft) from center line

Passing No. 4 sieve (%)

Passing No. Fouling index 200 sieve (Passing No. 4 + (%) Passing No. 200)

1.28 0.364 0.854 1.3 3.33 7.7 9.58 13.4 43.3 1.47 7.53 32.2 17.7 27 1.46 21.1

0.465 1.82 0.38 0.496 0.831 1.29 3.31 3.82 14 0.577 1.9 7.44 4.01 4.59 0.563 2.05

1.75 2.18 1.23 1.8 4.16 8.99 12.89 17.22 57.3 2.05 9.43 39.64 21.71 31.59 2.02 23.15

Water (%)

Condition

1.09 0.54 0.66 0.74 0.99 0.96 2.78 2.49 4.28 0.94 2.55 4.56 4.17 4.62

Clean Clean Clean Clean Clean Light Fouling Med. Fouling Med. Fouling# High Fouling# Clean Fouled# Fouled# Fouled Fouled# Clean—undercut Fouled

4.2

# = pumping. ** = center line crib.

Table 2.

Ballast fouling thresholds (Selig & Waters, 1994).

Fouling thresholds Category

Fouling index (Passing No. 4 + Passing No. 200)

Clean Light Fouled (LF) Medium Fouled (MF) Fouled Highly Fouled (HF)

<1 1 to <10 10 to <20 20 to <40 ≥40

The ballast fouling index (FI) values computed as the percent passing the No. 4 sieve plus the percent passing the No. 200 sieve according to Selig & Waters (1994) are also listed in Table 1. The fouling index is a useful tool to describe the amount of ballast fouling. Table 2 lists guideline threshold levels used for the categorization of fouled ballast sections. The GPR measurements were used to identify fouled ballast locations to collect soil samples. The fouling was then verified by laboratory testing to investigate the effectiveness of GPR in accurately describing the amount of ballast fouling. As an example, the samples collected from the centerline of track at MP 106.95 and MP 112.1 (see Table 1 and Figures 7a & 7b) represent highly fouled-pumping track with very high fouling indices, whereas samples taken 1.5 m (5 ft) from the centerline at these locations show cleaner ballast with much lower FI values. Testing was conducted using both low frequency (500 MHz) GPR horn antenna and high frequency (2 GHz) GPR horn antenna. The lower frequency antenna is used to penetrate the ground deeper, while the high frequency antenna has less ground penetration. The most useful ballast fouling information was obtained using the high frequency (2 GHz) GPR horn antennas. 1287

3

HOT-MIX ASPHALT TRACK BED

The use of Hot Mix Asphalt (HMA) in the trackbed has been proposed for various short segments of track such as railroad crossing, switches and diamonds. In recent years, HMA has been installed in longer lengths during additional new track construction. Typically, a 0.15-m (6-in.) HMA layer is installed to substitute 0.3-m (12-in.) granular sub-ballast material. Various questions and legitimate concerns have been raised by railroad engineering professionals regarding the use of HMA. For example, whether or not HMA would develop surface cracks and high pore water pressures would develop resulting in reduce track strength. In 1995, BNSF started installing a 0.15-m (6-in.) thick layer of HMA rather than granular sub-ballast on several new track construction projects. New track construction projects ranged in length from 8 to 16 km (5 to 10 miles). Approximately 320 km (200 miles) of HMA underlayment has been installed. Most of these HMA installations are on BNSF intermodal mainline in northern Oklahoma and the Texas panhandle. A key decision to install HMA was the favorable contractor bid prices to install 0.15 m (6 in.) of HMA rather than the typical 0.3 m (12 in.) of granular sub-ballast material. One objective of the ballast-HMA investigation was to evaluate the performance of HMA after 10 years of service in heavy freight traffic. A second objective was to compare performances of 0.15-m (6-in.) HMA and the typical 0.3-m (12-in.) granular sub-ballast layers. A third objective was to investigate various concerns raised about use of HMA. To evaluate HMA performance ballast, HMA, and sub-grade samples were collected (see Figure 8). Standard laboratory tests were conducted on the samples including gradation and moisture content. After 10 years of service, the 0.15-m (6-in.) HMA layer performed well. No cracks or surface deviations were observed in the HMA layer. Laboratory gradation tests showed ballast was moderately clean after 10 years of service based on fouling index evaluations. The minimum amount of ballast fouling at HMA sites was not sufficient to consider ballast cleaning. Subgrade soil samples showed no water buildup under the HMA layer. The subgrade moisture content was at a desirable level near optimum moisture content. Repeated testing of subgrade soil moisture during the past years showed moisture content to be equal to or less than the amount of moisture when subgrade was installed. Thus, the HMA layer appears to act as a cover to shed surface water to adjacent drainage ditch. Laboratory tests on HMA core samples showed no significant asphalt deterioration. Track surfacing information to compare surfacing requirements for HMA versus granular constructed track was desired, but was not possible since sites with similar traffic conditions and age were not available. While a brief comparison of recent track surface index calculated by track geometry car suggests HMA surface quality was significantly better than the surface quality on adjacent granular sub-ballast track, a direct comparison was not possible due to ballast installation dates.

Figure 8. Ballast sample & HMA surface measurement (left); HMA core & subgrade samples (right).

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4

SUMMARY AND CONCLUSIONS

Soil and ballast samples collected on Orin coal line in Wyoming to validate Ground Penetrating Radar (GPR) equipment evaluation showed no intrusion of subgrade material into the ballast section. Fouled ballast and localized ballast pumping resulted from fouled material entering the ballast section, primarily coal fouling material, not subgrade intrusion. The unique red colored sub-ballast layer remained intact between the ballast and the subgrade and no signs of subgrade material migrating up through the sub-ballast layer were observed. After 10 years of heavy intermodal traffic, the 0.15-m (6-in.) thick Hot Mix Asphalt (HMA) underlayment has performed well. No surface deviations and cracks in the HMA layer were observed. Ballast analyses at the HMA underlayment sites showed the ballast condition to be relatively clean. This was based on the samples collected and the fouling index evaluations made from the laboratory gradation tests. A direct comparison of the performances of HMA and granular sub-ballast surfacing was not possible. An economic benefit of the HMA layer was demonstrated during the construction bid process when contractors bid to install 0.15 m (6 in.) of HMA at much less expense compared to the installation of 0.3-m (12-in.) thick granular sub-ballast layer. REFERENCES AREA, 1980. Stresses in railroad track—the Talbot Reports. The Reprinted Reports of the Special Committee on Stresses in Railroad Track (1918–1940), American Railway Engineering Association. Selig, E.T. & Waters, J.M. 1994. Track geotechnology and substructure management. Thomas Telford, London.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Effects of incorporating a bituminous subballast layer on the deformation of railway trackbeds T. Ferreira, P.F. Teixeira & R. Cardoso IST – Technical University of Lisbon, Lisbon, Portugal

ABSTRACT: This paper analyzes the performance of bituminous subballast against environmental actions as an alternative to the granular subballast layer usually used in European high-speed tracks. The comparison between both designs is made in terms of the vertical displacements and its seasonal variation as well as the capability of maintaining the moisture content along the year. Two methods were used for the calculation of the relative humidity/suction in the soil depending on the subballast. The first assumes that the soil would have a given percentage of the atmospheric relative humidity and uses the Barcelona Basic Model (BBM) to calculate the deformations associated to it. The second method uses the numerical finite elements program CODE_BRIGHT to perform this calculation. From the different theoretical approaches developed, it is found that the bituminous subballast should allow an important reduction in the seasonal vertical displacements within the trackbed, reducing therefore overall track maintenance needs. 1

INTRODUCTION

The maintenance needs of a railway track are highly influenced by the behaviour of its infrastructure along its life cycle. The use of sand and gravel layers on conventional highspeed lines aims to fulfil an accurate protection of the formation not only against traffic load, but also against weather effects. However, it is found that along the track lifetime those layers tend to loose their filter characteristics. Being almost completely water-resistant, the use of bituminous subballast may offer important comparative advantages concerning the long term deterioration of the subgrade, when compared to the granular solutions. The aim of this paper is to present the results of a work performed (Ferreira, 2007) to assess the impact of using a bituminous subballast layer on the track infrastructure deformation process due to variations of relative humidity along a given period of time. To achieve this goal, two methods were used for the calculation of the relative humidity/suction in the soil. The first one is a simple approach where it is assumed that the soil would have a given percentage of the atmospheric relative humidity and uses the Barcelona Basic Model (BBM) to calculate the deformations associated to it. The second method uses the numerical program for finite elements CODE_BRIGHT (Olivella et al., 1994) to perform this calculation. 2

SUCTION DUE TO WEATHER EFFECTS

Railway infrastructure is composed by different soil layers, which are generally exposed to seasonal moisture changes due to weather actions. Rainfall, changes in the relative humidity and temperature lead to water infiltration/evaporation into the ground, resulting in soil moisture fluctuations. Moreover, the seasonal alternate wetting-drying cycles controlled by atmospheric actions, are responsible for strong changes in suction. These variations in suction due to the evolution of the water content of the soil during the year are associated with volume changes (swelling and shrinking) which are responsible for vertical displacements. 1291

The mechanics of partially saturated soils is considered to be appropriate to perform the calculation of displacements due to environmental changes. Suction can be defined as the free energy state of soil water and can be measured in terms of the relation between the partial vapour pressure and the saturation pressure of the soil water (Fredlund & Rahardjo, 1974), this relation is generally referred as relative humidity. The thermodynamic relationship between total suction and the relative humidity, RH, is given by the Psychometric Law and can be written as follows:

ψ =−

RT ρw ln ( RH ) wv

(1)

where ψ = soil suction or total suction (kPa); R = universal (molar) gas constant [i.e., 8.31432 J/(mol K)]; T = absolute temperature [i.e., T = (273.16 + t0) (K) with temperature t0 in ºC]; −4 ρw = density of water [i.e., 998 kg/m3 at t0 = 20ºC] – ρw = 1007.9exp−4,573×10 T; Wv = molecular mass of water vapour (i.e., 18.016 kg/kmol); RH = relative humidity on the soil voids. Soil and the surrounding air exchange water in the gas (vapour) and/or in the liquid phase but the amounts exchanged depend on the soil’s water retention capability. In fact, the water in the liquid phase present in the soil depends on many factors such as soil grading size and soil density (pore dimensions and geometry). To use Equation 1 in a realistic way, the relative humidity considered must be the one of the air from the soil voids (in equilibrium with the water in the liquid phase of the soil), and not the one of the atmosphere. 3

CALCULATION OF SOIL DEFORMATIONS USING THE BARCELONA BASIC MODEL

Suitable unsaturated soils constitutive models are required for the calculation of soil deformations due to suction changes. The model used in this work is the Barcelona Basic Model, BBM, proposed by Alonso et al. (1990). BBM is a hardening elastoplastic constitutive model appropriated to model the behaviour of slightly or moderately expansive soils and is based in two independent sets of stress variables: the excess of total stress over air pressure, p, and suction, s. It provides the mathematical formulation to calculate the soil deformations due to suction changes and/or stress changes. 3.1 Application of BBM to the case study According to the formulation of BBM, an Elastic domain is enclosed in the (p, s) plane by the LC (after loading collapse) and SI (after suction increase) yield surfaces (Figure 1). Loading paths leading to mean stresses or suction values out of the Elastic domain are responsible for Plastic Deformations, therefore to a new definition of the LC and/or SI yield curves according to the hardening laws. In railway infrastructures, an adequate compaction is necessary to prevent the development of plastic deformations in service. A value for preconsolidation, p0*, greater than the design loads in service (train, rails, sleepers, track support, etc.) must be achieved to ensure that plastic deformations will not occur. Considering that construction of the railway infrastructure is designed in order to avoid the future development of irrecoverable (plastic) deformations, it is assumed that paths in the (p, s) space only associated to suction changes (under constant stress) to be considered in this analysis are in the Elastic domain (Figure 1). 3.2 Cross sections design The design of the cross sections, defined to compare both trackbed solutions, is made in order to simulate a 5 m high embankment and is based on typical geometry, material and thicknesses of trackbed layers. To reach an equivalent structural behaviour of a granular subballast layer with 30 cm of thickness, the subballast layer is design with 12 cm (as proposed by Teixeira et al., 2006). Granular and bituminous cross sections designs are presented in Figure 2. Vertical displacements 1292

Figure 1.

Independent paths in the (p, s) plane due suction changes in the elastic region.

Figure 2.

Cross sections: (a) Granular subballast; (b) Bituminous subballast.

due to suction changes are calculated on control points located over the rail axis line between the subballast and the formation layer as shown by Figure 2 for both compared designs. 3.3 Characteristics of materials The initial state of the infrastructure layers is controlled by the compaction conditions of the materials which compose them. The calibration of BBM requires defining the adequate parameters for soil materials (pc, λ(0), k, r, β and ks) which compose these layers. Displacements registered on control points result from accumulated deformations on subgrade and formation layer and depend on the properties of the soil composing it. Within the framework of comparison between granular and bituminous designs, different types of soils are considered. It is assumed that, for each type of soil, both subgrade and formation layer are composed by the same material (this is not an exact description of reality but in terms of comparison as similar results). The parameters related with the elastic volumetric behaviour of the soil are presented in Table 1. 3.4 Weather actions In this analysis, a Mediterranean climate is simulated (Tarragona, Spain—from Alonso, 1998) characterized by warm and dry summers and moderate winters (Tav = 18ºC). The Relative Humidity has an irregular distribution (RHav = 71.3%) with high Temperatures in summer enhancing evaporation. The annual data is presented in Figure 3. 3.5 Granular vs. Bituminous: parametric analysis Using BBM, it is possible to calculate the volumetric strains within the Elastic domain associated to changes in suction from s0 to s1 in distinct time intervals t0 and t1. The calculation 1293

depends on the elastic soil parameter ks according to Equation (2) where pat is the atmospheric pressure: ⎛ s + pat ⎞ ⎛ s + pat ⎞ ⎛ s + pat ⎞ ε se (t1 ) = ks ln ⎜ 0 − ks ln ⎜ 1 = ks ln ⎜ 0 ⎝ s1 + pat ⎟⎠ ⎝ pat ⎟⎠ ⎝ pat ⎟⎠

(2)

The comparison between the granular and the bituminous solutions is made by comparing the maximum annual amplitude of the vertical displacements, Δ: difference between the maximum shrinking (volume decrease) and the maximum swelling (volume increase) observed in one year. To allow a theoretical approach, a simplified method is adopted. It is assumed that each layer provides a given reduction on the relative humidity (RH) of the air from the atmosphere. This reduction is dependent on the soil properties and depth of the layer. The parameter which represents the subballast reduction on the atmospheric RH is named λ. Considering that the granular subballast layer provides a given reduction on the atmospheric RH, λ Granular =10% (this value was computed with the finite elements program CODE_BRIGHT presented forward), a parametric analysis can be performed to assess the potential reduction on the atmospheric RH provided by the use of a bituminous material on the subballast layer – λBituminous. The process which considers the reduction on the atmospheric RH provided by subballast layers is illustrated in Figure 4. The annual RH series associated to the formation

Table 1.

Model parameters for different types of soils (from Alonso, 1990). Model parameters

Reference soil1 Compacted silty soil2 Lower Cromer till3 Compacted Kaolin4

λ(0)

k

r

β (MPa–1) pc (MPa)

λs

ks

0.200 0.140 0.066 0.065

0.020 0.015 0.008 0.011

0.75 0.26 0.25 0.75

12.5 16.4 20.0 20.0

0.080 0.050 – 0.025

0.008 0.010 0.001 0.005

0.100 0.043 0.012 0.010

1

Reference soil—Clayey soil (classification ML), moderately expansive, with low plasticity and with low compressibility when compacted (wL = 29% and IP = 18%); 2 Compacted silty soil—silty soil (classification ML) moderately expansive and with low compressibility when compacted (wL = 39% and IP = 12%); 3 Lower Cromer till—low plasticity sandy clay (classification SC, with clay fraction 15% in mass) (fines classification: ML; wL = 25% and IP = 15%) with compressibility when compacted lower that the one of soils (1) and (2); 4 Compacted Kaolin—silty soil with clay (classification ML, with clay fraction 22% in mass) moderately expansive (wL = 37% and IP = 28%) with compressibility when compacted lower that the one of soils (1) and (2), and also less expansive than them. 0.78

Rain (mm/10 days), Temp. (ºC).

45

Rain (mm/(10 days)) Temperature (ºC) Relative Humidity

40 35

0.76 0.74

30 25

0.72

20

0.70

15

0.68

10 0.66

5 34

31

28

25

22

19

16

13

7

10

4

0.64 1

0

Time (days/10)

Figure 3.

Climate data considered (Mediterranean—Tarragona, Spain), taken from Alonso, 1998.

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Figure 4.

Reduction on the atmospheric RH provided by subballast layers.

Figure 5.

Results for maximum annual amplitudes of vertical displacements: ΔGranular and ΔBituminous.

layer is calculated by maintaining the same RHAverage and reducing each 10-days value of the RHAtmospheric from a given percentage depending on the subballast RH reduction (granular: 10%; bituminous: λBituminous). The parametric analysis evaluates the influence of the RH reduction performed by the subballast layers assuming that the RH reductions for ballast, formation layer and subgrade are equal on both designs. The reduction on the annual RH series considered for each layer leads to smaller displacements on control points along the year. As mentioned before, the comparison between designs within the parametric analysis is made by measuring the effects of the potential RH reduction of the bituminous subballast—λBituminous—in terms of maximum amplitude of vertical displacements, Δ. Figure 5 exhibit the results of the parametric analysis considering three reference climates and four different types of soil presented in Sections 3.3 and 3.4. The series corresponding to ΔGranular and ΔBituminous are the values for maximum annual amplitudes of vertical displacements calculated for the granular and bituminous subballasts. The ΔGranular series are represented by straight lines once granular subballast is considered to provide a defined value for the RH reduction (λGranular = 10%). Curved lines representing the ΔBituminous series are dependent on the λBituminous parameter. A parameter named Bit.Δred below is defined according to Equation 3 and relates the amplitudes of vertical displacements, Δ, calculated for both subballast solutions. This parameter 1295

analyzes the reduction provided by the bituminous subballast in terms of Δ, taking the granular solution as reference basis. Bit.Δ red =

ΔGran. − ΔBit. ΔGran.

(3)

The results from the parametric analysis have shown that: ‒ Lower amplitudes for vertical displacements, Δ, are associated to soils with low values of suction compressibility, ks; ‒ Generally, maximum amplitude of vertical displacements, Δ, decreases as RH reduction provided by the bituminous subballast, λBituminous, increases; ‒ The adoption of bituminous subballast, designed in order to guarantee a RH reduction superior to 15%, is a better solution than the granular subballast layers; ‒ A 50% reduction in the amplitude of vertical displacements performed by the bituminous solution might be reached if considering a RH reduction higher than 50% for the climate evaluated. 4

SIMULATION OF BITUMINOUS PERFORMANCE WITH CODE_BRIGHT

The use of adequate formulation is necessary to rule the exchanges of water in both vapour and liquid phases between soil and the environment. Once this calculation is mathematically complex, an analysis of the bituminous subballast performance is carried out by recurring to the finite elements program CODE_BRIGHT (Olivella et al., 1994, 1996; DIT-UPC, 2000). The basic principles of the formulation used in the analysis performed with CODE_ BRIGHT consider Water Mass Balance, Air Mass Balance, Energy Balance and Equilibrium (mechanical) equations. The balance of solid mass is also included implicitly when the porosity changes in time are considered—its detailed explanation can be found in Olivella et al. (1994). Balance equations for water and air species are formulated considering the following basic phenomena: ‒ Water and Air flow: Liquid and gas flow in deformable porous media (Darcy’s law generalized for unsaturated conditions); Vapour diffusion (Fick’s law); Liquid – vapour phase changes (Perfect gases law / Psychometric law). ‒ Heat flow: Conductive transport (Fourier’s law); advective transport in liquid and gas phases. Using CODE_BRIGHT, a simulation exercise concerning a period of 5 years is performed to allow the study of the cross sections long term behaviour. 4.1 Weather actions The Mediterranean climate (Tarragona) data is simulated in this exercise (previous Figure 3). It is worth to note that in this analysis, besides Temperature and Relative Humidity (considered in the BBM analysis), this simulation also takes into account the influence of Rainfall. 4.2 Material constitutive models calibration The trackbed materials are described by constitutive models and parameters given in Table 2 and adapted to the type of materials usually adopted in practice (based on Alonso, 1998). The following comments complete Table 2: – Retention curve for ballast exhibits very small air entry pressure values (this property is controlled by parameter P0). Bituminous subballast has the highest value for air entry pressure to simulate its impermeability; – Intrinsic permeability matches the grain size distribution expected for the materials; – Water vapour flow is simulated by means of Fick’s law. A diffusion vapour molecular coefficient, depending on temperature, controls the intensity of vapour mass transfer; 1296

Table 2.

Figure 6.

Material models and parameters.

(a) Boundary flow rate conditions; (b) Partial mesh for granular subballast design.

– A linear elastic stress-strain relationship is adopted. The ballast and the bituminous are very stiff against suction changes. The subgrade and the granular materials can change their volume under suction changes (swells or shrinks); – All trackbed layers dilate or contract when subjected to temperature changes. 4.3 Boundary Conditions and Initial unknowns The initial water content corresponds to an equilibrium situation consistent with the water level located at the lowest boundary of the discretized domain. Boundary conditions and mesh design are presented by Figure 6. Different percentages of rain infiltration, α, are considered for upper boundary and slope. Table 3 resumes the Boundary Conditions and Initial Unknowns assumed to be adequate to perform the 5 years simulation. A sensitivity analysis to these parameters was developed in (Ferreira, 2008). 1297

Table 3.

Boundary conditions and initial unknowns (based on Alonso, 1998).

Parameter

Value

Unit

Layer

Porosity

Void ratio

a (coef. Suction strain) b (coef. Temperature strain)

0.005 1.10 × 10–04

MPa–1 ºC–1

0.50 0.40

1.00 0.67

Initial Stress

10

KPa

0.10

0.11

Suction

0.25

MPa

0.40

0.67

KBituminous (Intrinsic permeability) αUpper boundary (coef. rain infiltration) αSlope (coef. rain infiltration) βg upper boundary (Humidity term)

10–20 15 65 0.0002

m2 % % kg/s/MPa

Ballast Granular subballast Bituminous subballast Formation Layer Subgrade

0.40

0.67

a)

b)

Figure 7. Control points: (a) Granular subballast cross section; (b) Bituminous subballast cross section.

Figure 8. Evollution of vertical displacements—5 years: Granular subballast design (CODE_BRIGHT).

4.4 Simulation results for Granular and Bituminous subballast designs The comparison between the bituminous and granular subballast solutions is made in terms of the evolution of Vertical Displacements and Liquid Saturation on several control points (see Figure 7). 4.4.1 Vertical Displacements The evolution of vertical displacements on control points of both cross sections designs considering a simulation period of 5 years (1800 days) is shown by Figures 8 and 9. 1298

Figure 9. Evolution of Vertical Displacements—5 years: Bituminous subballast design (CODE_BRIGHT).

Figure 10.

Δ and Z at the 2nd year (720 days).

Bit.Δ red =

ΔGran. − ΔBit. ZGran. − ZBit. and/or Bit.Zred = ΔGran. ZGran.

(4)

Considering the evolution of vertical displacements presented for both designs, it is possible to analyze the reduction performed by the bituminous subballast in terms of: – Annual Amplitude of vertical displacements, Δ; – Accumulated vertical displacements, Z; Figure 10 illustrates the definition of Δ and Z. Equation (4)—similar to Eq. (3)—allows the calculation of the Bituminous reduction, Bit.red, in terms of Δ and Z taking the granular results as reference. The results for Bituminous reduction, Bit.red, considering the amplitude of vertical displacements, Δ, on the 2nd year and the accumulated vertical displacements, Z, on the 2nd year and at the end of the simulation—5th year—are presented in Figure 11. Analyzing Figure 11, it is worth to note that the most affected control points concerning the Bituminous reduction are the higher ones from the rail axis line and symmetry axis (A, B, D and E). The reduction in terms of amplitude of the vertical displacements, Bit.Δred, provided by the bituminous subballast is about 30% for these points. Considering the accumulated displacements on the 2nd year, the bituminous subballast allows a reduction (Bit. Zred) of 60% on points A and D, and 25% on points B and E. At the end of the 5 years, the bituminous subballast may perform a reduction on the accumulated displacements (Bit. Zred) between 60% and 80% on points A, B, D and E. Despite of the great displacements registered on points G and H, these points are barely affected by the bituminous subballast (Bit.red from 10% to 30%). Control points from the deeper positions—C, F and I—are associated to small vertical displacements and do not suffer a significant influence from the bituminous layer. 4.5 Liquid saturation The impervious properties of the bituminous subballast are assumed to be the most important advantages of the use of this material for trackbed construction instead of 1299

Figure 11. designs.

Bituminous reduction (Bit. red), Δ and Z registered for granular and bituminous subballast

Figure 12. Evolution of Liquid Saturation—5 years: Granular and Bituminous subballast design (CODE_BRIGHT).

Bituminous cross section

Figure 13.

Granular cross section

Liquid Saturation at the end of 5 years: Granular and Bituminous designs.

granular ones. Figure 12 presents the evolution of liquid saturation on control points of both designs—5 years (1800 days). In terms of liquid saturation, control points from the deeper positions—C, F and I—are not subjected to significant changes depending on the subballast design. A great reduction is verified for points B, E and H as well as for points A, D and G, which maintain a regular and seasonal evolution of Liquid Saturation during the 5 years on the bituminous design in opposite to the granular one. Figure 13 shows liquid saturation at the end of 5 years. Bituminous subballast works as a barrier against water infiltration and maintaining low levels of the moisture content inside the embankment. 1300

5

CONCLUSIONS AND FURTHER RESEARCH

From the different approaches developed, it was shown that bituminous subballast may allow an important reduction in the seasonal track vertical displacements. The amplitude of the displacements is related with their cyclic nature and leads to fatigue problems in the infrastructure, as well as an increase in the number of maintenance operations once these seasonal recoverable displacements may be considered irreversible (plastic) for small periods of time (associated to maintenance intervals). The results presented in the study correspond to an unfavourable situation of poor drainage conditions. Further research will aim at introducing on the model different drainage assumptions in order to get deepen on the evaluation of the impact of using bituminous subballast on track deformation. ACKNOWLEDGEMENTS To the Fundação para a Ciência e a Tecnologia (FCT), for its financial support under the project ref. PTDC/ECM/70571/2006. REFERENCES Alonso, E.E., Gens, A. and Josa, A. (1990). A constitutive model for partially saturated soils, Géotechnique 40, No. 3, pp. 405–430, 1990. Alonso, E.E. (1998). Suction and moisture regimes in roadway bases and subgrades, Simposio Internacional: Drenaje Interno de Firmes y Explanadas, pp. 57–104, 1998. Ferreira, T.M. (2007). “Influence due to the incorporation of a bituminous subballast layer in terms of deformations on railway trackbeds”. Thesis for Integrated Master Degree in Civil Engineering; Instituto Superior Técnico—UTL, Lisbon, November 2007. Fredlund, and Rahardjo. (1974), Fredlund. D.G. Rahardjo, H. “Soil mechanics for unsaturated soils”, Wiley, 1974. Olivella, S. (1994). “Manual user for CODE_BRIGHT—thermal-hydro-mechanical finite elements program”, 1994, 1996; DIT—Universitat Politécnica de Catalunya, 2000. Shahrour, I., Alshihabi, O. and Mieussens, C. (2002). “Experimental study of the influence of suction and drying/wetting cycles on the compressibility of a compacted soil”; Unsaturated soils, Jucá, de Campos & Marinho; Swets & Zeitlinger, Lisse, ISBN 90-5809-371-9, 2002. Teixeira, P.F., López Pita, A. Casas, C. Bachiller, A. and Robusté, F. (2006). Improvements in high-speed ballasted track design: benefits of bituminous subballast layers. Transportation Research Record: Journal of the Transportation Research Board Nº 1943, 2006, pp. 43–49, ISSN 0361-1981, ISBN 0-309-09425-9.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Influence of the stiffness-damping coupling of the foundation in the performance of a high-speed train track J. Cunha & A. Gomes Correia Universidade do Minho, Guimarães, Portugal

ABSTRACT: A brief revision of previous works in the definition of deformability characteristics in soils subject to cyclic dynamic loading is presented. Based on the dependency of stiffness and damping of soils with cyclic shear strain, parametric studies were conducted to investigate the influence of the cyclic shear strain in the performance of the rail track subject to the passage of a Thalys high speed train at 314 km/h. The modeling was done through the Finite Element Method in plane strain. The results obtained in those analyses are shown and discussed. It is shown in this work the importance of the shear strain level imposed in the soil subgrade, in the response of the rail track in terms of displacements and vibrations. 1

INTRODUCTION

The levels of demand associated with railways for high-speed trains imply great accuracy in the definition of numerical models for the prediction of its behavior. Therefore, it is increasingly important to account for the nonlinear behavior of foundation soils of these railways. These soils are subject to cyclic and dynamic loadings, and so, their dynamic response is affected by the induced level of cyclic shear strain. It’s well documented that the majority of soils subject to symmetric cyclic loading present a typical response such as the one shown in Figure 1a. In that Figure is represented the typical response to the first cyclic loading, curve OCA, followed by the unloading AB and finalized by the reloading BEA. This representation is ideal because it is symmetric and the diagram closes at point A, and so any stiffness degradation through the cycle is neglected. The incorporation of this cyclic behavior of soils in numerical models can be done with the characterization of this curve through parameters that define its shape in a generic way. Therefore, it is possible to implement an approach of linear, iterative calculus (Seed & Idriss 1970). Generally, the parameters that characterize this curve are its size and slope. The slope can be given by its tangent, which represents in each instant the tangent modulus of distortion Gtan. Although in a loading cycle Gtan varies, its average can be approximated by the secant to the curve’s peak: τ Gsec = a γa

(1)

τa and γa are shear stress and shear strain. This way, Gsec can be considered the modulus of distortion that corresponds to a level of deformation γa. For levels of strain lower than 10–5 the behavior of the soils is considered to be linear and the shear modulus reaches a maximum value, G0 (Gomes Correia 2004). As the level of strain in the soils varies, so does its behavior curve, with its extreme points following along the curve BOCA (Figure 1a). The size of the curve can be conveniently defined through its area, which is a measurement of the energy dissipation, and is therefore related with the damping coefficient: ξ=

ΔW 4πW

=

ΔW 2π G γ sec a

1303

2

(2)

ΔW is the curve’s area, and W is the energy imposed by the strain γa. G γ W = sec a 2

2

(3)

Gsec/G0

Damping, ξ

Figure 1b represents the variation of stiffness and damping of the soil with the shear strain. This representation is generic for the majority of the soils, but not exact since the values depend of the type of soil. Vucetic & Dobry (1991) gathered data from 16 publications where was studied the influence of various parameters in the variation of Gsec/G0 and ξ with γa. The plasticity index (PI) has great influence on the stiffness of the soil. The bigger the plasticity of the soil is, the bigger will be the elastic phase of its behavior. The data of Figures 2a and 2b are valid for a vast gamma of consolidation ratio, confirming the little influence of the geological history of the ground in these parameters. The results gotten for PI = 0 are coherent with those gotten previously for non-cohesive soils (Seed et al. 1986). With an assumed variation of the Gsec/G0 with ξ, the behavior of the soil can “be corrected” attributing it a stifness and damping in accordance to the imposed strain level, thus resulting

(a)

(b)

γ

a

Gsec/G0

Damping, ξ (%)

Figure 1. Typical behavior of soils: (a) shear stress-shear strain relation for the first loading cycle (Lopez-Caballero et al. 2004); (b) variation of stiffness and damping with shear strain (adapted from Assimaki et al. 2000).

γ (%) a

(a) Figure 2.

γ (%) a

(b)

Relation of cyclic shear strain with: (a) stifness; (b) damping (Vucetic & Dobry, 1991).

1304

in equivalent linear models that take in account non-linearity of the material, through the attribution of equivalent linear parameters. These methods have some limitations because linear equivalent models imply that the strain will return to zero in the end of the loading. Therefore, they are not indicated for cases with permanent deformations under cyclic loading and, on the other hand, rupture can never happen because in linear models the limit of tension in the material does not exist. Neverthless, since the most used methods of analysis of the response of soils are based on the use of linear equivalent parameters, the variation of Gsec and ξ in function of γa have been widely studied for various types of soils. Ishibashi & Zhang (1993) proposed a relation to obtain the curves that relate Gsec/G0 with γa. The relation is: m (γ , I ) − m G p 0 sec = K (γ , I ) × σ ′ p 0 G 0

(4)

with ⎡

⎡ ⎛ 0.000102 + n( PI ) ⎞ ⎤ ⎟⎠ ⎥ γ ⎣ ⎝ ⎦

K (γ , PI ) = 0.5 ⎢1 − tanh ⎢ln ⎜

⎢ ⎣

0.492 ⎤

(5)

⎥ ⎥ ⎦

0.4 ⎡ ⎡ ⎛ 0.000556 ⎞⎤ ⎤ 1.3 ⎢ m(γ , I p ) − m0 = 0.272 1 − tanh ⎢ln ⎜ ⎟⎥ ⎥ exp −0.0145PI γ ⎢ ⎥ ⎝ ⎠ ⎣ ⎦ ⎣ ⎦

(

)

(6)

and n(PI) is given by ⎧0.0 for PI = 0 ⎪ ⎪3.37 E − 6 × I p1.404 for 0 < PI ≤15 ⎪ n( PI ) = ⎨ ⎪7.0 E − 7 × I p1.976 for 15 < PI ≤ 70 ⎪ for PI > 70 ⎪⎩2.7 E − 5 × I p

(7)

They also proposed a relation between Gsec/G0 and ξ which is given by the following equation: ξ = 0.333

(

) ⎢0.586 ⎛⎜ Gsec ⎞⎟2 − 1.547 Gsec + 1⎤⎥

1.3 ⎡ 1 + exp −0.0145I p 2

⎢ ⎢⎣

⎜ G ⎟ ⎝ 0 ⎠

G0

⎥ ⎥⎦

(8)

Other authors have presented similar formulations (Santos 1999).

2

CASE STUDY

The case study is, in part, based in an experience carried in a stretch of rail track in the line of Brussels-Paris, close to the locality of Ath, 55 km the South of Brussels (Degrande & Lombaert 2000). In this stretch it was carried a series of measurements of vibrations in the superstructure and the ground, at distances that vary from 4 m to 72 m of the track during the passing of a Thalys HST at various speed between 160 km/h and 330 km/h. The results of these measurements served as comparison to the ones gotten in the numerical simulations, making possible, thus, the validation of the used numerical tools (Correia et al. 2007). A schematic representation of the track and measurement points considered for this study is presented in Figure 3. 1305

Figure 3.

3

Representation of the high-speed track section and measurement points.

NUMERICAL MODELLING

To study the effect of the variation of stiffness and damping in the soil’s performance under high speed rail tracks, a numerical model in the program DIANA (TNO 2005) was implemented. This model in plane strain incorporates rail, interface, sleeper, ballast, sub-ballast, sub grade and the soil. The study was based on the choice of some materials to which was attributed an initial stiffness and for which some levels of shear strain were assumed. Considering that υ (Poisson’s ratio) is constant, it can be said that: G E sec = sec G E 0 0

(9)

This way, instead of using shear secant modulus, one can use secant Young’s modulus, normalized with the initial Young´s modulus E0. Depending on this initial modulus, to each chosen value of shear strain corresponds a value of Esec(γa) and ξ(γa) as given by the equations 4, 8 and 9. These values were given to the soil in the numerical model, and the dynamic analysis was carried out in order to study its behavior. This procedure was repeated for various values of γa (and corresponding Esec(γa) and ξ(γa)) to study the variation of the soil´s behavior with the variation of γa. In each case attention was focused on the maximum upwards acceleration and maximum downwards displacement at each measurement point. The numerical models created are 63.3 m width and 65 m high; because of the symmetry of the track and loading, only half of the track was modeled. The model comprised 2775 elements, being 12 of them triangular of 6 nodes, 2601 rectangular of 8 nodes and 162 absorbing boundaries. The later ones were used to account for the vibration propagation to outer regions. DIANA software considers Rayleigh damping: [C ] = α [ M ] + β [ K ]

(10)

where [C] is the damping matrix, [M] is the mass matrix and [K] is the stiffness matrix. The parameters α and β are the damping coefficients. In order to establish these parameters it’s necessary to relate them with the hysteretic damping through: ξi =

1⎛ α

⎞ + βω i ⎟ ⎜ 2 ⎝ ωi ⎠

(11)

ωi is the frequency and ξi is the damping that corresponds to that frequency. In order to determine the two parameters one needs to establish two equations which can be accomplished by using equation 11 for the frequencies of the first two modes of the model. The dynamic loading used was the one that corresponds to the passage of a Thalys HST at 314 km/h (Marcelino 2007). 1306

A sand soil was studied for different shear strain levels (Gomes Correia and Cunha 2007) with behavior following the proposal by Vucetic & Dobry (1991). The equations 4, 8 and 9 were adopted and the initial values considered for the soil were E0 = 100 MPa and σ'0 = 30 kPa. Table 1 shows for each case the considered shear strain and the corresponding stiffness and damping. The maximum values of acceleration and displacement in the measurement points can be observed in Figures 4, 5, 6, 7, 8 and 9. The relation between shear strain and displacements is approximately linear when the shear is between 1E-4 and 1E-3. This agrees with the relation between shear strain and stiffness as seen in Figure 2a. For smaller strains the modulus is practically equal to E0 and the displacements are almost the same in this range. For the whole range of strains studied, (from 1E-5 to 1E-3) the displacements raised to approximately 300% of the initial value. The accelerations present an abrupt diminution up until shear strain of 2E-4 and then they maintain practically constant for increasing shear strain. The variation of accelerations was of approximately 150%. Table 1.

Properties used for shear strain variation of sand.

Property

Case 1

Case 2

Case 3

Case 4

Case 5

Case 6

Case 7

Case 8

γ E (MPa) ξ

1 E-05 92,75 0,023

5 E-05 71,79 0,064

1 E-04 56,55 0,104

2 E-04 40,39 0,157

4 E-04 26,38 0,211

6 E-04 19,87 0,238

8 E-04 16,049 0,2554

1 E-03 13,51 0,267

Figure 4.

Displacement variations with shear strain levels at point A4.

Figure 5.

Displacement variations with shear strain levels at point A5.

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Figure 6.

Displacement variations with shear strain levels at point A7.

Table 2.

Properties used for shear strain variation of clay.

Property

Case 1

Case 2

Case 3

Case 4

Case 5

Case 6

Case 7

Case 8

γ E (MPa) ξ

1 E-05 34,85 0,010

5 E-05 34,17 0,012

1 E-04 33,33 0,014

2 E-04 31,71 0,020

4 E-04 28,86 0,030

6 E-04 26,46 0,041

8 E-04 24,43 0,051

1 E-03 22,68 0,060

Figure 7.

Acceleration variations with shear strain levels at point A4.

Figure 8.

Acceleration variation with shear strain levels at point A5.

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Figure 9.

Acceleration variations with shear strain levels at point A7.

A clay was also studied using the same equations and for the same range of shear strain as for the previous case. The initial values adopted for this clay were: PI = 50, σ'0 = 30 kPa and E0 = 35 MPa. The displacements show a different variation from that seen for the sand. Initially there is a diminution of the displacements that is related to the bigger elastic zone (because of the plasticity) and the rising of the damping. As the strain gets higher, the modulus starts to decrease and so the displacements that initially were diminishing, start to stabilize and then rise to values close to the initial one. This makes the variation of displacements throughout this strain range very small (around 25%) indicating that the displacements in the clay are not as affected by shear strain as in the case of the sand. As would be expected, the initial variation of acceleration is not as large as in the sand. This variation is more gradual throughout the range of strain studied. In the case of the point A4, less sensible to the damping variations, there is almost a linear relation between the maximum acceleration measured and the cyclic shear strain adopted. For the other measurement points, a diminution of the slope is seen at strains close to 2E-4. 4

FINAL REMARKS

A study of the influence of cyclic shear strain in the behavior of high-speed train tracks was presented. This study was done for two different soils through parametric analyses by adjusting, for each case, appropriate stiffness and damping. For the sand, an initial increase of the damping occurs for lower strains than for the case of the soils with higher plasticity. This induces a considerable initial variation of accelerations which is followed by a phase of stabilization. For the clay, the initial variation is not so abrupt since the damping also changes in a more moderate way. Following this initial variation comes another one even less abrupt but it never reaches stabilization like in the case of the sand. As for the displacements, they naturally tend to increase along with shear strain. However, this can be preceded by a small phase where there is a diminution, mainly at strains a little higher than 1E-5 where the stiffness is virtually E0. An interesting point to retain from these analyses is that both the vibrations and displacements show an alteration in their tendency at strains close to 2E-4. So for this configuration of rail track, it would be benefit to guarantee that shear strain in the soil is close to this value as that induces low displacements and accelerations. It is shown that the knowledge of the shear strain induced in the soil foundation of the rail tracks for high-speed trains is important. It induces a variation in the soil´s stiffness and damping that is reflected in the accelerations and displacements. The knowledge of these variations might be important to accomplish a configuration that combines lower accelerations with lower displacements on the track and soil. 1309

ACKNOWLEDGEMENT The authors acknowledge the financial support for this research from the Foundation for Science and Technology (FCT) (project POCI/ECM/61114/2004—Interaction soil-railway track for high speed trains). REFERENCES Assimaki, D., Kausel, E. & Whittle, A.J. 2000. Model for dynamic shear modulus and damping for granular soils. Journal of Geotechnical and Geoenvironmental Engineering, 126(10): 859–69. Degrande, G. & Lombaert, G. (2000). High-speed train induced free field vibrations: In Situ measurements and numerical modelling. Proceedings of the International Workshop Wave 2000, Wave Propagation, Moving Load, Vibration Reduction, edited by N. Chouw and G. Schmid, Rühr University, Bochum, Germany, pp. 29–41. Gomes Correia, A. 2004. Deformability characteristics of soils interesting the serviceability of structures (in portuguese). Revista de Geotecnia, SPG nº 100, pp. 103–122. Gomes Correia, A. & Cunha, J. 2007. The influence of cyclic strain of soils in performance of high speed rail track (in portuguese). Revista de Engenharia Civil da Universidade do Minho, nº 28 73–86. Gomes Correia, A., Cunha, J., Marcelino, J., Caldeira, L., Varandas, J., Dimitrovová, Z., Antão, A. & Gonçalves da Silva, M. 2007. Dynamic analysis of rail track for high speed trains. 2D approach. Proceedings of the 5th International Workshop on Applications of Computational Mechanics in Geotechnical Engineering, Guimarães. Ishibashi, I. & Zhang, X. 1993. Unifieded dynamic shear moduli and damping ratios of sand and clay. Soils and Foundations, 33(1): 182–191. Lopez-Caballero, F., Modaressi, A. & D’Aguiar, S. 2004. “Amélioration du modèle de comportement non linéaire existant dans le logiciel CyberQuake®”. École Centrale Paris, Laboratoire de Mécanique des Sols, Structures et Matériaux. Marcelino, J. 2007. Bi-Dimensional model for vibration studies induced by high speed trains (in Portuguese). Relatório LNEC, Lisboa, Portugal. Santos, J.A. 1999. Characterization of soils by dynamic and torsional cyclic tests. Application to the study of pile behaviour under static and dynamic horizontal actions (in Portuguese). PhD Thesis, IST, Lisbon, Portugal. Seed, H.B. & Idriss, I.M. 1970. Soil moduli and damping factors for dynamic response analyses. Report EERC-70-10, Earthquake Engineering Research Center, University of California, Berkeley, CA. Seed, H.B., Wong, R.T., Idriss, I.M. & Tokimatsu, K. 1986. Moduli and damping factors for dynamic analyses of cohesionless soils. Journal of Geotechnical Engineering—ASCE, 112(11): 1016–1032. TNO DIANA. 2005. DIsplacement method ANAlyser, cd-rom, version 9, Building and Construction Research, Holland. Vucetic, M. & Dobry, R. 1991. Effect of soil plasticity on cyclic response. Journal of Geotechnical Engineering—ASCE, 117(1): 89–107.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Measurement of vibrations induced by high-speed trains J. Martins, A. Gomes Correia & L.F. Ramos University of Minho, Guimarães, Portugal

J. Marcelino & L. Caldeira National Laboratory of Civil Engineering—LNEC, Lisbon, Portugal

J. Delgado National Railway Network—REFER, Lisbon, Portugal

ABSTRACT: The paper describes the preliminary test campaign carried out in the national research project POCI/ECM/61114/2004, entitled “Interaction soil-railway track for highspeed trains”, in Portugal. In this context, a preliminary measurement test campaign with vibration sensors was performed in the Portuguese North Railway Line. The next project task will be the instrumentation of several sections with different geometric and geotechnical characteristics. Therefore, the paper present aspects related to testing equipment, the testing and results discussion, including the signal processing. The measurement results will be also used to calibrate numerical models. 1

INTRODUCTION

One of the essential characteristics of the soil-rail structure behavior is related to its deformation under loading. The optimum soil-track structure should be able to support the rail deformations (reversible and permanent settlements) compatible with its performance in service (admissible deformation). This depends, most of all, on the rail support, on the load per axle and on the train speed (Brandl, 2004). In the case of high-speed railways, the dynamic loads generated by trains play an important role in the behavior of the soil-track structure. Excessive vibrations can lead to large costs in the maintenance, to a high level of discomfort for passengers and to induce vibrations in the surrounding structures (Anderson et al. 2000 and Zhai et al. 2004). Therefore, the level of vibrations caused by the passage of high-speed trains can be an indicator for quality and performance of the railway. To study this phenomenon, numerical models to predict the vibrations generated by highspeed trains are continually being studied. Thus, in situ measurements assume a crucial role to assess the quality of the track and/or to validate those numerical models. The interest to study the vibrations induced by high-speed trains has been increasing in Portugal due to the construction of new high-speed railways. In the framework of a national research project POCI/ECM/61114/2004, entitled “Interaction soil-railway track for highspeed trains”, funded by the Foundation for Science and Technology, it was established a protocol between the Portuguese National Railways Network (REFER) and the Tecminho (an University Enterprise Association for the development as a representative of the consortium UM/LNEC/IST/FCT-UNL), with the aim to develop the knowledge within the methodology of construction and to control the railways embankments and the platform layers. In this scope, a preliminary test campaign with improved techniques for measuring vibrations was carried out in the Northern Line of Portugal. In one the test campaign, vibrations were measured on the soil surface, on the layer of the road bed, on the sub ballast and on the ballast. At this stage, only the field functionality was tested. The main purpose of the campaign was to check out all the problems that can arise in 1311

future, like the procedures for fixing the equipment, power supply, data acquisition problems, and to identify important aspects for data processing. The present paper presents the characteristics of the Pendolino train (“Alfa Pendular”), as well the track and the soil properties. Furthermore, it is presented the experimental setup and the in situ measurements. Finally, the signal processing is presented with the results discussion. 2

CHARACTERIZATION OF THE “ALFA PENDULAR” TRAIN

Figure 1 shows the Pendolino train (“Alfa Pendular”). It is a passenger train which has a top speed of 220 km/h and consists of six coaches with twelve bogies and, consequently, with twenty four train axles. The axle positions X and the loads F are summarized in Table 1. 3

GEOMETRIC AND GEOTECHNICAL CHARACTERIZATION OF THE RAILWAY

The chosen place for the preliminary testing was at the PK 36.850 km (see Fig. 2), near to the Carregado railway station, which integrates the subsection 1.2 of the Portuguese North Line. The reasons for testing this section were the foundation conditions, the line geometry, and the proximity of the electrical central power of Carregado, which it is a significant source of electromagnetic and environmental noise. Thus, the preliminary tests were held in the possible worst conditions in terms of noise. The place is characterized by the existence of a simple track, known as old line, and a double track, which, according to the draft implementation, consists of rails type UIC60 in Iberian gauge (1.668 m) on concrete sleepers monoblock pre-stressed (DW model, 2.60 m length and 204 kgf weight) at 0.60 m spacing over granite ballast layer of nominal size of 25/50 mm. This layer rests on a sub-ballast layer, which is based on a platform of class P3, according to the UIC 719R 2004. Regarding the geological framework, the subsection 1.2 develops throughout the West Basin board Aluvionar Tagus, which is mainly characterized by pliocenic, miocenic, forma-

Figure 1.

Table 1.

Pendolino train (“Alfa Pendular”) layout.

Axle positions and loads for Pendolino train (“Alfa Pendular”).

X (m)

F (kN)

X (m)

F (kN)

X (m)

F (kN)

X (m)

F (kN)

3.9 6.6 22.9 25.6 28.9 31.6

139.2 137.2 124.5 123.5 129.4 130.3

47.9 50.6 53.9 56.6 72.9 75.6

127.4 126.4 140.1 139.2 130.3 131.3

78.9 81.6 97.9 100.6 103.9 106.6

129.4 127.4 125.4 136.2 128.4 132.3

122.9 125.6 128.9 131.6 147.9 150.6

134.3 134.3 125.4 126.4 140.1 140.1

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Central of Carregado

36 + 800

36 + 900

Instrumented Section

c . 2 6i . VAE c . 2 6i . VDE

Figure 2.

Location of the instrumented section.

tions and alluvial deposits and terrace. The site is located in an alluvial area which is characterized by a surface layer of silty-clay nature desiccated, overlapped at predominantly muddy levels from soft to very soft which can reach thicknesses of meters (Fortunato, 2005). 4

EXPERIMENTAL SETUP

Acceleration measurements have been carried out at several locations with sensors distributed perpendicularly to the railway tracks (see Fig. 3a). The measurements for several train types were performed with eight uniaxial accelerometers. The accelerometers were placed in the upright position, in the ballast and sub ballast layer, in the embankment and in the foundation. The profile of the instrumented section is shown in Figure 3b. The measuring points allow to know the vibration response of the near and the far field locations. Table 2 summarizes the adopted distances for each of the accelerometers and their technical characteristics (sensitivity and dynamic range). Note that in the case of preliminary tests, different types of accelerometers were used in the same positions to check the quality of the signals. To measure and to record the signals, a data acquisition system from National Instruments (NI) was used. The system was composed by an eight channel signal condition card, one digitalization card with 16-bit resolution and a laptop connected by USB connection. The experience gained with the first vibration measurements allowed to state that is better to use batteries to supply the measuring equipment than to use a diesel generator, which introduces more noise in the measurements. The measurements were performed with a sampling interval Δt equal to 0.5 ms, i.e. with a sampling frequency Fs equal to 2000 Hz. To measure the soil vibrations at the surface it should be guaranteed that the sensor are efficiently attached to the soil, so that is ensured the sensors verticality and stability during measurements. According with literature, this can be done by using a steel cube sealed on the ground surface (SUPERTRACK, 2005), by using aluminium stakes (Degrande, 2000), or by mounting the accelerometer on a wooden pedestal in the ground (Bahrekazemi, 2004). For the case, the accelerometers placed on the ballast and sub ballast were mounted on an iron stake with 12 mm of diameter, while the others sensors were mounted on wooden stakes, as can be seen in Fig. 4. in this way, it was considered that the system stake-sensor allows the effective adhesion to the soil. The experience with the installation of stakes allowed to conclude that the wooden stakes offer some difficulty in nailing on rigid soil surfaces and can cause some disturbance of the 1313

OLD TRACK

lla

m

ba

b Su

Ac1

ASCENDING EAST LINE

t

en

st

st

lla

Ba

Ac2

nk

km

Em

Em

Ac3

t

en

t m en ank b n Em ba

ba

Ac5

n

io

at

nd

u Fo Ac6

n

Ac7

n

io

io

at

nd

u Fo

at

nd

u Fo Ac8

Ac4 DESCENDING EAST LINE

0.26

5.00 6.40 1.90 10.51

0.26

15.51

1.90

20.51

5.00

25.51

6.40 10.51 15.51 20.51 25.51

a)

b)

Figure 3.

Table 2.

Instrumentation plan: a) plant view; b) section.

Accelerometers characteristics used for vibration measurements.

Designation

Accelerometer

Sensibility (V/g)

Measurement range (g)

Location (m)

Ac1 Ac2 Ac3 Ac4 Ac5 Ac6 Ac7 Ac8

Wilcoxon 799M Wilcoxon 799M PCB 393B13/Wilcoxon 799M PCB 393B13/Wilcoxon 799M PCB 393B13/Wilcoxon 799M PCB 393B13/Wilcoxon 799M PCB 393B13/Wilcoxon 799M PCB 393B13/Wilcoxon 731A

1 1 10/1 10/1 10/1 10/1 10/1 10/10

±5 ±5 ±0,5/±5 ±0,5/±5 ±0,5/±5 ±0,5/±5 ±0,5/±5 ±0,5/±0,5

0,26 1,90 5,00 6,40 10,51 15,51 20,51 25,51/20,51

a) Figure 4.

b) General view of the accelerometers: a) sub ballast; b) soil foundation.

soil material. Therefore, it is thought that the use of aluminium stakes in a cross shape is more adequate in order to make the nailing process easier and to minimize mentioned problem. 5

IN SITU MEASUREMENTS

The in situ measurements consisted in two phases. In the first phase, measurements of environmental noise and vibrations due to the passage of different train compositions were carried out. The environmental noise was measured with 1314

the purpose of quantify the signal to noise ration. Measurements of the train passages were carried out to optimize the signals digitalization, by tuning the digitalization range in accordance with acceleration peaks in the accelerograms. In a second phase, measurements carried out to record the vibrations induced by the passage of several train compositions in the two railtracks: in east descendent railtrack (DEL) and the east ascending rail track (EAL). Vibrations induced by Pendolino train (“Alfa Pendular”) and Inter-City trains were recorded at speeds of about 220 km/h and 190 km/h, respectively, according to information collected near the REFER staff. According to the same source, the Suburban and Regional trains passage were recorded at speeds of about 120 km/h. 5.1 Environmental noise Figure 5a shows the acceleration measurements for the accelerometer Ac2 and Figure 5b shows the corresponding power spectra for the environmental noise. The amplitudes for the ambient noise ranges from –4 mg to 4 mg and the spectrum is flat in the frequency range of interest (from 15 to 200 Hz). Figure 5c shows that the significant environmental noise is characterized by the frequency range between 0 and 2 Hz. 5.2 Vibration measurements induced by train passage Several records have been performed for different train compositions and speeds. In this paper only measurements induced by the passage of Pendolino (“Alfa Pendular”) will be discussed, since this one travels at the highest speed. For Pendolino (“Alfa Pendular”), the highest accelerations were recorded during the passages in the VDE. In the ballast, peak accelerations of 30 m/s2 were observed. Figures 6 and 7 present the results in time and frequency domain, respectively. In the time domain it is possible to observe the passage of each axes of the train. Concerning the time histories of the first four sensors placed at a maximum distance of 6.40 m (Ac1 to Ac4), the contribution of each individual axle is clearly observed. For the ballast sensor (Ac1), the peak positive acceleration is around 30 m/s2 and the negative acceleration amplitudes are around 15 m/s2, which are about one half the positives ones. For the others, it can be seen that the acceleration amplitudes are of the same order. The peak accelerations from sensors Ac2 to Ac4 are of same order (0.60 m/s2), showing no significant reduction for the vibrations between these sensors. When comparing the peak amplitudes between the sensor Ac4 (0.40 m/s2) and Ac5 (0.08 m/s2), a significant reduction factor equal to 5 can be observed. From sensor Ac5 to Ac7, a reduction factor of 0.5 can be visualized between each consecutive sensor Sensors Ac7 and Ac8 placed at the same position for this experimental setup. The obtained results were in agreement with what was expected according to experiences in other countries for high-speed trains (Degrande 2000). With respect to spectral contents, it can be observed that the frequency of interest is in the range of 0 to 200 Hz. The spectral contents for sensors Ac1 to Ac4 are dominated by high frequencies, while lowest frequencies

a)

c)

b)

Figure 5. Measurements of environmental noise for accelerometer Ac2: a) time history; b) frequency spectrum; c) detail of frequency spectrum.

1315

Ac1

Ac2

Ac3

Ac4

Ac5

Ac6

Ac7

Ac8

Figure 6. Time history response of the vertical acceleration to the Pendolino train type (“Alfa Pendular”) passage.

Figure 7. Frequency spectrum response of the vertical acceleration to the Pendolino train type (“Alfa Pendular”) passage.

1316

characterise the spectral contents of the sensors placed far away from the track. At a train speed of 188.8 km/h (52.4 m/s) the expected main frequencies corresponds to axle, bogie and sleeper passage, whose approximated frequencies are respectively 19.42 Hz (L = 2.70 m), 2.76 Hz (L = 19 m) and 87.41 Hz (L = 0.60 m). 6

PROCESSING RESULTS

6.1 Determination of train velocity In the study of foundation behaviour for the passage of high speed trains, it is essential to know the train velocity. In theory, if, the train geometry and the instant of the passage of each axle is well known, the determination of train velocity is simple. However, in practice establishing the “moment of the passage of the axle” can be difficult. In Figure 8, is illustrated the determination of the moment of the passage of the axes in an acceleration diagram determined by a calculation model. In this case the determination of the time lag between the passage of the axes is simple. The calculation consists on the determination of the time lag between the passage of the first and last axle, with the purpose of minimize the error. Figure 8b refers to the measurements of the passage of the first train bogie, but in this case the localization of the instants of the passage of the axes is not clear. Concerning to the way of presentation of real measurements it is necessary to develop an algorithm for determination of train velocity. In that algorithm the initial estimate of velocity is done based on the determination of the instants when occur the first and last acceleration peaks, considering that these correspond to the passage of the first and last axes, respectively. Then, considering that this estimative could be affected by an error resulting from the difficulty of determination the exact moment of the passage of the axes, it is verified if it is possible to have a better estimation of that value. By better estimation it is meant the value of the initial instant and the train velocity that maximize an objective function. It was considered the following function: OF = {Axles} (t T

ini

,V )

× {a}

(1)

where {a} represents the acceleration vector and {Axles} (tini ,V ) represents a vector where elements are null with exception to the elements corresponding to the position of the axes. This vector depends on the initial instant and on the train velocity, i.e. which are precisely the variables which to be optimized. Depending on the form of the digital sign, noise, etc, application of the algorithm could lead to small variations of the initial estimate of velocity. Figure 9 presents the estimate of velocity and axes positions for one of the measurements for the Pendolino (“Alfa Pendular”) train. In this case the initial and final estimate only differs of 0.9 km/h. T

Figure 8.

Instant for axles passage: a) analytical model; b) measurements.

1317

6.2 Velocities and displacements Besides the value of accelerations, velocities and displacements induced by the passage of trains must be computed. These can be obtained through the accelerations by single and double integration, respectively. However, numerical integration of digital samples trend to spread the error and the noise causing significant deviations in the results. One way to overcome this problem is to apply filters to the digitalized signals. In the following diagrams an example of the application of a filter “base line correction” and “moving average” (with 600 points) to the diagrams of acceleration and velocity are presented. Figure 10 presents the diagrams without the application of filters, where miscalculation of diagrams of velocity and displacement can be observed. Figure 11 presents the same diagrams with the application of the filters mentioned above. The diagrams refer to the second point of measurement (sensor Ac2). As shown in Figures 10 and 11, the use of digital filters is very important in signal processing. Without these, results may be affected of important errors. Despite the numerical difficulties, always present in the application of digital filters, due to the possibility of removing important data from the signal, the information obtained is very valuable in assessing the quality and performance of the railway. These results are consistent with international experience, thus validating the methodology used. 7

FINAL CONSIDERATIONS

The measurements of vibration induced by the passage of high-speed trains are an important tool in assessing the quality and performance of the railway line. Excessive vibrations of the soil-track structure can carry high operating costs, particularly with regards to high-speed

Figure 9.

a) Figure 10.

Estimation of train speed and axles position.

b)

c)

Velocity and displacement calculus without application of filters.

1318

a) Figure 11.

b)

c)

Velocity and displacement calculus with application of filters.

railways, besides the discomfort caused to passengers and to people living near the railway line. On the other hand, the measurements provide essential data for validation numerical models. The detailed study of this phenomenon is of significant interest given the construction of high speed railways in Portugal. The paper addresses the issues regarding first “in situ” vibration measurements. The measurements were able to redefine test procedures and to detect weaknesses in the measuring system. In addition, the results were used to test the procedures for estimating the train velocities, the frequency range of interest for the near and far field and to estimate de soil deformations. ACKNOWLEDGEMENTS This work was carried out under the protocol of cooperation between the National Railway Network (REFER) and Tecminho—University Enterprise Association for development as a representative of the consortium UM/LNEC/IST/FCT-UNL, to develop knowledge within the methodology for the construction and the control of railway embankments and rail track layers, as part of the project POCI/ECM/6114/2004—“Interaction soil-railway track for high-speed trains”. REFERENCES Anderson et al. (2000). Model testing of two-layer railway track ballast. Journal of Geotechnical and Geoenvironmental Engineering, April 2000. Bahrekazemi, M. (2004). Train-induced ground vibration and its prediction. PhD Thesis. Royal Institute of Technology, Sweden. Brandl, H. (2004). Geotechnical aspects for high-speed railways. Gomes Correia & Loizos (eds), Proceedings of the International Seminar on Geotechnics in Pavement and Railway Design and Construction: 117–132, Rotterdam, Netherlands. Degrande, G. (2000). Free field vibrations measurements during the passage of a Thalys high speed train. Internal report BWM-2000-06, K.U. Leuven. Fortunato, E.M.C. (2005). Renewal of railways platforms. Studies about bearing capacity. PhD Thesis, University of Oporto, Porto, Portugal (in portuguese). Hendry, M.T. (2007). Train-induced dynamic response of railway track and embankments on soft peaty foundations. Master Thesis. University of Saskatchewan, Saskatoon, Canada. Madshus, C. & Kaynia, A.M. (2000). High-speed railway lines on soft ground: Dynamic behaviour at critical train speed. Journal of Sound and Vibration 231(3): 689–701. SUPERTRACK. (2005). SNCF Final report 2-Track measurements in Zouffgten. UIC. (1994). Earthworks and track bed construction for railway lines. Code UIC 719R, 2nd edition. Zhai et al. (2004). Modelling and experiment of railwayballast vibrations. Journal of Sound and Vibration 270 (2004): 673–683.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

The use of biaxial geogrids for enhancing the performance of sub-ballast and ballast layers—previous experience and research J. Kwon & J. Penman Tensar International Corporation, Atlanta, GA, USA

ABSTRACT: This paper describes experiences in the use of biaxial geogrids in rail applications. Since their first use more than 25 years ago, geogrids have been used for ballast/ sub-ballast reinforcement on many occasions on main line track projects, industrial rail spurs and the development of intermodal yards. Incorporated within unbound aggregate layers, geogrids interact with the surrounding aggregate particles to help carry the tensile loads imposed by rail vehicles. In the early application of geogrids within the ballast and sub-ballast layers of rail structures, the products were typically used to provide an extension of the roadbed service life. In more re-cent times however, the emphasis seems to have switched, whereby the focus tends to be more on a reduction in the thickness of the ballast layer, or more likely the underlying subballast. The adoption of this approach is intended to maximize “up front” cost savings for the project. In the UK, the approach to roadbed thickness reduction has progressed to such an extent that clear guidance now exists to allow the designer to quantify the reduction that can be attained using geogrid reinforcement; this is provided by Network Rail (the country’s National Rail Authority) in their Code of Practice RT/CE/C/039 (2003). 1

INTRODUCTION

1.1 Geogrid reinforcement Most geosynthetics used in transportation engineering applications are made of synthetic polymers. A polymer is essentially a long-chain molecule containing one or more repeating units of atoms, joined together by strong covalent bonds. Polymer molecules and their chains make up the polymeric material and therefore define the behavior and performance of geosynthetics (Koerner 1997). Although there are several different types of geogrid currently available within the market, the content of this paper is confined to one particular type—a geogrid that is formed from an integral plastic sheet that is punched with a regular series of holes and then stretched in both the longitudinal and transverse directions, thus aligning the long chain molecules. Due to the nature of the manufacturing process, this specific type of geogrid possesses a unique combination of material properties, essential for generation of the most efficient transfer of stress from the surrounding aggregate i.e. strong junctions, high ribs, high torsional strength, etc. Biaxial geogrids have high tensile stiffness in both the longitudinal and transverse direction. This results in the mobilization of reinforcement benefits at low strain. They are also characterized by rigid apertures, dimensioned to suit a particular aggregate grading. 1.2 Geogrid reinforcement mechanism Incorporated within unbound aggregate layers, geogrids interact with the surrounding aggregate particles to help carry the tensile loads imposed on the roadbed material due to the trafficking of the rail vehicles above. As granular material is compacted over a geogrid, the coarse aggregate particles partially penetrate through the apertures to create a strong and 1321

positive “mechanical interlock” (Figure 1). This enables the geogrid to confine individual aggregate particles and reduce shear, thereby mobilizing the maximum bearing capacity of the underlying subsoil. In short, the use of geogrids results in stiffness enhancement and stiffness retention of a granular layer, leading to improved long-term performance. The confinement of aggregate particles is particularly important in rail applications as this reduces the amount of lateral spread, a major cause of roadbed settlement. The use of geogrids in ballast/sub-ballast reinforcement applications can be divided into two main categories: Sub-ballast Reinforcement When used within the sub-ballast layer, the geogrid is invariably placed at the bottom of the -layer i.e. at the interface with the underlying subgrade. The main reason for adopting a geogrid in this manner is to help distribute the imposed traffic loads more efficiently onto the subgrade (Figure 2). As such, this technique tends to be adopted most commonly when the subgrade strength is less than ideal i.e. CBR < 5%. The principle benefit of using a geogrid to reinforce the sub-ballast layer is to increase the factor of safety against bearing failure for a particular roadbed thickness. Alternatively, for a given target factor of safety, the required roadbed thickness can be reduced significantly. Ballast Reinforcement When reinforcing the ballast layer, the geogrid can be placed within the layer itself i.e. nearer to the load source. Although there is evidence to suggest that raising the geogrid position within the ballast layer can provide a performance benefit, for practical purposes, it is generally installed at the ballast/sub-ballast interface. The main reason for including a geogrid within the ballast layer is to reduce its rate of settlement during trafficking, thereby extending the period between resurfacing or ballast replacement operations. Geogrids can also assist with the effective separation of the roadbed and underlying subgrade. When properly graded aggregate fill is used, the aggregate performs as a “natural filter.” This helps to minimize subgrade problems such as ballast pockets and subgrade attrition, major sources of poor track geometry. 1.3 Installation The placement method for geogrids depends on the nature of the rail line construction. In order to reinforce the roadbed beneath a new rail line for example, geogrids are simply rolled out directly on top of the prepared subgrade or ballast layer (Figure 3). A 300 to 900 mm overlap (shingle style, in the direction of fill advancement) is sufficient to ensure stability across the installation. The actual overlap length required is dependent on the subgrade strength (i.e., the weaker the subgrade, the greater the overlap length required). When geogrids are used to rehabilitate existing rail lines, the existing track and underlying ballast is

Figure 1.

Mechanical interlock resulting from the partial penetration of aggregate particles.

1322

Subgrade

Subgrade

Geogrid

Figure 2.

Load distribution with and without geogrid reinforcement.

Figure 3.

Standard geogrid installation procedure for new construction projects.

removed completely and a procedure similar to that described for a new track is adopted. In some cases however, the existing track is jacked up and the underlying ballast removed before rolling out the geogrid. The track is then lowered and a track mounted ballast machine is used to place and compact new ballast material on top of the geogrid. Recent advancements have been made whereby track ballasting operations are now often undertaken using specialized track mounted maintenance equipment. The ballasting machine lifts and cleans the existing ballast as it travels along. For projects where the recycled ballast needs to be reinforced, a simple modification is made to the machine, which allows the geogrid to be rolled out during normal maintenance operations (Figure 4). No significant loss of time results from the installation of the geogrid. Compaction of loosely placed ballast is normally achieved using a track-mounted tamping machine. Care must be taken to ensure that the geogrid is not damaged as a result of ballast compaction operations. A minimum clearance of 100 mm is required at the bottom of the tines to ensure the geogrid remains intact. 2

PREVIOUS RESEARCH

2.1 Queen’s University, Ontario, Canada Research on the use of geogrids to reinforce roadbed layers dates back as early as the mid 1980’s. Raymond & Bathurst (1987) provided a summary of the research work undertaken at 1323

Figure 4.

Geogrid installation during ballast cleaning operation. Number of cycles 0

1

10

100

1,000

10,000

100,000

1,000,000 10,000,000

Settlement (mm)

25

50

75 CBR = 100% control 100

CBR = 100% reinforced CBR = 39% control

125

CBR = 39% reinforced CBR = 1% control

150

Figure 5.

CBR = 1% reinforced

Queen’s University test results (Raymond & Bathurst, 1987).

Queen’s University in Kingston, Ontario. A large-scale test program was carried out to simulate full-scale single tie loading on ballast placed over artificial subgrades of variable compressibility. American Railway Engineering and Maintenance-of-Way Association (AREMA) Grading No. 4 ballast was used in the test. An MTS hydraulic actuator was mounted on top of test box applied repeated loads at a rate of 0.5 Hz. A steel cross-tie was used to transfer the load to the ballast surface with an applied pressure of 100 MPa. The tests indicated that inclusion of a biaxial geogrid within the ballast layer lead to a decrease in permanent vertical deformations of up to 50% after only 100,000 load applications (Figure 5). These benefits increased with time whereby the number of load cycles required to produce a permanent vertical deformation of 50 mm increased by a factor of 10 when a geogrid was used. 2.2 British Rail research, Derby, United Kingdom Similar research was undertaken in the UK in the early 1990’s. The National Rail Authority (then called British Rail) undertook a series of independent tests at their own test facility in 1324

Derby; the results of the testing are published in Matharu (1994). In these tests, a full-scale rail track was built with a “rolling load rig” used to apply the load through the rail and tie structure to the underlying roadbed. The British Rail trial consisted of three tests that took place on monitored ties placed on ballast material compacted above a simulated soft subgrade. In two of the tests, a geogrid was included within the underlying ballast material. A third unreinforced test served as a control section. The results of these tests were then compared with a previous test undertaken in the same test facility using a solid formation characterized by a subgrade modulus of 10 MPa. In each test, a total traffic loading of 2 million gross tons was applied to the test track. Potentiometers were used to measure the elastic and permanent settlement of the track as illustrated in Figure 6. The performance of the various reinforced and unreinforced roadbed sections trafficked during the British Rail testing are presented in Figure 7. Based on these results, it can be seen that the performance of a roadbed is improved significantly through the inclusion of geogrid reinforcement. In addition to monitoring the long-term settlement of the track during loading, the instrumented cross-ties were also analyzed to determine the dynamic deflection occurring during each load cycle (Figure 8). Based on these results, it was determined that the rail track deflection is reduced by approximately 40% when the underlying roadbed is reinforced with a biaxial geogrid. 2.3 The University of Nottingham Rail Test Facility, UK More recently, performance of geogrid reinforced ballast was evaluated at the Nottingham Centre for Pavement Engineering in the UK (Brown et al. 2006). The large-scale testing was undertaken using three actuators which applied load in sequence to three individual cross-ties, thus simulating the passing of a train. A series of 92 kN loads were applied to the cross-ties at a rate of 3 Hz. A large (65 mm wide) aperture biaxial geogrid was placed at the interface between a 300 mm-thick ballast layer and the underlying silt subgrade. Potentiometer 50 or 100 mm 300 mm

Biaxial geogrid British Rail test facility (Matharu, 1994).

Initial lift to operational level (mm)

Rail track Rail track level raised level before reinstatement during re-ballasting

Figure 7.

Settlement (mm)

Position after 2MGT of trafficking

Settlement after 2MGT of Traffic (mm)

Figure 6.

“Soft sub-structure” Rubber bonded cork mats

0

10

Initial lift (mm) 20 30

40

50

0 Firm subgrade 10

20

Soft subgrade With Geogrid

Improvement from Geogrid

30

Soft subgrade Without Geogrid

40 Test 1: Soft subgrade and no geogrid Test 2: Soft subgrade and geogrid 50 mm above Test 3: Soft subgrade and geogrid 100 mm above

Long-term settlement of reinforced and unreinforced roadbed sections (Matharu, 1994).

1325

Position of wheel along track (m) 5

10

15

20

Deflection (mm)

–5

0

5

10

15 Test 1: unreinforced roadbed Test 3: geogrid reinforced roadbed Figure 8.

Dynamic roadbed settlement for an individual load cycle (Matharu, 1994).

Number of cycles 0

200,000

400,000

600,000

800,000

1,000,000

0 Control Control

Settlement (mm)

2

Reinforced Reinforced

4 6 8 10 12 14

Figure 9.

Relative performance of reinforced and unreinforced ballast (Brown et al. 2006).

The settlement profiles for an unreinforced (control) and biaxial geogrid reinforced ballast section are presented in Figure 9. These results indicate that the number of cycles required to attain a permanent settlement of around 7.5 mm is 350,000 for the unreinforced section. When a biaxial geogrid is included within the ballast layer however, the number of cycles required to attain the same permanent settlement goes up to 1,000,000. This marks a 2.8 fold increase in the service life of the ballast layer. 3

FIELD CASE STUDIES

3.1 Network Rail field test at Coppull Moor, UK Sharpe et al. (2006) describe a full-scale field test undertaken at Coppull Moor on the West Coast Main Line, the most heavily trafficked rail line in the UK. The existing roadbed was constructed 1326

Standard deviation of surface deflection over 35m (mm)

Year

1995 0 1

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

With geogrid geogridstabilization stabilization

2 3 4 5

Limit for imposing speed restrictions

Without geogrid

6 7

Track rehabilitation rehabilitation Track with geogrid with geogrid

Figure 10. Surface deflection data for section of West Coast Main Line at Coppull Moor, UK (Sharpe et al., 2006).

over a fairly soft subgrade and had a long history of problems requiring regular maintenance. The owners of the track (Network Rail) were interested in finding a more permanent solution to the problems associated with this particular section of track. Therefore, during one of the regular maintenance events, a biaxial geogrid was included within the ballast section. Regular monitoring of the track was undertaken both prior to and following installation of the geogrid. A High Speed Track Recording Coach (HSTRC) is essentially a machine that measures the deflection of the track itself during trafficking and thereby determines the stiffness of the underlying roadbed. It is used to help identify the sections of track most in need of maintenance. Figure 10 shows the results of the surface monitoring undertaken by the HSTRC. Based on this testing, it can be seen that the rate of track settlement was reduced by a factor of around 3.6 times once the geogrid was installed. A separate section of track where a geogrid was installed actually showed an identical 3.6 fold extension of the ballast service life, though the magnitude of the deflection rates (1.44 mm/year unreinforced and 0.4 mm/year reinforced) were different. The reduction in the rate of surface deformation provided by the geogrid reinforcement, extended the periods between ballast cleaning/tamping operations significantly for this busy section of track. 3.2 CSX line rehabilitation, Milstead, Alabama, USA Specific full-scale project experience in the United States dates back as early as the late 1980’s and includes a CSX rail project in Milstead, Alabama (Walls & Galbreath 1987). Due to persistent problems requiring regular track maintenance, the original track had already been moved once in 1976. However, within months of the reconstruction, more problems were observed as a result of the poor soil conditions and high groundwater table. The foundation soils consisted of inter-bedded sands and soft clays. By May 1983, maintenance was required every 2 to 4 weeks and an 8 kmh speed restriction was in permanent effect. An additional realignment of the track was considered, but in the end the decision was made to reinforce the new clean ballast using a biaxial geogrid; A lightweight, non-woven geotextile was also included within the rehabilitated ballast to provide additional separation. Placement of the biaxial geogrid and geotextile within the ballast was undertaken as part of routine ballasting operations. The track was first raised using power jacks and the geosynthetics unrolled beneath the raised cross-ties. Following three months of post-rehabilitation rail trafficking, no track stability problems were encountered and the maximum speed was raised to 56 kmh. After four years of problem-free operation, all speed restrictions were lifted. 3.3 Utah Transit Authority (UTA) light rail, Salt Lake City, Utah, USA A new 70 km-long commuter rail line was constructed between Weber County and Salt Lake City, Utah. The subgrade soil mainly consists of low-to-medium strength cohesive soils with some 1327

30

Deflection (mm)

20 10 0 –10 –20

Before maintenance After Geogrid Geogridinstallation installation

–30 124850

Figure 11.

124900

124950

125000 Chainage (m)

125050

125100

125150

Surface deformation before and after geogrid installation—Nagykanizsa, Hungary.

stretches constructed on loose to dense sand. Due to the high cost of good quality aggregate in the area, the contractor sought ways to reduce the amount of sub-ballast required for the project. The original design called for a 300 mm thick ballast section over 300 mm of sub-ballast. Due to the stiffening effect of the reinforcement, it was demonstrated that the use of a biaxial geogrid could reduce the required sub-ballast thickness by 100 mm. This provided significant savings in both material costs and the speed of construction. In addition to reducing sub-ballast requirements, the geogrid reinforcement also reduced the amount of subgrade excavation required and allowed the contractor to keep the existing shallow utilities in place. 3.4 Ground stabilization for rail track, Nagykanizsa, Hungary A section of main line track in Nagykanizsa, Hungary required surface maintenance at a rate of around once every month. The problems were associated with the continuous penetration of fine particles from the embankment body into the ballast layer, along with movement of ballast particles into the underlying subsoil. Again, the client sought a long-term solution that would avoid the need for regular maintenance. Rehabilitation of the roadbed section consisted of excavation of the existing ballast and the uppermost 10 cm of contaminated subgrade. A lightweight non-woven geotextile was then placed on the exposed formation and immediately overlain with a large aperture biaxial geogrid. New ballast stone was then placed on top of the geogrid to the same level as before. The roadbed condition was monitored both before and after rehabilitation using a track mounted monitoring machine (similar to that used at Coppull Moor in the UK). The results of the track monitoring (Figure 11) clearly illustrate the stiffening effect provided by the geogrid reinforcement. As a result of the geogrid reinforcement, service disruptions caused by frequent track maintenance have been eliminated. 4

DESIGN METHODOLOGIES

4.1 Network Rail company code of practice for formation treatment Network Rail (2003), the National Rail Authority in the UK have published a Code of Practice dedicated to the subject of formation treatments. As there is very little new rail line 1328

WithoutReinforcement Without Reinforcement WithGeogridReinforcement With Geogrid Reinforcement

Figure 12. Network Rail design chart for determining the required roadbed thickness (Network Rail, 2003).

construction in the UK at present, the scope of the document is limited to the remodeling of existing track and track renewals. The use of geosynthetics is described in Section 9.3 of Network Rail Company Code of Practice. The use of geogrid reinforcement is advocated where ‘there has been difficulty in achieving the required track geometry in the past’. It is stated that for existing lines, the minimum Dynamic Sleeper Support Stiffness (K) required is only 30 kN/mm/sleeper end for a geogrid reinforced roadbed compared with 60 kN/mm/sleeper end when the geogrid is absent. As the actual roadbed stiffness attained is determined by the thickness of aggregate used, this effectively means that the required sub-ballast/ballast thickness is significantly less when geogrid reinforcement is used. The main design chart for determining the required roadbed thickness is presented in Figure 12. For the case illustrated, it is assumed that the subgrade strength is around 80 kN/m2 i.e. a stiff clay. Under these conditions, the required roadbed thickness would be 600 mm for an unreinforced roadbed; this thickness would be reduced to only 400 mm however if a biaxial geogrid is used to reinforce the roadbed section. It is indicated within the code of practice that the design chart has been derived using a combination of empirical data and multi-layer elastic theory. Further, it is stated that the thicknesses determined using the chart are in general agreement with those adopted by the National Rail Authority in Germany. When considering using the design chart presented in Figure 12, it is important to understand that the geogrid curve is only appropriate for specific geogrid products that have undergone the rigorous approval process required by Network Rail. 4.2 American Railway Engineering and Maintenance-of Way Association (AREMA) The AREMA design manual (2007) indicates that the load distribution through a roadbed structure is approximately the same regardless of the relative thicknesses of the subballast and ballast layers. Therefore, the combined depth of ballast and sub-ballast is calculated as a single unit to ensure that the pressure imposed on the subgrade does not exceed the allowable bearing pressure for a particular set of subsoil conditions. Based on a series of laboratory tests undertaken at the University of Illinois, Talbot (1920) developed an empirical formula to determine the vertical pressure exerted onto the ballast 1329

under the centerline of a rail tie at its intercept with the rail and at a given depth below the bottom surface of the cross-tie: pc = 16.8 ×

pa h1.25

(1)

Therefore, ⎛ p ⎞ h = ⎜16.8 a ⎟ pc ⎠ ⎝

0.8

(2)

where pc = stress at depth h under tie centerline, including safety factor (psi); pa = pressure at tie face (psi); and h = depth of ballast plus sub-ballast below the ties (in.). The formulas in the AREMA manual effectively provide a means by which an engineer can determine the imposed bearing pressure for an unreinforced roadbed section. To allow for the inclusion of geogrid reinforcement, it is necessary to understand how the load distributed onto the subgrade changes when the aggregate is fully confined. Guidance on this is provided by the US Army Corps of Engineers (2001). The approach adopted by the Corps is to modify the bearing capacity factor (Nc) used to determine the ultimate bearing pressure of the subgrade. It is stated that for an unreinforced section, an Nc value of 2.8 should be used to determine the ultimate bearing pressure. When the aggregate is confined with a punched and drawn biaxial geogrid (full specification provided by the Corps based on their own independent testing), the Nc factor to be used rises to 5.8. 5

SUMMARY

The paper has described several research projects and case studies associated with the use of biaxial geogrids to reinforce the sub-ballast and ballast layers beneath rail structures. Geogrids placed within the sub-ballast layer are typically used to reduce the required aggregate thickness and provide initial construction cost savings. Additional life cycle savings can be provided by inserting a geogrid within the ballast layer, thus extending the period between ballast resurfacing or replacement operations. REFERENCES American Railway Engineering and Maintenance-of-Way Association: 2007. Manual for railway engineering. Brown, S.F., Brodrick, B.V., Thom, N.H. & McDowell, G.R. 2006. The Nottingham railway test facility, UK. In Proceedings-Institution of Civil Engineers Transport. Vol. 160 (2): 59–66. Koerner, R.M. (4th edition) 1997. Designing with geosynthetics. New Jersey: Prentice Hall. Matharu, M.S. 1994. Geogrids cut ballast settlement rate on soft substructures. Railway Gazette International: 165–166. Network Rail Code of Practice. 2003. RT/CE/C/039. Formation treatments. Raymond, G.P. & Bathurst, R.J. 1987. Performance of large-scale model single tie-ballast systems. Transportation Research Record. 1131: 7–14. Sharpe P., Brough M. & Dixon J. 2006. Geogrid trials at Coppull Moor on the West Coast Main Line. Railway Foundations-Railfound 06: 367–375. Talbot, A.N. 1920. Second progress report of the committee on stresses in track. In proceedings of the AREA. Vol. 21: 645–814. U.S. Army Corps of Engineers, 2003. Technical Letter ETL 1110-1-189, Engineering and Design. Use of geogrids in pavement construction. Department of the Army. Washington D.C. USA. Walls, J.C. & Galbreath, L.L. 1987. Railroad ballast reinforcement using geogrids. In Proceedings of Geosynthetics ’87. IFAI. Vol. 1: 38–45. New Orleans. USA.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Comparison of in situ performance-based tests methods to evaluate moduli of railway embankments A. Gomes Correia & J. Martins University of Minho, Guimarães, Portugal

L. Caldeira National Laboratory of Civil Engineering—LNEC, Lisbon, Portugal

E. Maranha das Neves Technical University of Lisbon—IST, Lisbon, Portugal

J. Delgado National Railway Network—REFER, Lisbon, Portugal

ABSTRACT: Compaction control based on performance-based test methods has been used recently. These test methods use different load and strain rates as well as boundary conditions requiring the need of calibration and correlation between them. In this paper, correlations are established between the small strain modulus Ev measured from different “in situ” performed-based test methods carried on a trial embankment. The Ev modulus was obtained from spot tests, namely, static plate loading test (SPLT), light falling weight deflectometer (LFWD), soil stiffness gauge (SSG), and a continuous test with “Portancemètre” equipment. The SPLT was used as a reference test. The paper describes the experimental plan, presents the theory for each test method, and gives the results and established correlations. 1

INTRODUCTION

The current quality control/quality assurance (QC/QA) methods depend on achieving a certain dry density using acceptable compaction energy, for a certain moisture content previously defined. Mechanical properties (i.e., stiffness and strength) are another acceptance criterion for earthworks with higher demands for compaction control, like railway embankments and rail track layers. These mechanical properties are often measured through static plate loading tests. This conventional approach is time consuming, labour intensive and costly. Moreover, these tests are often limited in number and do not provide a statistical basis of the earthwork quality. Since railway embankment and rail track layer design methods are based on engineering parameters of materials, such as stiffness and/or strength, the QC/QA procedures of construction should be based on a criterion that is closely correlated to the performance parameters used in the design. Besides, a guarantee of acceptable earthwork performance cannot be achieved using only soil density and moisture content. There is a recent strong trend towards using stiffness and strength to control compaction, given the importance of these mechanical properties in the evaluation of pavement materials (Edil & Sawangsuriya 2005, Alshibli et al. 2005, Loizos et al. 2003, Nazzal 2003, Briaud 2001). Increasing demands for better, cheaper and faster compaction control have lead to technology improvements. Instruments for the field test evaluation of soil mechanical properties have been recently developed, such as the Light Falling Weight Deflectometer (LFWD), the soil stiffness gauge (SSG) and “Portancemètre”. These are non-destructive tests that can be conducted independently and in conjunction with conventional moisture density testing, 1331

improving statistical evaluation and reducing variability. Thus, the construction quality of the entire earthwork is substantially enhanced. The Qc/Qa for railways according to the “Union Internationale des Chemins de fer,” Code UIC 719R (UIC 1994) states that compaction requirements should be precise and depend on the type of railway and the traffic. However, compaction control of the sub-ballast layer for new railway lines requires an Ev2 modulus higher than 120 MN/m2, as well as a dry density higher than 103% of Standard Proctor (Standards NF P 94093 and DIN 18127). The national research project POCI/ECM/61114/2004, entitled “Interaction soil-rail track for high speed trains”, financed by the Foundation for Science and Technology, met its goal of establishing a protocol between the National Railway Network (REFER) and four national research institutions to develop the knowledge concerning the methodology for the construction and control of the railway embankments and rail track layers for high speed trains. One of the objectives of this protocol is to establish a methodology for quality control of compacted layers by different available test methods, promoting continuous compaction control. This objective was met by constructing a trial embankment, which took place near the new Évora railway line, about 2.5 km from the “Monte das Flores” railway station, and running tests between October and November of 2006. This paper describes the trial embankment, the experimental program and the different tests carried out for evaluation of the moduli, including SPLT, LFWD, SSG and “Portancemètre”, and it presents correlations between results of these tests. 2

TRIAL EMBANKMENT AND EXPERIMENTAL PLAN

In order to complete the work, a trial embankment was constructed near the new Évora railway line, and an experimental plan for the evaluation of the physical and mechanical properties of the studied materials was developed. Materials similar to the ones used on the new Évora railway line were employed in the trial embankment. Two types of materials were tested: soil for the embankment layers and aggregate for the sub-ballast layer (see Figure 1). Due to length constraints, only some results for soil material will be presented in this paper. The soil material used is classified as clayey sand (SC ) (ASTM D 2487 2000) with liquid limit (LL) of 32% and plasticity index (PI ) equal to 11%. The optimum moisture and maximum dry density obtained from modified Proctor test was 8.6% and 20.5 kN/m3, respectively. Before the construction of the trial embankment, foundation with 0.60 m thickness was compacted in two layers with 0.30 m thickness, in order to promote homogeneity of the support of the trial embankment.

Figure 1.

Experimental embankment: aggregate layer on the left side and soil layer on the right side.

1332

Table 1. Synthesis of the state conditions and geometric characteristics of soil layers adopted on the experimental embankment construction. Moisture content (%)

Thickness (m)

Layer dimensions (m)

Executed above

wopt –2

0.30 0.40 0.50

50 × 6 25 × 6 50 × 6

Foundation 0.30 m wopt –2% Foundation

wopt

0.40

50 × 6

Foundation

wopt +2

0.40

50 × 6

0.30 m wopt –2% and 0.30 m wopt

4

SRM-WC-SPLTLFWD-SSG (6)

5

6

SRM-WC-SPLTLFWD-SSG (8)

7

8

SRM-WC-SPLTLFWD-SSG (6)

SRM-WC-SPLTLFWD-SSG (8)

9

10 SRM-WC-SPLTLFWD-SSG (4)

LA SRM-WC-SPLTLFWD-SSG (10)

SRM-WC-SPLTLFWD-SSG (12)

SRM-WC-SPLTLFWD-SSG (10)

SRM-WC-SPLTLFWD-SSG (12)

L1 WC-LFWD-SSG

B

WC-LFWD-SSG

L2 WC-LFWD-SSG

WC-LFWD-SSG

L3

SRM-WC-SPLTLFWD-SSG (6)

C

SRM-WC-SPLTLFWD-SSG (8)

SRM-WC-SPLTLFWD-SSG (4)

SRM-WC-SPLTLFWD-SSG (4)

SRM-WC-SPLTLFWD-SSG (8)

SRM-WC-SPLTLFWD-SSG (6)

LC SRM-WC-SPLTLFWD-SSG (10)

Figure 2.

SRM-WC-SPLTLFWD-SSG (12)

SRM-WC-SPLTLFWD-SSG (10)

SRM-WC-SPLTLFWD-SSG (12)

PORTANCE MÉTRE

SRM-WC-SPLTLFWD-SSG (4)

A

3

PORTANCE MÉTRE

2

PORTANCE MÉTRE

1

Experimental plan for each layer.

The several layers of the trial embankment were compacted with the state conditions and geometric characteristics summarized in Table 1. The experimental plan consisted of spot tests, the sand replacement method, water content, SPLT following AFNOR NF P91-117-1 and DIN 18134 standards, LFWD, SSG, and a continuous test “Portancemètre”. Each layer was divided into lanes of two metres (A, B, C) and columns with 5 m width (1 to 10). In lanes A and C, all types of tests were performed, while lane B was only subject to non-destructive tests (see Figure 2). Note that in lanes A and C, the “Portancemèmetre” passages were done after the SPLT tests. Each layer was tested for different energy levels corresponding to 4, 6, 8, 10 and 12 passages of the vibrating roller.

3

PROCEDURES/STANDARDS

3.1 Static Plate Loading Test (SPLT) based on the AFNOR NF P94-117-1 standard This standard specifies a method for the determination of the relationship between the load and settlement (load-settlement curve). The goal is to assess the deformation and strength characteristics of the soil and to determine the strain modulus (NF P 94-117-1 2000). The test consists in the application, after a preload, of two successive loading cycles on a plate with stiffness and diameter normalised. For a 600 mm diameter plate (see Figure 3a), the first load cycle should correspond to a 0.25 MPa stress under the plate, and this stress is maintained until the plate settlement is stabilised. Upon this stabilisation, the load is immediately released. The second load cycle uses a stress under the plate of 0.20 MPa. The load release should be done only after the plate settlement stabilisation, as in the first load cycle. 1333

a)

b)

Figure 3. Static Plate Loading Test (SPLT) based on standard AFNOR NF P94-117-1: a) in situ test; b) interpretation.

The strain modulus EV 2, is calculated for the second loading cycle using the Boussinesq solution and secant method (see Figure 3b) as follows: EV 2 =

π p⋅r ⋅ (1 −ν 2 ) 2 z2

(1)

where ν is the Poisson ratio, r is the radius, p is the normal stress below the plate and z2 is the settlement of the plate. 3.2 Static Plate Loading Test (SPLT) based on the DIN 18134 standard As with the AFNOR standard, the DIN standard specifies a method to determine the strain modulus EV 2, although the procedure is different (DIN 18134 2001). To determine the strain modulus EV , the load is applied in at least six stages, in approximately equal increments, until the required maximum normal stress is reached. Each increase in load (from stage to stage) must be completed within one minute. The load is released in stages, first to 50% and 25% of the maximum load and then completely. This is followed by a second loading cycle, in which the load is immediately increased to the final stage of the first cycle. A 300, 600 or 762 mm loading plate can be used. To determine the strain modulus for design calculations, the load is increased until a settlement of 5, 8 or 13 mm, or a normal stress below the plate of 0.50, 0.25 or 0.20 MN/m2, respectively, is reached. If the required settlement is reached first, the normal stress measured at this stage is taken as the maximum stress. A 300 mm diameter plate was used for this work (see Figure 4a). The strain modulus Ev2, is calculated for the second loading cycle using the tangent method (see Figure 4b) as follows: EV 2 =

1.5 ⋅ r a1 + a2 ⋅ σ 0 max

(2)

where r is the radius, σ0 max is the maximum average normal stress below the plate and a1 and a2 are factors of the smooth load settlement curve. 3.3 Light Falling Weight Deflectometer (LFWD) The LFWD is a portable device used to determine the strain modulus (also called dynamic modulus) ELFWD. It consists of a loading device that produces a defined load pulse, a loading transducer and at least one geophone sensor to determine the deflection of the centre of the plate. The ELFWD is calculated from the load pulse and deflection. 1334

a)

b)

Figure 4. Static Plate Loading Test (SPLT) based on standard DIN 18134: a) in situ test; b) interpretation.

(1) Mass (2) Rubber buffers (3) Stress cell (4) Plate

a)

b)

Figure 5. Light Falling Weight Deflectometer: a) general aspect; b) detail of components (adapted from Fortunato 2005).

A Prima 100 LFWD manufactured by Carl Bro Pavement Consultants was used in the experiments. It weighs approximately 26 kg and has a 10 kg falling mass that drops on the bearing plate via four rubber buffers (see Figure 5). The centre geophone sensor measures the deflection caused by the impact on the loading plate. During the test, the falling mass impacts the plate, producing a load pulse in the range of 1–15 kN in about 15–20 ms. The diameter of the loading plate used in this study was 300 mm. The measured deflection at the centre of the plate was used to calculate the strain modulus ELFWD using the Boussinesq solution as follows: E LFWD =

k ⋅ (1 −ν 2 ) ⋅ σ ⋅ R δc

(3)

where k = π/2 for rigid plate or K = 2 for flexible plate; δc = centre deflection; σ = applied stress; and R = radius of the plate. Several studies have been recently conducted to evaluate LFWD measurements. The SPLT test is standardised and has been used for many years as a useful in situ test to evaluate the strength/stiffness of pavement, and it can be considered as a reference test. Some studies using both the SPLT and LFWD (Livneh & Goldberg 2001; CBPC, 2000) proposed some equations to correlate results from these tests. Different types of soils were tested with LFWD and SPLT (Alshibli et al. 2005) in a laboratory setting to understand their relation, where values of the latter ranged approximately from 0 to 700 MPa. 1335

Fortunato (2005) performed 36 in situ tests with LFWD and SPLT during a geotechnical site investigation work on the platform of the old railway of the Portugal North railway line. The equipment and standards used were similar to those used in this study. The SPLT values of EV2 range from 36 to 148 MPa, and relationships between moduli obtained by the two tests were established. 3.4 Soil Stiffness Gauge (SSG) The Humboldt Stiffness Gauge is a field instrument that non-destructively measures soil stiffness and soil modulus; it is intended for the evaluation of soils, aggregates and treated materials used in earthworks and roadways. The instrument weighs approximately 10 kg. It has a compact size of 28 cm in diameter by 25.4 cm in height (see Figure 6a). The device rests on the soil surface via a ring-shaped foot, which has an outside diameter of 114 mm and an inside diameter of 89 mm. The foot rests directly on the soil and supports the weight of the “Geogauge” via several rubber isolators. The foot rests directly on the soil and supports the weight of the “Geogauge” via several rubber isolators. A mechanical shaker, which is attached to the foot, shakes the “Geogauge” from 100 to 196 Hz in 4 Hz increments, producing 25 different frequencies and generating a force of 9 N. The “Geogauge” has sensors that measure the force F and the deflection δ of the foot (see Figure 6b). The magnitude of the vertical displacement induced at the soil–ring interface is typically less than 1.27 × 10–6 m. It is measured using velocity sensors. A microprocessor computes the stiffness k (the layer’s resistance to deflection) for each of the 25 frequencies, and the average value of the 25 measurements is displayed along with a standard variation. The “Geogauge” stiffness can then be converted to the soil strain modulus ESSG using the following equation: ESSG =

k ⋅ (1 −ν 2 ) 1.77 ⋅ R

(4)

where ESSG = soil’s strain modulus (MPa); k = “Geogauge” reading (MN/m); ν = Poisson’s ratio; and R = radius of the “Geogauge” foot. A measurement of the depth on the order of twice the foot outside diameter is produced (i.e., 23 cm). A laboratory evaluation (Alshibli et al. 2005) on different soil types using both SSG and SPLT gave values for the latter from approximately 0 to 500 MPa. Equation 5 describes the regression model: ESPLT = 15.8e 0.011⋅ESSG

(R2 = 0.69)

(5)

1 – Rigid foot with annular ring 2 – Rigid cylindrical sleeve 3 – Clamped flexible plate 4 – Electro-mechanical shaker 5 – Upper velocity sensor 6 – Lower velocity sensor 7 – External case 8 – Vibration isolation mounts 9 – Electronics 10 – Control & display 11 – Power supply a) Figure 6.

b) The Humboldt Stiffness Gauge (SSG): a) general aspect; b) schema of components.

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3.5 “Portancemètre” The “Portancemètre” is an instrument developed by the “Centre d’Études Techniques de l’Équipment” (CETE) in France. This equipment applies a load at a frequency 35 Hz to the soil through a vibration wheel while rolling at a speed of 1 m/s. The instrumentation installed on the equipment permits the measurement of the vertical component of acceleration of the vibration and suspended masses, and the vibration frequency and the phase angle between the vibration vertical amplitude and the centrifugal force applied to the wheel (see Figure 7). An associated algorithm calculates the vertical force applied to the soil and the corresponding deflection. The vertical component of the applied force by the vibration wheel is calculated by the following expression (Quibel 1999): FTA = M1 ⋅ g + M 0 ⋅ ΓV 1 + (M1 − M 0 ) ⋅ ΓV 2 + me ⋅ ω 2 ⋅ cos ϕ

(6)

where M1 * g is the total weight; M0 * ΓV1 is the inertial force of the vibrating mass with ΓV1 being the vertical acceleration measured by means of a single axial accelerometer; (M1 – M0)* ΓV2 is the inertial force of the frame with ΓV2 being the vertical acceleration of the suspended mass; me * ω 2 * cosϕ is the vertical component of the centrifugal force produced by the eccentric mass. The vertical movement of the vibration wheel is determined by a double integration of the signal of the vertical acceleration. The mean of the measured values of the force and deflection in thirty successive periods gives the force-deflection curve, of which the upward part is subject to a linear regression in the zone 30% to 90% of the vertical maximum force applied to determine the stiffness. With a vibration frequency of 35 Hz and a travelling speed of 1 m/s, the “Portancemètre” device provides a value of the modulus for every meter (EPortancemètre). The overall travelling speed is measured with an ultrasonic Doppler radar that also measures the distance covered and therefore situates the results in a longitudinal profile. The “Portancemètre” device is applicable to compacted layers of soil or aggregates (natural or treated) with a strain modulus in the range of 30 to 300 MPa measured by the static plate test (600 mm diameter). The material thickness taken into account is about 0.60 m. Several tests have been performed with the “Portancemètre” on structures constructed with different materials (aggregates, soils and treated materials), showing a variation of the EV2 modulus determined via a SPLT test (600 mm diameter) from 20 to 500 MPa. In addition, a very good correlation between measures of stiffness with the “Portancemètre” and modulus values determined by dynaplaque 2 was obtained (Quibel 1999): E=5⋅k

(7)

where E is expressed in MPa and k in kN/mm. Other experimental results (Quibel 1999) use the “Portancemètre” device in applications of the bottom of cuttings, layers and upper parts of embankments and sub-grades, giving values of the elastic modulus in the range of 30 to 300 MPa. The assumed material thickness is about 0.60 m.

a) Figure 7. scheme.

b)

c)

The “Portancemètre” equipment: a) general aspect; b) vibrating wheel detail; c) function

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4

RESULTS

4.1 State parameters The analysis of the different test results shows an important heterogeneity in water content and density in each layer of the trial embankment, despite the soil bee previously to compaction subject to a process to make it homogeneous, at least in water content. However, the relation between these index parameters followed the normal trend (see Figure 8). 4.2 Correlation between EV modulus for several tests As previously referred, the goal was the establishment of correlations between Ev modulus for different tests with SPLT as reference test. To reach the objective, results obtained from tests done in the same spot or in the same grid (5 × 2 m2) were compared assuming homogeneity of density and moisture content per grid. For this reason, it is believed that correlations presented are independent from the energy level and from state parameters of each layer, and so, results from all layers were compared together ever results were available. The “Portancemètre” test results were grouped into homogeneous areas. A homogeneous area was defined by averaging the moduli from the “Portancemètre” in each 5 × 2 m2 grid into groups with intervals within the range of 10 MPa. For example, every grid with an average “Portancemètre” modulus value between 80 to 90 MPa belongs to the same homogeneous area. Spot tests that belong to a given homogeneous area were also grouped together. These groups of test results (“Portancemètre” and the other spot tests) were averaged. The correlation between the “Portancemètre” results and the other tests was established by comparing the respective average value for each homogeneous area. Figure 9 shows soil correlations close to unity observed between the “Portancemètre” modulus (EPortancemètre) and SPLT modulus (ELFWD), based on the AFNOR and DIN standards for an energy level corresponding to twelve passages of the roller. An acceptable correlation is verified for comparison with EV 2_AFNOR results (R2 = 0.56). However, EV 2_DIN results had a higher scatter, which leads to a poor correlation. This result demonstrates one advantage of using a plate with larger diameter. A reasonable correlation between EV 2_AFNOR and ELFWD was also noted, and a poor correlation between EV 2_AFNOR and ESSG modulus was observed (see Figure 10). The LFWD correlation corresponds to tests done in exactly the same spot, and SSG corresponds to tests done in the same grid. The presented results correspond to several energy levels. Despite the higher scatter of data, analysis of Figure 10 shows that the correlation between ELFWD and EV 2_AFNOR is close to unity, while the SSG modulus tend to be approximately 40% higher than SPLT modulus (EV 2_AFNOR) This correlation is important since it illustrates the advantages of using LFWD test on compaction control.

100 12 Passages 4 Passages

CR (%)

98 96 94 92 –4.5

–4

–3.5

–3

–2.5

–2

–1.5

–1

–0.5

0

Δw (%)

Figure 8. Variation of compaction degree (CR) with water content changes (Δw) for 4 and 12 passages of the vibratory roller on the 30 cm layer with wopt –2%.

1338

150

Prediction Limit 95%

125

EV2_DIN (average) [MPa]

EV2_AFNOR (average) [MPa]

150

y = 0.92x

100 75

0,30 m / wopt-2% 0,40 m / wopt 0,50 m / wopt-2%

50

Prediction Limit 95%

y = 0.94x

125 100 75

0,30 m / wopt-2% 0,40 m / wopt 0,50 m / wopt-2%

50 50

75

100 125 150 E"Portancemétre" (average) [Mpa]

50

a)

75 100 125 150 E"Portancemétre" (average) [Mpa]

b)

Figure 9. Comparison of elastic modulus EV obtained by “Portancemètre” and by interpretation of: a) AFNOR standard; b) DIN standard. 150

250

100

y = 0.98x

50

0,30 m / wopt-2% 0,40 m / wopt-2% 0,50 m / wopt-2% 0,40 m / wopt 0,40 m / wopt+2%

0 0

50 100 ELFWD [MPa]

150

a)

EV2_AFNOR [MPa]

EV2_AFNOR [MPa]

Prediction Limit 95%

0,30 m / wopt-2% 0,40 m / wopt-2% 0,50 m / wopt-2% 0,40 m / wopt 0,40 m / wopt+2%

200 150

y = 0.61x

100 50

Prediction Limit 95%

0 0

50

100 150 ESSG [MPa]

200

250

b)

Figure 10. Variation of the EV 2 modulus, for soil layers with different energy levels, obtained with SPLT (AFNOR standard) and with: a) LFWD; b) SSG.

Comparisons of soil moduli between “Portancemètre” (EPortancemètre) and LFWD (ELFWD) and also with SSG (ESSG) had data with a large scatter, and correlations obtained cannot be used in practice, and consequently are not presented. 5

CONCLUSIONS

The determination of the strain modulus with different kinds of tests was possible by establishing correlations and verifying equipment calibrations using static plate loading test (SPLT) as a reference. The correlation between static plate loading test based on the AFNOR NF P94-117-1 standard (EV 2_AFNOR) and “Portancemètre” (EPortancemètre) moduli was close to unity, which means that results given by these tests are approximately the same. These results validate the calibration method used and indicate the huge potential of this equipment for the continuous stiffness evaluation on earthwork platforms. A correlation close to unity between EV 2_AFNOR and the light falling weight deflectometer (LFWD) moduli was also observed, despite higher scatter of the data. This suggests that this kind of test (LFWD), which is easily managed, has practical utility although being a spot test. The relation of EV 2_AFNOR to the soil stiffness gauge (SSG) moduli yielded data with a large scatter, and the modulus was approximately 40% greater for the SSG test results. The results from this equipment should be treated with caution. 1339

ACKNOWLEDGEMENTS This work was financed by the Portuguese Foundation for Science and Technology (FCT) under the POCI/ECM/611/2004 project entitled “Soil-rail track interaction for high speed trains”. The authors wish to thank to FCT and also to the enterprises, whose collaboration was essential to carried out the work programme: REFER, MOTA-ENGIL and GEOCONTROLE, as well as, to Doctor Alain Quibel (CETE, France) for his contribution to plan the working programme. REFERENCES Alshibli, K.A., Abu-Farsakh, M., Seyman, E. (2005). Laboratory evaluation of the geogauge and Light Falling Weight Deflectometer as construction control tools. Journal of Materials in Civil Engineering, ASCE, September/October. pp. 560–569. ASTM D 2487. (2000). Classification of soils for engineering purposes (Unified Soil Classification System). American Society for Testing and Materials. Briaud, J.L. (2001). Introduction to soil moduli. Geotechnical News, Vol. 19.02 BiTech Publishers, Richmond, B.C., Canada. CBPC. (2000). Prima 100 FWD. Comparative measurements. Internal Report. Vejen. DIN 18134. (2001). Determining the deformation and strength characteristics of soil by plate loading test. Deutsches Institut für Normung. Edil, T., Sawangsurya, A. (2005). Earthwork quality control using soil stiffness. Proceedings of the 16th International Conference on Soil Mechanics and Geotechnical Engineering, Osaka, Japan. Fortunato, E.M.C. (2005). Renewal of railways platforms. Studies about bearing capacity. PhD Thesis, University of Oporto, Porto, Portugal (in portuguese). Livneh, M., Goldberg, Y. (2001). Quality assessment during road formation and foundation construction. Transportation Research Board 1755, Transportation Research Board, National Research Council, Washington D.C., USA, pp. 69–77. Loizos; A., Boukovalas, G., Karlaftis, A. (2003). Dynamic stiffness modulus for pavement subgrade evaluation. Journal of Transportation Engineering, ASCE, July/August, pp. 434–443. Nazzal, M.D. (2003). Field evaluation of in situ test technology for QC/QA during construction of pavement layers and embankments. Master Thesis, Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College, Louisiana, USA. NF P 94-117-1. (2000). Soils: investigation and testing—Formation level bearing capacity—Part 1: Plate test static deformation module (EV2). Association Française de Normalisation (in french). Quibel, A. (1999). New in situ devices to evaluate bearing capacity and compaction of unbound granular materials. Unbound Granular Materials. Laboratory Testing, In-situ Testing and Modelling. Gomes Correia A. (ed.), A.A. Balkema, Rotterdam, Netherlands, pp. 141–151. UIC. (1994). Earthworks and track bed construction for railway lines. Code UIC 719R, 2nd edition.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Railway bridge transition case study J.P. Hyslip HyGround Engineering, Williamsburg, MA, USA

D. Li Transportation Technology Center Inc., Pueblo, CO, USA

C.R. McDaniel Norfolk Southern Corporation, Roanoke, VA, USA

ABSTRACT: Railway track transitions at bridge approaches are often significant maintenance problems. Problems arise from settlement of the track at the bridge-approach along with stiffness and damping disparity between the fixed-structure and the approach. The substructure (ballast, subballast, subgrade and drainage) of the bridge-approach profoundly affects the settlement, stiffness and damping of the track at the transition location. To better characterize the condition and behavior of certain bridge approaches under heavy-axle load traffic and to also advance the state-of-the-art in bridge and track transition design and maintenance, two undergrade bridges were investigated on a major heavy axle load (coal and mixed freight) line in a mountainous territory in the eastern United States. The investigation consisted of standard test boring sampling, SPT and CPT testing along with track modulus and gage strength testing. This paper presents a case study of the investigation and analysis performed for the bridges at the project site. Also included is information on the past maintenance history and operating environment specific to the two bridges. Potential solutions are presented that are intended to arrest any settlement of the bridge approach and also achieve stiffness compatibility between the bridge and bridge-approach. 1

INTRODUCTION

Fundamentally, as with all track transitions, the bridge transition problem arises from the relatively abrupt change from one type of track structure to another. At railway track transitions loading and substructure conditions change significantly over very short distances. Transitions at bridge approaches, road grade-crossings and special trackwork can become significant maintenance problems. The AAR (Association of American Railroads) estimates that $200 million is spent annually on US railroads on track transition maintenance (Sasaoka et al., 2005). Other reports indicate that more than $110 million is spent on transition zones in Europe (ERRI, 1999) and more than $100 million is spent annually by the US highways industry in bridge transition problem areas (Briaud et al., 1997). The problem at a particular bridge can have any one or a combination of contributing factors. In general, rough track geometry at bridge transitions, which is a source of high stress in the track system, is often due to differential settlement between the track on and off of the bridge. The stiffness and damping disparity between the bridge-approach and the bridge also contribute to the problem. Dynamic simulation modeling of the bridge approach condition suggests that the combination of stiffness change and abrupt surface geometry change can generate dynamic loads of two to three times the static load at typical freight train speeds (Davis et al., 2003). The causes of bridge approach problems fall into one of three categories: 1) track stiffness change, 2) ballast settlement, and 3) geotechnical issues (Li & Davis, 2005). The track substructure greatly influences each of these. 1341

The substructure (ballast, subballast, subgrade and drainage) of the bridge-approach profoundly affects the settlement, stiffness and damping of the track at the transition location. The subgrade, i.e., the approach embankment fill, is affected by its original construction, poor materials, poor drainage, and its interaction with the bridge forces. The subgrade is also subject to changes induced by traffic, in particular, progressive settlement. The ballast settlement, especially immediately adjacent to the bridge abutment where proper tamping and compaction is difficult to achieve, is often the primary contributor to bridge transition problems. The ballast at bridge transitions is typically subject to increased levels of deterioration, flow, fouling, frost effects and poor drainage. 2

PERFORMANCE OF RAILWAY BRIDGE TRANSITION

Two undergrade bridges were investigated at Norfolk Southern’s East Mega Site in southern West Virginia in order to better understand railroad bridge approaches and to develop recommendations for mitigation of the problems. These bridges are located at milepost MP352.2 and MP352.8 on Norfolk Southern’s “N-Line” mainline between Norfolk, Virginia and Bluefield, West Virginia. The MP352.2 bridge is located in a 10-degree curve and on a 1.1% grade. The MP352.8 bridge is located in a 9.7-degree compound curve on a 0.9% grade. Track speed is 25 miles per hour (40 km/hr) as loaded trains move downhill from west to east with full dynamic brake and often with air brakes applied. Under heavy axle load train operation with an annual tonnage approximately 55 MGT (million gross tons), these open-deck bridges and their approaches experience track geometry degradation in vertical surface (profile) and/or horizontal alignment that has required frequent tamping and alignment work. The open-deck bridges also experience broken spikes and fasteners, plate cutting, and rail breaks (Li & Sasaoka, 2006). The rough geometry appears to be resulting in rail fatigue and breakage. To address misalignment and cross-level problems, bridge BR352.2 was modified from an open-deck structure to a ballast-deck in the fall of 2007. Track geometry data obtained from Norfolk Southern’s automated track geometry measurement vehicles were analyzed for the two East Megasite bridges for the time period between August 2005 and July 2008 in order to see how the track was performing in service. The roughness and deterioration of vertical surface and horizontal curvature data were analyzed. The raw track geometry data were quantified using Running Roughness (Ebersöhn & Selig, 1994), which is a mean square statistical calculation that provides a magnitude analysis of the geometry measurements. The maximum roughness values at each end of the undergrade bridges (i.e., at the east end and west end bridge approaches) were plotted versus time, as presented in Figure 1. The roughness of horizontal curvature was computed in a like manner. The relatively high variability and high rates of vertical surface deterioration for the west end of BR352.2 and the east end of BR352.8 indicates issues with substructure at the bridge approaches. There is an appreciable improvement in surface geometry at BR352.2 since

Figure 1.

Track geometry vertical surface roughness at Bridges BR352.2 and BR352.8.

1342

the ballast-deck was installed in August 2007. In other words, replacement of open deck to ballast deck for the bridge at BR352.2 led to consistent track structure from the bridge to the approaches, thus leading to consistent alignment performance. In addition, consistent track structure has improved track surface performance, as indicated in Figure 1. The track approaches used to require alignment and surface work on a monthly basis before the deck replacement. After the deck replacement, little track maintenance has been needed.

3

CONDITION OF RAILWAY BRIDGE TRANSITION

As part of the East Mega Site research program funded by the AAR and the Federal Railroad Administration (FRA), engineers from the Transportation Technology Center Inc. (TTCI) and Norfolk Southern conducted an investigation to determine the causes of the problems. The investigation included site inspection, vertical track modulus tests using TTCI’s Track Loading Vehicle (TLV), subgrade strength testing using TLV equipped Cone Penetrometer Test (CPT), gage restraint testing using FRA’s Gage Restraint Measurement System (GRMS) test vehicle, and standard test borings (penetration tests and sampling). Figure 2 shows test boring rig drilling at the east end of the bridge at MP352.2. All on-track work complied with FRA safety requirements. The results of the field testing were used to develop longitudinal profiles of the bridge approaches for BR352.2 and BR352.8. Figure 3 presents the generalized approach condition for the two bridges and is typical of many railway undergrade bridges on this part of Norfolk Southern’s system. The substructure condition of the bridge approaches contribute to the transition problem. Other factors affecting performance are differential support due to abutment skew and lateral issues including differences in lateral stiffness of the track on and off of the bridge as well as train forces from lateral curving and braking (Li & Sasaoka, 2006). The track settlement due to the deformation of the substructure under train traffic is dependent on the magnitude and number of repetitions of load, as well as the condition of the granular layer and subgrade layers. The ballast, the old roadbed fill and the subgrade all contribute to the top of rail settlement at the bridge approach. The ballast settlement,

Figure 2.

Test drilling at east end of bridge BR352.2.

1343

Figure 3.

Generalized approach for East Mega Site bridges.

especially after tamping is critical. Tamping of track is a maintenance technique used to correct geometry roughness by lifting and aligning the track and mechanically vibrating ballast stone under the tie to hold the track in its new position. Although tamping works to smooth the track geometry, it also loosens ballast from its compacted state (derived under traffic) and increases the settlement rate of the ballast until it settles back to a denser condition. The settlement after tamping results in a dip in the track reoccurring near to the bridge since the tamping maintenance process looses effectiveness near to the fixed structure. Models have been developed to quantify the cumulative top of rail settlement for any ballast and subgrade condition and for any mix of traffic loads (Selig & Hyslip, 2003; Davis et al., 2007). These models determine the track settlement as related to substructure properties and consider aptly the mix of wheel load as well as the number of repetitions of the 1344

load. The model of bridge approach transition settlement found the parameters the most significant are subgrade and ballast condition, ballast thickness, crosstie type and wheel load (Davis et al., 2007). 4

DISCUSSION OF SOLUTION ALTERNATIVES

For open-deck bridge structures, one way to mitigate the bridge approach is to convert the open-deck structure to a ballast-deck structure. This provides a more gradual transition and also allows for using conventional tamping maintenance to smooth the track geometry on and off the bridge. The conversion of BR352.2 from open-deck to ballast-deck occurred in September 2007 and cost approximately $500,000 for both tracks of the two-track mainline bridge. The geometry analysis results shown in Figure 1 indicate a significantly lower geometry roughness for BR352.2 after it was converted to a ballast-deck. However, it is possible to achieve similar improvement of the bridge transition through the mitigation of problems within the bridge approach, and at a potentially much lower cost. In most instances, the key to solving the bridge approach transition problem is to arrest the settlement of the approach and also increase the approach stiffness to make it more compatible with the non-settlement and support stiffness of the bridge. Other mitigation techniques have focused on reducing the track stiffness on the bridge by use of special pads and ties (Kerr & Bathurst, 2001; Sasaoka et al., 2005). This has some mitigating effect on the transition problem by lessening the stiffness difference between the bridge and approach, but does nothing for the settlement differential that develops between the bridge and approach embankment. Maintaining a compact and non-deforming ballast layer is key to limiting settlement at bridge approaches. Techniques such as chemical or cement-based grouting of the ballast matrix can reduce settlement of the ballast layer by essentially creating a stable mass of ‘glued’ ballast. Grouting can often also be used to raise the track to level position. Reinforcing the ballast layer with geogrid has been shown to reduce ballast layer settlement (Davis et al., 2008). Soil improvement and/or reinforcement techniques are available to improve the settlement and deformation characteristics of the subgrade soil, for situations where the low density (granular soil) or low consistency (fine-grained soil) of the deeper approach soil contribute to the top of rail settlement and track deflection under load. Techniques such as compaction grouting, rammed-aggregate piers (geopiers), soil mixing, jet-grouting, vibro-replacement, and pin piles are available soil improvement methods. Bridge approach slabs have been used as a semi-structural method to ease the transition from approach embankments to the fixed bridge structure (Moroney, 1991; Sharpe et al., 2002). Approach slabs require good connection at the abutment and good support conditions away from the abutment. Sharpe et al., (2002) present the design of a new transition zone that incorporates a sloping transition slab and a reinforced granular wedge as well as a ‘manual adjustment zone’ on the fixed structure that allows for over lifting and settlement of the ballast in the approach. Stoneblowing, which is another maintenance technique that competes for use with tamping, can be effective in eliminating the transition problem in locations where the settlement of the ballast is the primary source if differential settlement of the rail on and off the bridge. Stoneblowing has been shown to be a more durable geometry correction compared to conventional tamping (Chrismer, 1990; McMichael & McNaughton, 2003). 5

EAST MEGA SITE BRIDGE TRANSITION SOLUTIONS

In general, one of the primary contributors to the transition problem at most of the East Mega Site bridges appears to be differential settlement caused by ballast settlement, with some contribution also coming from progressive deformation from the loose/soft subgrade soil. The other contributor is the inconsistent lateral track strength (gage and panel shift 1345

strength), which is the main reason for misalignment growth for bridges located in curves. Another contributor to the problem are skewed abutments where there is a tie support transition zone where 4 to 5 ties adjacent to the abutment are partially supported on ballast and partially supported on abutment backwall, resulting in awkward track support. The desirable characteristics of the solution to the bridge transition problem: 1) effective, 2) low cost, 3) minimal disruption to traffic, and 4) track remain in-place. For this situation, the key to solving the bridge approach transition problem is to arrest the settlement of the approach and also increase the approach stiffness to make it more compatible with the non-settlement and support stiffness of the bridge. Other improvement that could supplement the mitigation of the approach settlement are: elastic fastening in approaches, elastic pads on bridges, reduced tie spacing in approaches, side ballast walls to provide lateral confinement of ballast (Li & Sasaoka, 2006). A ‘manual adjustment zone’ on the bridge could also be used to allow for over-lifting and settlement of the ballast in the approach. Possible treatments to improve the settlement and deformational characteristics of the approach substructure are chemical grouting of the ballast layer or reinforcing the ballast with tensile reinforcing grid. These techniques could stiffen the track support and also limit ballast settlement, and may have to be supplemented with the improvement of the deeper loose/soft soil with a soil improvement technique such as rammed-aggregate piers. Figure 4 presents a conceptual solution using chemical grout. For bridge transition improvement, the chemical grouting technique starts with the high-pressure injection of a very low viscosity chemical grout in the upper ballast (Zone 4 in Figure 4) that permeates and

Figure 4.

Chemical grouting solution option.

1346

Figure 5.

Geogrid reinforced ballast and geopier option.

fills the void spaces in ballast layer and stabilizes and stiffens the ballast by the inclusion of chemical grout in the ballast matrix. The track is then lifted to a smooth geometry through pressurized-grouting in Zone B and Zone C. The continuous mat of grouted ballast in Zone A not only provides a stable ballast layer, but also provides a continuous structural layer that can be lifted by pressure grouting from below. This chemical grouting technique has the benefit of using low viscosity grout that can readily permeate the ballast matrix, has very rapid ‘set-up’ time and is able to be done with the track in-place. Improvement of the deeper soil would be performed before the chemical grouting. Figure 5 presents another conceptual solution to mitigate substructure settlement and stiffness differential using geogrid reinforced ballast and supported with geopier soil improvement. Geopiers are rammed-aggregate columns constructed, as their name implies, by auguring a hole in the ground and then refilling the hole with aggregate in lifts (layers) that are rammed (compacted) into place. The ramming densifies the surrounding soil and the compact aggregate columns provide vertical support to loads above. The tensile reinforcement (geogrid) mat acts to transfer the track loads to the geopiers, and also reduces the ballast settlement by providing tensile reinforcement and confinement to the ballast layer. This technique requires the track to be removed. 6

CONCLUSIONS

Railway bridge transitions from the approach embankment to the fixed-structure often result in a high stress-state and a corresponding high maintenance demand. The investigation of two railway bridge approach transitions in heavy axle load territory has indicated a major cause of the transition problem to be the condition and performance of the track substructure. The bridge transition problem can be mitigated by changing the bridge structure from an 1347

‘open-deck’ to a ‘ballast-deck’, thereby lessening the support difference between bridge and approach, and also allowing for similar track maintenance to be performed across the entire structure. However, improving the approach substructure condition, rather than changing the bridge structure, may produce the same mitigating improvement at a lower cost. These bridges will continue to be studied as part of the East Mega Site heavy axle load program research program conducted by TTCI.

REFERENCES Briaud, J.L., James, R.W. and Hoffman, S.B. (1997). “Settlement of Bridge Approaches (The Bump at the End of the Bridge)”. NCHRP Synthesis of Highway Practice 234. Transportation Research Board, Washington, DC. Chrismer, S. (1990). “Track Surfacing with Conventional Tamping and Stone Injection.” Association of American Railroads, Report No. R-719, AAR Technical Center, Chicago. Davis, D., Otter, D., Li, D. and Singh, S. (2003). “Bridge Approach Performance in Revenue Service,” Railway Track & Structures, December, pp. 18–20. Davis, D., Anaya, R., Chrismer, S. and Smith, L. (2007). “Development of a Differential Settlement Model for Design and Maintenance of Track Transitions”. Technology Digest TD-07-002, Transportation Technology Center Inc., Pueblo, CO. March. Davis, D., Hyslip, J., Ho, C. and Terrill, V. (2008). “Evaluation of Reinforced Ballast for Foundations in Rail Joints and Special Trackwork,” Technology Digest TD-08-019, Transportation Technology Center Inc., Pueblo, CO. May. Ebersöhn, W. and Selig, E.T. (1994). “Use of Track Geometry Measurements for Maintenance Planning.” Transportation Research Record No. 1470, Transportation Research Board, Washington, DC. ERRI (European Rail Research Institute), D230.1 Specialists’ Committee (1999). “State of the Art Report—Bridge ends Embankment Structure Transition”. ERRI Project No. D230.1, Utrecht, Netherlands. November. Kerr, A. and Bathurst, L. (2001). “A Method for Upgrading the Performance and Track Transitions for High-Speed Service”. Report No. DOT/FRA/RDV-02/05, Federal Railroad Administration, US Department of Transportation, Washington, DC. September. Li, D. and Davis, D. (2005). “Transition of Railroad Bridge Approaches.” Journal of Geotechnical and Geoenvironmental Engineering, ASCE, November. Li, D. and Sasaoka, C. (2006). “Problems and Potential Remedies: Open Deck Steel Bridges and Their Approaches at Eastern Mega Site (NS).” Internal TTCI document. March 27. McMichael, P. and McNaughton, A. (2003). “The Stoneblower—Delivering the Promise: Development, Testing and Operation of a New Track Maintenance System.” Transportation Research Board Annual Meeting, Washington, DC, January. Moroney, B.E. (1991). “A Study of Railroad Track Transition Points and Problems”. Master of Civil Engineering Thesis, University of Delaware. December. Sasaoka, C., Davis, D., Koch, K., Reiff, R. and GeMeiner, W. (2005). “Implementing Track Transition Solutions”. Technology Digest TD-05-001, Transportation Technology Center Inc., Pueblo, CO. January. Selig, E.T. and Hyslip, J.P. (2003). “Effects of Heavy Axle Loads on Track Substructure,” Conference Proceedings, International Heavy Haul Association Specialty Conference, Dallas, TX, May. Sharpe, P, Armitage, R., Heggie, W. and Rogers, A. (2002). “Innovative Design of Transition Zones.” Conference Proceedings Railway Engineering 2002, ECS Publications, London.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Comparison of coal dust fouled railroad ballast behavior— granite vs. limestone W. Dombrow, H. Huang & E. Tutumluer Department of Civil & Environmental Engineering, University of Illinois, Urbana, Illinois, USA

ABSTRACT: Fouling refers to the condition of railroad ballast when voids in this unbound aggregate layer are filled with fine materials or fouling agents commonly in the form of ballast aggregate breakdown, outside contamination such as coal dust from coal trains, or from subgrade soil intrusion. Effects of coal dust on shear strength of different ballast aggregates were studied through the use of a large shear box device. The strength properties of both granite and limestone ballast samples were determined when coal dust was added to clean ballast samples at various percentages by weight of ballast under both dry and wet conditions. When the coal dust fouling percentage increased, the ballast shear strength generally decreased. Wet fouling was found to exacerbate this trend. However, coal dust had more detrimental impact on granite ballast strength when compared to limestone ballast. This could be caused by limestone’s higher crushing tendency and/or possibly any differences in void structures since gradation properties of the granite and limestone samples varied. 1

INTRODUCTION

Major derailments occurred in 2005 in the joint coal line in Powder River Basin (PRB) of Wyoming, the largest source of incremental low-sulfur coal supplies in the U.S., which threatened to interrupt the supply of coal to power plants. In the derailment locations, the ballast was observed to be heavily fouled by coal dust. The derailments were suspected to be due to coal dust fouling, where coal dust spilled from loaded cars on to the ballast and accumulated moisture, allegedly resulting in the loss of strength of the track. Early research studies reported that around 70% of the fouling materials were from ballast breakdown (Selig et al., 1988; Collingwood, 1988; and Selig et al., 1992). Railroad company internal studies also noted that almost all fouling fines in the railroad track were commonly from aggregate breakdown (CN, 1987). According to Selig and Waters (1994), ballast breakdown on the average accounts for up to 76% of the ballast fouling followed by 13% infiltration from subballast, 7% infiltration from ballast surface, 3% subgrade intrusion, and 1% due to tie wear. However, coal dust as a fouling agent has been less touched. In terms of the stability and load carrying ability of the fouled ballast layer, three volumetric phases can be identified for the different conditions of fine materials filling the void space (see Figure 1). Phase I shows a clean or very slightly fouled ballast sample with almost all aggregates establishing contact with each other at the aggregate surface to sufficiently carry the load (see Figure 1a). As shown in Figure 1b, phase II will have the voids in between contacting aggregates filled with enough amount of fine particles that could significantly reduce the strength, however, still maintaining aggregate to aggregate contact. Whereas, in a phase III fouled ballast condition, due to the excessive amount of fine particles, aggregate to aggregate contacts are mostly eliminated and the aggregate particle movements are then only constrained by the fine particles filling the matrix or voids between the particles (see Figure 1c). Traditional methods specifically used to assess track ballast condition only deal with checking visually for evidence of fouling, pumping and water accumulation (ponding) at ditches and shoulders. Additionally, ballast sampling and testing for fouling through laboratory sieve analyses generally provide some insight into the compositions of the larger aggregate 1349

(a) Clean ballast (Phase I)

Figure 1.

(b) Partially fouled ballast (Phase II) (c) Heavily fouled ballast (phase III)

Critical ballast fouling phases.

particles and the amount of fines. Nonetheless, for a better evaluation of the serviceability and proper functioning of the existing layer, ballast strength needs to be characterized for the effects of coal dust fouling using different ballast aggregate types with different gradations and properties. This paper presents findings from a laboratory-testing program recently conducted at the University of Illinois with the objective to study effects of coal dust fouling on different types of ballast aggregate. Using large direct shear (shear box) tests, strength and deformation characteristics of both granite and limestone type ballast materials were investigated for clean ballast and ballast fouled by coal dust at various stages under both dry and wet conditions. The shear strength properties, cohesion intercept and friction angle are linked to field ballast fouling levels to better assess the impact of coal dust fouling on track instability and ultimately loss of track support leading to derailments. 2

CLEAN AND FOULED BALLAST STRENGTH BEHAVIOR

2.1 Materials tested The ballast materials tested were granite aggregate obtained near Cheyenne, Wyoming and limestone aggregate obtained near Paducah, Kentucky. The granite aggregate is commonly used in the PRB joint line railroad track structures as the ballast layer. Table 1 lists size properties of the granite and limestone ballast materials tested. Figure 2 shows the grain size distributions of the granite and limestone samples. Table 2 lists engineering properties of coal dust (Tutumluer et al., 2008). Figure 3 shows the size distribution of coal dust collected from the PRB Orin line milepost 62.4 and tested in this study. 2.2 Testing apparatus Direct shear strength tests were performed on the reconstituted clean and fouled aggregate samples. Figure 4 shows the large shear box equipment used for testing at the University of Illinois. The test device is a square box with side dimensions of 305 mm (12 in.) and a specimen height of 203 mm (8 in.). It has a total 102 mm (4-in.) travel of the bottom which is a 152-mm (6-in.) high component, large enough for ballast testing purposes to record peak shear stresses. The vertical (normal direction) and horizontal load cells are capable of applying and recording up to 50-kN load magnitudes. The device controls and the data collection are managed through an automated data acquisition system controlled by the operator through a build-in display and the test data are saved on to a personal computer. 2.3 Sample preparation Clean ballast was poured into the lower box in two lifts. Each lift was compacted until no noticeable movement of particles was observed with a vibratory compactor on top of a 1350

Table 1.

Specific gravities and grain size properties of the granite and limestone ballast materials.

Granite Limestone

Specific gravity

Dmax

Dmin

D50

2.62 2.68

63.5 mm (2.5 in.) 50.8 mm (2 in.)

25.4 mm (1 in.) 12.7 mm (0.5 in.)

35 mm (1.38 in.) 24 mm (0.95 in.)

Ballast Gradations

100.0

Percentage passing (%)

90.0 80.0

Granite

70.0

Limestone

60.0 50.0 40.0 30.0 20.0 10.0 0.0 100

10

1

Sieve Opening (mm) Figure 2. Table 2.

Coal dust 1

Gradations of the granite and limestone ballast aggregate materials. Engineering properties of the selected fouling materials.

Specific gravity

Liquid limit (%)

Plastic limit (%)

Maximum Optimum moisture dry density1 content or OMC1 (%) (kg/m3)

1.28

91

50

35

874

Passing 0.075 mm or No. 200 sieve (%) 24

Obtained from standard Proctor ASTM D 698 test procedure.

Percentage passing by weight (%)

100

Coal Dust Gradation

Coal Dust

80 60 40 20 0 1.00E+01

Figure 3.

1.00E+00 Sieve Size (mm)

Grain size distribution of the coal dust tested.

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1.00E-01

1.00E-02

Figure 4. Table 3.

Direct shear strength test equipment at the University of Illinois. Weight and volume relationships for the limestone and granite samples.

SI units

Limestone

Granite

US Customary units

Limestone

Granite

Specific gravity Volume, m3 Total weight, kg Vol. of solids, m3 Vol. of air, m3 Porosity Coal weight fully fouled, kg Porosity after fully fouled Foulant by weight

2.68 9.21772E-06 25.65 5.5716E-06 3.63793E-06 39.52%

2.62 9.21772E-06 24.3 5.40773E-06 3.8018E-06 41.28%

Specific gravity Volume, in.3 Total weight, lbs Vol. of solids, in.3 Vol. of air, in.3 Porosity Coal weight fully fouled, lbs Porosity after fully fouled Foulant by weight

2.68 0.5625 57 0.34 0.222 39.52%

2.62 0.5625 54 0.33 0.232 41.28%

12.2

13.5

12.36% 21.40%

11.23% 25.00%

5.49

6.075

12.36% 21.40%

11.23% 25.00%

flat load bearing plate to ensure even compaction. The total weight of aggregate used was recorded. By using the weight of aggregate, specific gravity, and the known volume of the box, the voids (porosity) was reported. All subsequent tests of the same material targeted the optimal porosity. The achieved voids for each material were essentially the same, 41% for granite and 39% for limestone. Table 3 lists detailed weight and volume relationships computed for the limestone and granite aggregate samples. For samples containing a fouling agent, the prescribed weight of coal dust was added in 2 to 3 lifts with vibration applied to simulate the “shakedown” effect. In this procedure, the fouling accumulates from the bottom of the sample up until fully fouled condition occurs. Fully fouled condition is assumed when all voids were filled and no more coal dust could be forced into the granular assembly in the box. If the fouling condition tested was wet (in this case “wet” refers to optimum moisture content of the coal dust), a prescribed weight of water was sprinkled over the specimen after each application of fouling material. The coal would soak up the water and produce uniform moisture content throughout the sample. Finally, the upper ring (76 mm high) was placed on top of lower box and aligned with sides and back edge of the lower box. A single lift was then placed and compacted in the upper ring. Figure 5 shows the placement and compaction of clean ballast in the lower box. Obtaining the fouling material and introducing it into the clean sample is depicted in Figure 6. Before testing, the box and ring assembly were placed into the shearing apparatus. The lower box was clamped in place and the load bearing plate was placed on ballast but inside upper ring. Air-bladder was placed on bearing-plate, air supply opened and normal pressure 1352

Figure 5.

Stages of ballast compaction.

Figure 6.

Addition of coal dust and moisture as source of fouling.

set using an in-line pressure regulator. The load cell recording applied shear force was adjusted directly against the upper ring. The Labview data logger software was initiated to record normal and shear forces during testing. The loading speed was set to an input shear rate of 12.2 mm/min. (0.48 in./min.), which is approximately 4% strain per minute and the tests were conducted until the shear force output peaked or 15% strain has occurred.

3

TEST RESULTS

The ballast samples were sheared horizontally in the shear box under target normal pressures of 172, 241, 310 kPa (25, 35, 45 psi), typical ballast layer confining pressures, so that the relationships between the normal stress and shear stress could be established. The maximum shear stress at failure under each applied normal pressure was recorded from each test. This maximum shear stress typically occurred when approximately 10% shear strain was reached during testing. Figure 7 shows the peak shear strengths plotted against applied normal stresses for clean granite sample and samples fouled with different percentages of coal and moisture contents (OMC is optimum moisture content). As the applied normal stresses increased, the maximum shear stresses at failure or simply shear strength τmax also increased primarily influenced by the increase in ballast fouling percentage and the moisture condition of the coal dust, i.e., dry or wet at optimum moisture content = 35%. As expected, the highest shear strength values were obtained from the clean ballast at all applied normal stress levels (see Table 4). When ballast samples were fouled, the shear strengths typically decreased. For all the samples tested, wet coal dust fouling resulted in lower shear strengths when compared to those obtained from dry coal dust fouling. The lowest shear strength values were recorded for the fouling level of 25% by weight (fully fouled) of ballast when wet coal dust was at 35% moisture content. Figure 8 shows the peak shear strengths plotted against applied normal stresses for clean limestone sample and samples fouled with different percentages of coal and moisture contents. Although, it can still be observed that the lowest strength value occurred at the fouling level of 21.4% by weight (fully fouled) when the coal dust was at its optimum moisture content, no clear trend can be observed in strength changing with the increase in coal dust content (see Table 4). 1353

500 Clean Granite 5% Coal Dry 15% Coal Dry

Shear Stress (kPa)

400

25% Coal Dry 5% Coal OMC 15% Coal OMC

300

25% Coal OMC

200

100 100

200

300 Normal Stress (kPa)

400

500

Figure 7. Direct shear test results of the granite ballast samples fouled by coal dust at dry and optimum moisture content (OMC) conditions.

Table 4. Cohesion intercept and internal friction angles based on Mohr-Coulomb shear strength envelopes for each fouling condition. Internal friction angle Condition Granite Dry

Fouling

Cohesion intercept (kPa)

ϕ (rad.)

ϕ (deg.)

Clean 5 15 25

105.16 96.31 92.87 75.21

1.02 0.991 0.773 0.688

45.6 43.9 36.2 36.6

Wet (OMC)

5 15 25

61.35 76.73 35.20

0.963 0.731 0.744

44.7 37.7 34.5

OMC + 5%

5 15 25

125.58 22.22 82.32

0.658 0.894 0.569

33.3 41.8 29.7

Clean 5 15 21

62.24 39.74 103.85 86.87

0.882 0.962 0.649 0.712

41.4 43.9 33.0 35.5

Limestone Dry

Wet (OMC)

5 15 21

30.15 73.55 67.76

0.995 0.921 0.739

44.9 42.6 36.5

OMC + 5%

5 15 21

24.15 51.82 40.43

1.034 0.953 0.863

46.0 43.6 40.8

1354

500

Clean Limestone

Shear Stress (kPa)

400

5% Coal Dry 15% Coal Dry 21% Coal Dry

300

5% Coal OMC 15% Coal OMC 21% Coal OMC

200

100

Figure 8.

200

300 Normal Stress (kPa)

400

500

Direct shear test results of the limestone ballast samples fouled by coal dust.

The upper and lower bound of shear strength envelopes for both aggregate types are shown in Figure 9. The range clearly represents the change in shear strength with various conditions tested. Granite produced a larger variation in strength from clean to fouled specimens when compared to limestone. The shear strength envelopes for all of the limestone tests with varying degrees of coal dust fouling and moisture contents fell within a narrow band. This result indicates that for the given gradation the limestone ballast did not lose any stability due to coal dust fouling. The larger band given for the granite makes granite ballast samples more susceptible to decreases in strength and stability when fouled with wet coal dust. Several possible explanations can be offered for the differences in the performance under fouling for the granite and limestone ballast samples which can be attribute to volumetrics and packing orders. The granite sample had more void space to be filled with the fouling material coal dust when compared to the limestone (see Table 4). In addition, the granite ballast sample was continuously graded (see Figure 2) which implies that most of the individual granite particles are members of the main aggregate-interlock structure supplying shear strength. Some weak spots, due to the coal dust fouling, could cause the decrease in strength of the whole structure. Whereas the limestone ballast was more or less “gap” graded, which means coarse particles would form the main load carrying structure and the finer particles would most likely fill the voids in between the large particles. When this sample was fouled, the contacts of the smaller particles were separated, but the large particles remained in contact and still provided a strong skeleton. The shear strength then was not compromised since the large particle contacts “bridged” the missing contacts, and the overall strength was somewhat maintained. Another possibility is the mechanism for which the limestone samples fail. In general terms, limestone is much weaker than granite and thus is more susceptible to crushing. If the limestone particles in the shearing plane crushed before sliding occurred, the addition of fouling material would show no effect (under the assumption coal dust fouling reduces particle friction and the reduction of shear strength is attributed to this weakness). Table 4 lists for direct comparison purposes the shear strength values computed under normal stress levels of 200 and 300 kPa (29.0 and 43.5 psi), i.e. typical railroad ballast stress conditions experienced by the granite and limestone ballasts in the field. Most of the trends already mentioned and their effects can be clearly seen by comparing the computed shear strength values. It is worth noting that the “cohesion” term is obtained from the interception of the shear strength line which does not imply a cohesive material. Increasing the moisture content from OMC to OMC + 5% exacerbates the fouling effect. In the case of granite,

1355

500 450

Granite Limestone

Shear Stress (kPa)

400 350 300 250 200 150 100 50 0 0

100

200

300

400

Normal Stress (kPa) Figure 9. Mohr-Coulomb shear strength envelopes indicating the maximum and minimum strength limits to establish the ranges for the limestone and granite ballast samples.

5% more moisture content further reduces the friction angle; whereas in the case of limestone, it affects the strength by decreasing the apparent cohesion. 4

SUMMARY AND CONCLUSIONS

Large-sized shear box direct shear laboratory tests were conducted at the University of Illinois on ballast samples obtained from the Powder River Basin (PRB) joint line in Wyoming to measure strength and deformation characteristics of both granite and limestone ballast aggregates fouled with coal dust. Coal dust was mixed with clean aggregates for achieving different fouling levels under dry and wet, mostly optimum moisture content (OMC), conditions. The coal dust material was spread on the clean aggregate specimen and vibrated on top to achieve its percolation into the voids in an effort to realistically simulate coal dust falling off the trains into the ballast layer in the field. From the direct shear tests, the highest shear strength values were obtained from the clean ballast samples at all applied normal stress levels, which were representative of typical stress states experienced in the ballast layer under train loading. For the granite sample, when ballast samples were fouled, the shear strengths always decreased. This was mostly apparent with lower friction angles and cohesion intercepts. Wet fouling resulted in much lower ballast shear strengths when compared to those obtained from dry coal dust fouling. Limestone samples did not show a drastic decrease in shear strength similar to the granite samples when fouled with coal dust even with the fouling agent being dry or wet. This was possibly due to the different gradation of the limestone and granite aggregates with limestone having less void space that the granite material. In addition, limestone had a higher tendency to crush during strength testing when compared to granite. It is advisable to conduct future research to further investigate the effects of gradation and internal void structure on the susceptibility to loss of shear strength through coal dust fouling.

1356

ACKNOWLEDGEMENTS The authors would like to thank Burlington Northern Santa Fe (BNSF) Railroad Company for providing the financial support needed to carry out this research study. The authors would also like to thank Mr. Henry M. Lees with BNSF for sharing his valuable knowledge and experience on the research topic and for providing help and support with obtaining materials. The contents of this paper reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. This paper does not constitute a standard, specification, or regulation. REFERENCES CN (Canadian National) Rail. 1987 Ballast Performance in Concrete Tie Track. Prairie Region. Edmonton. CN, Geotechnical Service. Internal Report. Collingwood, B.I. 1988. An Investigation of the Cause of Railroad Ballast Fouling. Master of Science Degree Project Report No. AAR88-350P. University of Massachusetts. Selig, E.T., Collingwood, B.I. & S.W. Field. 1988. Causes of Fouling in Track. AREA Bulletin 717. Selig, E.T., DelloRusso, V. & K.J. Laine. 1992. Sources and Causes of Ballast Fouling. Report No. R-805. Association of American Railroad (AAR), Technical Center, Chicago. Selig, E.T. & J.M. Waters. 1994. Track Geotechnology and Substructure Management. London, Thomas Telford Publications. Tutumluer, E., Dombrow, W. & H. Huang. 2008. Laboratory Characterization of Coal Dust Fouled Ballast. AREMA 2008 Annual Conference and Exhibition, Salt Lake City, UT.

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Full-scale testing

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Validation of NCAT structural test track experiment using INDOT APT facility E. Levenberg North Central Superpave Center, Purdue University, West Lafayette, Indiana, USA

ABSTRACT: The National Center for Asphalt Technology (NCAT) operates a full-scale test road for studying the response and performance of asphalt pavements. During the 2003–2005 testing phase, NCAT instrumented eight of their test sections with stress and strain gauges. Two of the test sections were later replicated, along with embedded instrumentation, for subsequent testing in the accelerated pavement testing (APT) facility operated by the Indiana Department of Transportation. The availability of similarly constructed and instrumented pavement systems loaded in different conditions offered a unique opportunity to develop and test the prediction ability of pavement models. Exploring this aspect is the topic of the present paper, in which an attempt is described to use the APT experiment and forecast resilient responses obtained at NCAT that were generated under completely different loading and environmental conditions. The modeling and analysis approach are outlined and computations are compared with NCAT measurements. 1

INTRODUCTION

The National Center for Asphalt Technology (NCAT) operates a full-scale test facility for studying the response and performance of asphalt roads by way of applying accelerated truck traffic to different (adjoining) pavement structures. During the 2003–2005 testing phase, NCAT carried out a ‘structural study’ by embedding instrumentation in eight of their test sections, denoted as N1 to N8 (Timm et al. 2004, 2006, Timm & Priest 2006). In 2004 Purdue University and the Indiana Department of Transportation (INDOT) engaged in a research project that was closely related to the ‘structural study’ experiment; in this project the two NCAT sections N1 and N2 were replicated along with embedded instrumentation (denoted as n1 and n2 respectively) in the INDOT accelerated pavement testing (APT) facility for subsequent testing. The overall objective of the Purdue study was to develop an analysis approach by which pavement behavior in the APT, obtained under a limited set of loading and environmental conditions, could be used to reliably forecast the behavior of a similarly constructed pavement in the field serving different loading and environmental conditions. Therefore, the instrumented NCAT sections portrayed the role of a ‘field’ project and their replication in the APT served as means of validating any proposed approach. Due to scarcity of adequate performance data (i.e., rutting and cracking) from both experiments, only responses (i.e., stresses, strains and deflections) were considered. Additionally, the type of embedded instrumentation was only suited for monitoring transient ‘dynamic’ pavement reactions; because of this, only resilient (recoverable) responses were addressed. Subsequently, the analyses focused on the early stages of both experiments when the pavements were in pristine condition. The preset paper exposes the simplest and most basic analysis scheme proposed in the Purdue study, based on layered elastic theory (LET) with isotropic material properties. Due to space limitations only the n1-N1 sections are addressed. The more advanced approaches (Levenberg, 2008), which included material anisotropy and viscoelasticity, will be the topic of forthcoming papers. 1361

2

THE APT EXPERIMENT

2.1 APT facility The INDOT/Purdue APT facility was fabricated in the early 1990’s (White et al. 1990, Galal et al. 1998). The facility is housed in a 186 sq. m (∼2,000 sq. ft) hangar located near INDOT’s Research Division in West Lafayette. The testing area includes a pit embedded in a concrete floor which is 1.83 m (6 ft) deep and shaped as a square with 6.1 m (20 ft) long sides. Prototype scale pavements are constructed inside this pit. Overhanging the test pit from the ceiling is a radiant heating system capable of increasing the air temperature in the test area up to 60ºC (140ºF); the facility also has some cooling capabilities using an air-conditioning unit. The APT loading system is mounted on a large steel frame with beams spanning across and bridging the test pit. The frame itself is fixed on each side to steel rails embedded in the concrete floor; the fixtures can be loosened so the frame can be moved and positioned above any line of choice. Figure 1 shows a picture of the APT loading system (with an empty test pit). The loading system is capable of producing a downward force of up to 9,080 kg (20,000 lb) applied to the pavement surface through a half-axle wheel assembly. Two wheel assembly types are available: dual/conventional or single wide-base; either type is mounted to a carriage capable of traveling on the steel beams, traversing the test pit. The carriage is designed to accelerate from a static startup position to a speed of 8 km/h (5 mph) within the first 1.52 m (5 ft) of the test pit; the carriage speed is then maintained constant, at 8 km/h (5 mph), for the next 3.66 m (12 ft); finally, the speed is reduced to a complete stop within the last 0.91 m (3 ft) of the test pit. Depending on the desired mode of application, the wheel assembly can be raised from the ground and returned to the startup position for another loading cycle, resulting in unidirectional loading mode. Alternatively, the pavement can be loaded while the carriage travels back to the startup position, resulting in a bidirectional loading mode. Moreover, passes in the APT can be applied repeatedly in the same wheel path or with wander. In this study the test pit was split into two test lanes (n1 and n2), each 3.05 m (10 ft) wide (and 6.1 m long). The temperature in the testing area was set and maintained throughout the experiment at 15.5ºC (60ºF). Passes were applied without wander in unidirectional mode via the dualwheel assembly loaded to 6,810 kg (15,000 lb); tires were inflated to 0.70 MPa (100 psi).

Figure 1.

Picture of empty test pit and APT loading system.

1362

2.2 Pavement system The n1 pavement structure (or equivalently N1) was comprised of 127 mm (5 in.) of hot mix asphalt (HMA) overlaying 152.4 mm (6 in.) of crushed granite aggregate base course; placed on top of an A-4(0) soil serving as subgrade. The HMA course was made of two mix types and constructed in three lifts. The surface lift was made of Mix 1 and was 25.4 mm (1 in.) thick; the intermediate and bottom lifts, each 50.8 mm (2 in.) thick, were both made of Mix 2. Both mixes were densely graded, designed according to the Superpave methodology (80 gyrations) with a PG 76-22 binder (SBS modified); they mainly differed by the nominal maximum aggregate size which was 9.5 mm (3/8 in.) in Mix 1 and 19 mm (3/4 in.) in Mix 2. The aggregate base course was compacted in a single 152.4 mm (6 in.) lift and the subgrade soil was compacted in several lifts, each up to 152 mm (6 in.) thick. Compared to the NCAT experiment, compaction levels in the APT were slightly lower. Detailed and quantitative comparison between the APT and NCAT sections can be found in Llenín & Pellinen (2004) and in Levenberg (2008). 2.3 Embedded instrumentation A total of 12 gauges were used in section n1, consisting of four pressure cells and eight strain gauges. Pressure cells were Model 3500 manufactured by Geokon; strain gauges were Model ASG-152 manufactured by CTL Group. Two out of the four pressure cells measured vertical stresses on top of the base course (or bottom of the HMA); installed at a depth of 127 mm (5 in.) from the surface along the centerline of the test lane. The two additional pressure cells measured vertical stresses on top of the subgrade (or bottom of the base course); installed at a depth of 279.4 mm (11 in.) from the surface, also along the test lane centerline. All eight strain gauges were attached to the bottom of the HMA, at a depth of 127 mm (5 in.) from the surface. Four out of the eight gauges were installed along the centerline of the test lane, two of which measured horizontal strains in the loading direction while the other two measured horizontal strains in the transverse direction. The additional four strain gages targeted similar responses but were positioned along a parallel line that was offset by 0.61 m (2 ft) relative to the centerline. As the APT carriage traversed the n1 lane, measurements from these gauges were sampled and recorded at a rate of 100 Hz. The reader is referred to Llenín & Pellinen (2004) and to Timm et al. (2004) for more details about the instrumentation plan and placement. The collected response data is presented and discussed in Levenberg et al. (2008) and in Levenberg (2008). 2.4 Complex modulus testing Complex modulus tests were separately performed on specimens made of the two HMA mixes 1 and 2, executed in accordance with the provisional method described by NCHRP (2002). For this purpose materials were sampled in loose state from the delivery trucks at NCAT, transported to Purdue laboratories and compacted using gyratory equipment (after reheating) to an air void content of about 7%. The raw test results (i.e., dynamic moduli and phase angles) can be found in Barde & Cardone (2004), Timm & Priest (2006) and also in Levenberg (2008). The dynamic modulus of Mix 2 was found to be consistently higher than that of Mix 1 by about 25 to 50% over the entire range of temperatures and frequencies tested. Phase angles were also higher in Mix 2 compared to Mix 1 but only under low temperature conditions (4.4ºC or less); under higher temperatures the trend was reversed. 3

ANALYSIS

3.1 Pavement model In pursuance of relative simplicity a basic mechanistic model was initially applied to represent the pavement system, founded on LET with isotropic material properties. The APT experiment was analyzed first, with the n1 section modeled as a four layered system. The three 1363

HMA lifts were treated as one (top) layer, 127 mm (5 in.) thick with an assumed Poisson’s ratio of v1 = 0.30. The second layer from the top represented the crushed aggregate base course, with a thickness of 152.4 mm (6 in.) and v2 = 0.35 (assumed). Because no instrumentation was embedded in the subgrade (only on top), there was no available data to support its sub-layering. Hence, the subgrade was treated as one layer (third layer from the top) having a total thickness of 1.55 m (61 in.) and v3 = 0.40 (assumed). The fourth and final layer, with semi-infinite thickness, represented the concrete floor of the test pit. The elastic properties of this layer were taken as: E4 = 27,560 MPa (4,000,000 psi) and v4 = 0.20. 3.2 Calibration to APT Conditions The recoverable response to load of HMA mixtures is known to be anisotropic and nonlinear viscoelastic (Shields et al. 1998, Levenberg 2006, Uzan & Levenberg 2007). The resilient response of unbound layers is nonlinear elastic, stress-state sensitive (Uzan 1985, 1992) and also anisotropic (e.g., Tutumluer & Thompson 1997). Given that isotropic LET was used for the analysis, systematic errors were expected mainly because of noncompliance with actual material behavior. In an effort to minimize these errors, model parameters (i.e., elastic moduli) were derived through a process of backcalculation using the entire time history of all embedded gauge readings collected during one pass of the APT carriage. The inverse analysis was performed for the pavement in the initial phases of the APT experiment, after 5,000 passes out of the 90,000 passes that were applied overall (this choice was somewhat random). For this purpose the dual-wheel loading was represented by two circular areas, each 203 mm (8 in.) in diameter, transferring uniform vertical stresses of 1.03 MPa (150 psi) in magnitude to the pavement surface; the spacing between the load centers was 343 mm (13.5 inches). The moving APT carriage was simulated using the quasi-static approach in which dynamic (inertial) effects are disregarded. By manipulating the elastic moduli of the HMA, base and subgrade (simultaneously) using a nonlinear optimization algorithm (Fylstra et al. 1998), model generated stress and strain histories were forced to match the gauge measurements as best as possible. The resulting pavement properties are presented in Table 1. More details on the inverse analysis can be found in Levenberg et al. (2008) and also in Levenberg (2008). 3.3 Enhancing the APT model The calibrated APT model (i.e., Table 1) may be considered suitable for forward analysis only when the loading and environmental conditions are similar to those prevailing in the APT experiment. When other conditions need to be considered, the differences/changes in material properties, axle configuration, axle loads and axle speeds—should all be taken into account. It is straightforward to apply the layered model with different axle configurations and different axle loads. Also, axle speed is not an issue from a computational standpoint because the quasi-static approach is applied for simulating the moving load. The changes in material properties, however, must be accounted for exogenously; in particular, the HMA stiffness, which is sensitive to both loading speed and temperature. The unbound material properties, although stress-state sensitive, are assumed to be unaffected by the aforementioned changes. This may be justified, at least as a first order approximation, considering that there are preexisting effective confining stresses in these materials (of unknown magnitudes) including: vertical Table 1.

Backcalculated layer moduli in the APT for pass #5,000.

#

Layer

Thickness, mm (in.)

Poisson’s ratio [–]

Backcalculated moduli, MPa (psi)

1 2 3 4

HMA Base Subgrade Concrete

127 (5) 152 (6) 1,549 (61) Semi-infinite

0.30 0.35 0.40 0.20

2,412 (350,000) 165 (24,000) 83 (12,000) 27,560 (4,000,000)

1364

stresses due to self weight, locked-in horizontal stresses from the compaction process, and confining stresses due to negative pore pressures. The methodology proposed for enhancing the APT model called for manipulating the HMA modulus to reflect different loading speeds and temperatures relative to the APT case. This was accomplished after additional analysis of the complex modulus results. As a first step the individual dynamic modulus and phase angle data (for each of the two mixes) were united into a new dataset representative of a ‘combined’ HMA layer that is 127 mm (5 in.) thick. The following equations were suggested for this purpose (Levenberg 2008): 3

E1com

⎡h ⋅ 3 E + h ⋅ 3 E ⎤ 1 1,1 2 1,2 ⎥ =⎢ ⎢ ⎥ h1 + h2 ⎦ ⎣

E2com

⎡h ⋅ 3 E + h ⋅ 3 E ⎤ 1 2,1 2 2,2 ⎥ =⎢ ⎢ ⎥ h1 + h2 ⎣ ⎦

(1)

3

(2)

* Ecom = ( E1com )2 + ( E2com )2

(3)

⎛ E com ⎞ φcom = arctan ⎜⎜ 2com ⎟⎟ ⎝ E1 ⎠

(4)

in which h1 = thickness of Mix 1 in the pavement structure (i.e. 25.4 mm or 1 in.); h2 = thickness of Mix 2 in the pavement structure (i.e., 101.6 mm or 4 in.); E1,i = storage modulus of * = combined dynamic modulus; and Mix i (i = 1,2); E2,i loss modulus of Mix i (i = 1,2); Ecom φcom = combined phase angle. Although not explicitly shown, the aforementioned quantities (except h1 and h2) are temperature and frequency dependent. The results from these computations were then used as a basis for constructing master curves; this was done for a reference temperature of 15.5ºC (prevailing in the APT experiment) following the approach developed by Levenberg & Shah (2008). The dynamic modulus and phase angle master curves are both plotted in Figure 2 (vs. reduced frequency); the corresponding time-temperature shift factor aT is plotted in Figure 3 (vs. physical temperature). As a second step, it may be seen in Figures 2 and 3 that the HMA modulus from Table 1, obtained at a temperature of 15.5ºC and a loading speed of 8 km/h, is paired with a reduced frequency of 0.0232 Hz and a time-temperature shift factor of unity. Using the same figures a new HMA modulus can be computed for any given loading speed and temperature by adjusting fr and aT relative to the APT conditions. For example, if axles were moving 9 times faster than in the APT (i.e., 72.4 km/h or 45 mph instead of 8 km/h or 5 mph), and the HMA temperature would remain unchanged at 15.5ºC (60ºF), then aT = 1.0 and the reduced frequency would become 0.2088 Hz (= 0.0232·9.0·1.0); the corresponding modulus (using Figure 2) is therefore 4,028 MPa (584,100 psi). On the other hand, if a higher HMA temperature is also considered, say 30ºC instead of 15.5ºC, then aT = 0.0308 and the reduced frequency would become 0.0064 Hz (= 0.0232 · 9.0 · 0.0308); the corresponding HMA modulus in this case is 1,685 MPa (244,300 psi). 4

PROJECTION OF NCAT RESPONSES

4.1 Loading and environment Traffic loadings at NCAT were applied using a designated fleet of tractor-trailer trucks, each traveling at 72.4 km/h (or 45 mph), or 9 times faster than the APT carriage. A picture of one typical truck is provided in Figure 4. As can be seen, the truck has several wheel assemblies: single-axle single-wheels (steer axle), tandem-axle dual-wheels (drive axle) and single-axle 1365

45

100,000 Dynamic modulus (data)

15.5ºC

Phase angle (data)

Viscoelastic model 40 35 30 25

1,000 20 15 100

Phase angle [degrees]

Dynamic modulus [MPa]

10,000

10 5 Reduced frequency [Hz]

10 1E–08

0 1E–06

1E–04

1E–02

1E+00

1E+02

1E+04

1E+06

1E+08

Figure 2. Combined HMA dynamic modulus and phase angle master curves (reference temp. 15.5ºC)

1E+05

–10.0ºC

Time-temperature shift factor [–]

1E+03

+4.4ºC 1E+01 a T = 1.0

+21.1ºC

1E–01 +37.8ºC 1E–03

+54.4ºC

15.5ºC

Temperature [ºC] 1E–05 –20.0

Figure 3.

–10.0

0.0

10.0

20.0

30.0

40.0

50.0

60.0

Combined HMA time-temperature shifting (reference temp. 15.5ºC).

dual-wheels (trailer axle). The different axles are indicated in the figure, reportedly carrying the following average loads (in kg): 4,850 (1S), 9,225 (1D), 9,210 (2D), 9,540 (1T), 9,425 (2T), 9,675 (3T), 9,330 (4T) and 9,360 (5T). The radius of contact area for each of the truck tires was taken as 101.6 mm (4.0 in.); the respective stress intensity was slightly different in each case, calculated using the axle weights listed above. For the dual axles, center to center tire spacing was 343 mm (13.5 in.); for the dual tandem axles, axle spacing was 1.27 m (50 in.). In what follows an attempt is made to forecast resilient responses at N1 caused by one truck pass. The average HMA temperature at the time of interest was 27ºC (80.6ºF) which 1366

Figure 4.

Picture of a typical NCAT truck (based on Priest & Timm 2006).

pairs with aT = 0.062 in Figure 3. The HMA modulus was determined from Figure 2; the reduced frequency was simply calculated as follows: fr = 0.0232 · 9.0 · 0.062 = 0.013 Hz in which 0.0232 Hz is the reduced frequency that represents the APT loading speed and temperature, 9.0 accounts for the difference in loading speed between APT and NCAT and 0.062 is the time-temperature shifting. The resulting HMA modulus was 2,000 MPa (290,000 psi). 4.2 Forward analysis The calibrated APT model (i.e., Table 1) with adjusted HMA modulus based on the preceding discussion were used in forward calculating selected responses measured at NCAT. The concrete floor in the APT model (fourth layer from the top) was left in place during the forward analysis because deeper into the NCAT subgrade a rigid bedrock was expected. The moving NCAT truck was simulated by applying the tire loads at different locations relative to the evaluation points. Calculations were performed for every 0.001 seconds during which the axles traveled forward 20.1 mm (0.792 in.) based on a 72.4 km/h (45 mph) speed. Figure 5 presents the gauge array embedded in the N1 section, showing only the nine gauges that survived the construction process at NCAT. These included a pressure cell on top of the base (BBC), a pressure cell on top of the subgrade (ASC) and seven horizontal strain gauges that were attached to the bottom of the HMA measuring strains in Y (travel) direction (ALC, ALR, BLC and BLR) and also in X (transverse) direction (ATC, BTC and BTL). It is important to note that the wheel positions relative to the gauges were not measured in the NCAT experiment. These positions, however, were necessary for performing the forward analysis (i.e., LET computations). In an effort to resolve this issue it was assumed that peak gauge readings were attained when the load was in line with the corresponding gauge. This assumption helped position the moving axles in the Y direction (i.e., direction of travel). It was further assumed that the truck wheels were moving in a straight line, not necessarily parallel to road centerline, while passing over the gauge array. The oblique line of arrows in Figure 5 represents the travel path of the center of the rightmost truck tire. This line is seen to be located at an unknown transverse distance from the BBC gauge, denoted in the figure as X0 and at an unknown distance from the ASC gauge, denoted as X1. The determination of X0 and X1 was done, separately for each half-axle considered, such that model predictions best conformed with the measured responses of these two gauges only. Hence, the matching between model and experiment for gauges BBC and ASC should not be considered as pure prediction given that it was consciously minimized to position the axles. 4.3 Response projections In Figures 6 and 7 the computational model and the measured resilient responses at NCAT (vs. time) are graphically contrasted. Figure 6 presents the stresses and strains due to the drive axles 1D and 2D; Figure 7 presents the stresses and strains due to the third trailer 1367

Y-axis [ft]

X1 ASC

6 S = 45 mph = 792 in./s

4 ALR

ALC

2 ATC

X-axis [ft] –2

–4

2

BTC

4

BTL

–2 BLR

BLC

–4

X0 BBC

–6 Figure 5. Layout of N1 array of functional gauges and travel path location of the center point of the rightmost truck tire (connecting arrows).

axle 3T. Each figure contains nine charts, depicting the calculated and measured response of the individual gauges shown in Figure 5. The abscissa represents time in seconds with an arbitrary origin. The ordinate represents either vertical stress (in psi) or horizontal strain (in microstrains) depending on the gauge considered; note that the vertical scale changes from chart to chart. In addition, each figure also includes (bottom right), a picture of the NCAT truck with an arrow identifying the half-axle considered. Calculated responses due to other axles can be found in Levenberg (2008). As a general observation, it may be seen in Figures 6 and 7 that the model predictions capture relatively well the magnitudes as well as the trends in the measured responses. Better matching was usually achieved for the strains in the travel (longitudinal) direction (i.e., strains in Y) compared to the strains in the transverse direction (i.e., strains in X). The prediction ability of the vertical stresses cannot be assessed because these were used to position the loads. 5

SUMMARY AND CONCLUSIONS

The paper presented a simplified interpretation approach for using APT results in conjunction with laboratory test data to predict resilient field responses of similarly constructed pavement systems. The APT experiment was modeled first, using isotropic LET, with material properties obtained through backcalculation. For this purpose the entire time-history of embedded gauge readings was matched during one APT pass. This inverse analysis is a key point in the proposed scheme as it minimizes systematic errors originating from the application of a rudimentary pavement model. Next, the APT model was enhanced to apply to other experimental conditions by adjusting the modulus of the HMA to reflect differences 1368

Figure 6.

Calculated and measured N1 responses—right side of drive axle (1D and 2D).

in loading speed and temperature relative to the calibration conditions. This was achieved through analysis of complex modulus test data. The enhanced APT model was applied to forecast responses generated by a moving truck in a similarly constructed pavement system at NCAT. The enhanced model performed relatively well considering all aforementioned simplifying assumptions and the relatively few parameters used to represent the pavement system. More sophisticated pavement models are required to further improve the prediction ability through better matching of the response peaks and by capturing additional response 1369

Figure 7.

Calculated and measured N1 responses—right side of trailer axle (3T).

characteristics that cannot be simulated using LET, such as the time lag between peak responses and load location and asymmetry of the response traces. REFERENCES Barde, V. & Cardone, F. 2004. Dynamic modulus testing of NCAT mixtures. CE 597 Course Report. Submitted to Dr. Terhi Pellinen. School of Civil Engineering, Purdue University.

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Fylstra, D., Lasdon, L., Watson, J. & Waren, A. 1998. Design and use of the Microsoft Excel solver. Interfaces 28(5): 29–55. Galal, K., White, T.D. & Reck, C. 1998. Accelerated pavement testing facility. INDOT Division of Research report. West Lafayette. Indiana. Levenberg, E. 2006. Constitutive modeling of asphalt-aggregate mixes with damage and healing. Ph.D. dissertation. Technion—Israel Institute of Technology. Levenberg, E. 2008. Validation of NCAT structural test track experiment using INDOT APT facility. Final Report. Joint Transportation Research Program. SPR-2813 Project. North Central Superpave Center. Purdue University. Levenberg, E., McDaniel, R.S. & Pellinen, T.K. 2008. Backcalculation of layer moduli using time history of embedded gauge readings. Third international conference on accelerated pavement testing. Madrid. Spain. Levenberg, E. & Shah, A. 2008. Interpretation of complex modulus test results for asphalt-aggregate mixes. Journal of Testing and Evaluation 36(4). Llenín, J.A. & Pellinen, T.K. 2004. Validation of NCAT structural test track experiment using INDOT APT facility. Interim draft final report. Joint Transportation Research Program. SPR-2813 Project. Purdue University. NCHRP. 2002. Standard test method for dynamic modulus of asphalt concrete mixtures. Provisional test method DM-1. National Cooperative Highway Research Program. Project 1-37 A Report. Arizona State University. Priest, A.L. & Timm, D.H. 2006. Methodology and calibration of fatigue transfer functions for mechanistic-empirical flexible pavement design. NCAT Report 06-03. National Center for Asphalt Technology. Shields, D.H., Zeng, M. & Kwok, R. 1998. Nonlinear viscoelastic behavior of asphalt concrete in stress relaxation. Journal of the Association of Asphalt Pavement Technologists 67. Timm, D.H. & Priest, A.L. 2006. Material properties of the 2003 NCAT test track structural study. NCAT Report 06-01. National Center for Asphalt Technology. Timm, D.H., Priest, A.L. & McEwen, T.V. 2004. Design and instrumentation of the structural pavement experiment at the NCAT test track. NCAT Report 04-01. National Center for Asphalt Technology. Timm, D.H., West, R.C., Priest, A.L., Powell, B., Selvaraj, I., Zhang, J. & Brown, R. 2006. Phase II NCAT test track results. NCAT Report 06-05. National Center for Asphalt Technology. Tutumluer, E. & Thompson, M.R. 1997. Anisotropic modeling of granular bases in flexible pavements. Transportation Research Board. Transportation Research Record 1557: 18–26. Washington, DC. Uzan, J. 1985. Characterization of granular material. Transportation Research Board. Transportation Research Record 1022: 52–59, Washington, DC. Uzan, J. 1992. Resilient characterization of pavement materials. International Journal of Numerical and Analytical Methods in Geomechanics 16: 453–459. Uzan, J. & Levenberg, E. 2007. Advanced testing and characterization of asphalt concrete materials in tension. International Journal of Geomechanics 7(2): 158–165. White, T.D., Albers, J.M. & Haddock, J.E. 1990. An accelerated testing system to determine percent crushed aggregate requirements in bituminous mixtures—final report. Joint Transportation Research Program. FHWA/IN/JTRP-90-8. Purdue University.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Construction and field performance of hot mix asphalt with moderate and high RAP contents R. West, N. Tran, A. Kvasnak, B. Powell & P. Turner National Center for Asphalt Technology, Auburn, USA

ABSTRACT: Reclaimed asphalt pavement (RAP) can be used to replace a portion of the virgin materials in asphalt pavements. The use of RAP reduces material costs and demands on natural resources. RAP typically replaces 10 to 20 percent of virgin material in hot mix asphalt (HMA). In some regions, a surplus of RAP materials is available which could be used to further reduce costs. Often the percentage of RAP is not increased because of uncertainties about the performance and constructability of higher RAP content mixes. In 2006, research was initiated to investigate the feasibility of designing, producing, and constructing quality mixes containing moderate to high RAP percentages. Seven 200-foot test sections were built at the National Center for Asphalt Technology Pavement Test Track in September 2006. Since trafficking started in November 2006, over 10 million ESALs have been applied to these test sections. This paper discusses the construction and field performance of these RAP experiment sections. 1

INTRODUCTION

Removed asphalt pavement materials, termed reclaimed asphalt pavement (RAP), contain aggregates coated with asphalt binder which can replace a portion of virgin materials in asphalt pavements. The main benefits of using RAP include economic savings of material costs and conservation of natural resources, including both asphalt binder and aggregate materials. Some recent surveys indicate that the average RAP content used in new asphalt mixtures is about 15%. However, some regions of the United States have a surplus of RAP materials in some areas. Often HMA mixes containing higher RAP contents are not utilized because of uncertainties about their performance and constructablility. In 2006, research was initiated to investigate the feasibility of designing, producing, and constructing quality mixes containing moderate (15 to 25 percent) to high (more than 25 percent) RAP contents. Seven 200-foot test sections were built at the National Center for Asphalt Technology (NCAT) Pavement Test Track in September 2006. Since trafficking started in November 2006, over 10 million ESALs have been applied to these test sections. This paper discusses the construction and field performance of these moderate and high RAP experiment sections. 2

NCAT PAVEMENT TEST TRACK

The NCAT Pavement Test Track, shown in Figure 1, is a full-scale accelerated performance test (APT) facility located in Opelika, Alabama, United States. The test site includes 46 different 200-foot test sections around a 1.7-mile oval test track. Each test section is custom-built to evaluate the performance of HMA mixes and/or a flexible pavement structure. Surface mix performance sections are built on perpetual pavement structures to limit distresses to the surface mixes. Structural sections are typically thinner and highly instrumented pavements. A fleet of five heavy trucks is operated on the track to apply a design life-time of truck traffic (10 million equivalent single axle loads, or ESALs) within each research cycle of two years. 1373

Figure 1.

NCAT Pavement Test Track located in Opelika, Alabama, USA.

Table 1.

3

Experimental plan.

Test section

%RAP

Virgin binder

N5 W3 W4 W5 E5 E6 E7

0% 20% 20% 45% 45% 45% 45%

PG 67-22 PG 76-22 PG 67-22 PG 52-28 PG 67-22 PG 76-22 PG 76-22 & 1.5% Sasobit

EXPERIMENTAL PLAN

In order to evaluate the constructability and field performance of the moderate and high RAP content mixes in real-world conditions, the experimental plan, shown in Table 1, included one control mix and six RAP mixes placed in surface courses of mix performance experiment sections at the NCAT Pavement Test Track. The control section (N5) was constructed using HMA with all virgin materials. Two test sections—W3 and W4—utilized HMA containing 20 percent RAP. Four test sections—W5, E5, E6 and E7—were built with HMA containing 45 percent RAP. Three virgin binder grades— PG 52-28, PG 67-22, and PG 76-22—were used. The virgin binder grade was varied while the gradation was kept constant to evaluate the need for adjusting the binder grade and effectiveness of using a polymer modified binder. For the mix used in Section E7, Sasobit, which is a warm mix asphalt additive, was used as a compaction aid, and the mixing temperature was not reduced. For all mixes, the nominal maximum aggregate size (NMAS) was 12.5 mm. The number of design gyrations for all of the mixes in this experiment was 60 gyrations. 4

CONSTRUCTION OF TEST SECTIONS

The RAP experiment sections were constructed on September 25 and 26, 2006. The RAP mixes were placed in surface courses approximately 50 mm thick on a milled and tacked surface. The underlying pavement structure is approximately 560 mm of HMA over 1374

an aggregate base. All the mixes in the experiment used the same aggregates and RAP components. An Astec mobile screen, as shown in Figure 2, was used to fractionate the RAP into a coarse (–19.0 to 4.75 mm) and a fine RAP material (–4.75 mm). The fractionated RAP materials were added separately to the mixing drum using two RAP bins, as shown in Figure 3. Plant discharge temperatures ranged from 143 to 160οC. The density of the RAP test sections was monitored using a nuclear density gauge. The nuclear density readings were later calibrated based on the densities of five cores extracted from each test section. There was a concern about the compactability of the RAP mix (45 percent RAP and modified binder PG 76-22) used in Section E6 before the construction of this section. However, the contractor did not have any difficulty compacting this mix during the construction. The in-place density measured in each section is presented later in this paper. In general, the construction of the experiment sections at the NCAT Pavement Test Track went well.

Figure 2.

Astec mobile screen used for fractionating RAP.

Figure 3.

Separate bins used for coarse and fine RAP materials.

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5

MATERIAL PROPERTIES

5.1 Asphalt binder Table 2 summarizes binder test results determined in the laboratory for this experiment. Three binder testing programs were conducted. First, the RAP was sampled for determining the grade of the binder in the RAP. The binder was extracted and recovered from the RAP in accordance with ASTM D2172 and D5404, respectively. The recovered binder was then tested and graded as 89.1–16.4 according to AASHTO M 320-07. Second, during the construction, the virgin binder used for each mix in the RAP experiment was sampled to determine its true grade. Based on the recovered grade of the RAP binder and the true grade of each virgin binder, the grade of the binder in the corresponding RAP mix was calculated according to AASHTO M 323-07. Third, laboratory testing was conducted to determine the grade of the binder extracted and recovered from plant mixes sampled during the construction of each test section. As shown in Table 2, for most of the binders recovered from the RAP mixes, the calculated high and low binder grade temperatures were slightly lower and higher than the corresponding measured values, respectively. 5.2 Mixture properties Table 3 summarizes the quality control data determined during the construction of the RAP experiment sections. The control mix in Section N5 had a target design binder content of 5.8 percent. The target design binder content for the moderate RAP content mixes in Section W3 and W4 was 5.6 percent. For the mixes containing 45 percent RAP in other test sections—W3, E5, E6 and E7, the target design binder content was 5.0 percent. As shown in Table 3, the quality control air voids for three RAP mixes used in Sections W3, W4 and W5 were approximately 2 percent, which caused some concerns about the rutting resistance of these mixes. 6

FIELD PERFORMANCE MONITORING

Traffic began on all the test sections on November 10, 2006. Over 10 million ESALs have been applied to these test sections to date. Performance of the test sections is closely monitored on a weekly basis. Measurements include rutting, cracking, macro texture, and roughness. In each 200-foot test section, the first and last 25-foot portions are reserved for

Table 2.

Summary of binder test data. RAP binder

Virgin + RAP binder

Virgin binder

Test section

%RAP*

%RAP binder**

Recovered grade

N5 W3 W4 W5 E5 E6 E7

0% 20% 20% 45% 45% 45% 45%

0% 18.2% 17.6% 42.7% 41.0% 41.9% 42.7%

N/A 89.1-16.4 89.1-16.4 89.1-16.4 89.1-16.4 89.1-16.4 89.1-16.4

PG grade PG 67-22 PG 76-22 PG 67-22 PG 52-28 PG 67-22 PG 76-22 PG 76-22+ 1.5% Sasobit

* by weight of aggregates. ** by weight of binder.

1376

True grade

Calculated grade

Recovered grade

68.4-31.2 78.1-23.8 68.4-31.2 54.7-32.8 68.4-31.2 78.1-23.8 83.2-20.6

68.4-31.2 80.1-22.4 72.0-28.6 69.4-25.8 76.9-25.1 82.7-20.7 85.7-18.8

71.1-32.4 78.1-30.3 74.2-29.7 74.1-30.2 80.9-26.2 85.5-25.7 86.3-24.3

Table 3.

Summary of mixture properties for RAP experiment sections.

Test section

%RAP

N5 W3 W4 W5 E5 E6 E7

0% 20% 20% 45% 45% 45% 45%

Virgin binder

Binder content (%)

Air voids (%)

67-22 76-22 67-22 52-28 67-22 76-22 76-22+ Sasobit

5.8 5.6 5.8 4.9 5.1 5.0 4.9

2.9 1.9 2.1 1.7 3.2 3.5 3.6

VMA (%) VFA (%)

Dust-tobinder ratio

In-place density (%Gmm)

15.9 14.2 14.5 12.5 13.8 13.9 13.9

1.22 1.43 1.44 1.83 1.37 1.66 1.62

94.8 92.0 93.9 95.3 94.0 95.5 96.0

81.6 86.6 85.4 86.3 76.9 74.9 74.2

VMA = voids in mineral aggregate. VFA = voids filled with asphalt.

cutting cores for laboratory testing, and the middle 150-foot portions are used for monitoring field performance. An ARAN inertial profiler equipped with a full lane width dual scanning laser “rutbar” is used to determine individual wheelpath roughness, right wheelpath macro texture and individual wheelpath rutting for every experimental section. Additionally, three random locations were selected within each section in a stratified manner to serve as the fixed test location for nondestructive wheelpath densities. Transverse profiles are measured along these same locations regularly so that rutting may be calibrated with a contact method using a dipstick. Each section is inspected closely for cracking weekly. If a crack is detected, it is manually marked on the pavement and measured to generate crack maps for monitoring the progress of cracking in each test section. 7

FIELD PERFORMANCE OF RAP EXPERIMENT SECTIONS

7.1 Rutting performance Figure 4 shows a plot of the average rut depths versus traffic. Section W4 with 20 percent RAP and PG 67-22 exhibited the highest rut depth—this rut depth is within the acceptable range in the field. As shown in Table 3, the quality control air voids for the mix used in this section were 2.1 percent. Another study for evaluating the rutting resistance of HMA mixes using unmodified binder PG 67-22 at the NCAT Pavement Test Track showed that the rutting resistance of the mix reduced significantly when the quality control air voids were less than 2.5 percent. The mixes used in Sections W3 and W5 also had approximately two percent air voids. However, the mix in Section W3 used PG 76-22, and the mix in Section W5 had 45 percent RAP. Use of a modified binder (PG 76-22) or a higher RAP content (45 percent) may help to improve the rutting resistance of these mixes. All sections with 45 percent RAP performed well in terms of rutting. 7.2 Cracking performance Among the seven RAP experiment sections, three sections—N5, W3, and E7—exhibited some cracking. Figure 5 shows a crack map of the control section (N5). All the cracking past 140 feet was the result of embankment settling rather than mix performance. Cracking prior to 140 feet was generally reflective from the performance of Section N5 in 2005, which was milled and inlaid for Section N5 in 2006. 1377

10 9 8 Rut Depth (mm)

7 6 5 4 3 2 1 0 0

2

4

6

8

10

12

Traffic (Million ESALs) N5

Figure 4.

E5

E6

E7

W3

W4

W5

Average rut depths for all test sections.

A crack map of Section W3 measured on August 2008 is shown in Figure 6. The first crack in this section was observed in early April 2008. This longitudinal crack has been developed slowly along the edge of the outside wheel path. For Section E7, a small amount of cracking was found in late January 2008. These longitudinal cracks have progressed slowly along the edge of the wheel paths. Figure 7 shows a top-down crack map of the surface mix in Section E7 in 2005; the top 2-inch surface mix was milled in 2006 for the construction of the RAP experiment surface mix. The milled surface was inspected, and no cracks were found at the time of the construction in 2006. However, top-down micro-crack may have developed in the asphalt base course. Figure 8 shows a crack map of Section E7 observed in August 2008. By comparing the two crack maps, it appeared that the cracks in the wearing layer of Sections E7 observed in 2008 was similar to those observed in the previous surface layer in 2005. The cracks in Section E7 observed in 2008 appeared to be reflected from the asphalt base course. These cracks can only be noticed when walking on the test sections. According on the Distress Identification Manual for the LongTerm Pavement Performance Program (FHWA, 2003), the cracking in these sections was classified as low severity. 8

CONCLUSIONS

Based on the results obtained from the construction and field performance data monitored at the NCAT Pavement Test Track, the following observations and conclusions are offered: • The RAP can be fractionated into coarse and fine materials using a mobile screen and added into the drum using separate RAP bins. • The in-place density of a mixture with a high RAP content (45 percent) and a modified asphalt binder (PG 76-22) can be achieved with a reasonable compaction effort. No compaction aid is required unless a lower compaction temperature is desired. • For most of the binders recovered from the RAP mixes, the calculated high and low binder grade temperatures were slightly lower and higher than the corresponding measured values, respectively. 1378

1379

12 11 10 9 8 7 6 5 4 3 2 1 0

25

25

Figure 6.

14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

Figure 5.

Transverse Offset (ft)

Transverse Offset (ft)

45

45

55

55

Crack map for Section W3.

35

Crack map for Section N5.

35

65

65

85

95

105

115

85

95

105

115

Longitudinal Distance from Far Transverse Joint (ft)

75

Longitudinal Distance from Far Transverse Joint (ft)

75

125

125

135

135

145

145

155

155

165

165

175

175

1380

Transverse Offset (ft)

14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

35

45

55

65

85

45

55

Crack map for Section E7 in 2008.

35

65

95

105

115

85

105

115

125

125

Longitudinal Distance from Far Transverse Joint (ft)

75

95

Longitudinal Distance from Far Transverse Joint (ft)

75

Crack map for Section E7 in 2005 before the surface mix was milled.

25

25

Figure 8.

14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

Figure 7.

Transverse Offset (ft)

135

135

145

145

155

155

165

165

175

175

• The rut depth measured in Section W4 was higher than that of other test sections. Based on the results of another study at the NCAT Pavement Test Track on the effect of low air voids (less than 2.5 percent) on the rutting performance of HMA with an unmodified asphalt binder (PG 67-22), the higher rut depth seen in Section W4 may be due to a combination of low air voids (2.1 percent) and the use of unmodified binder (PG 67-22) in the mix. • Other test sections showed good rutting performance under heavy truck traffic at the NCAT Pavement Test Track. Use of a modified binder (PG 76-22) or a higher RAP content (45 percent) may help to improve the rutting resistance of these mixes. • Among the seven test sections built for this experiment, only three sections exhibited cracking. All the cracking in the control section (N5) was the result of embankment settling or reflective cracking rather than the surface mix performance. Section W3 showed low severity longitudinal cracking along the edge of the outside wheel path. Section E7 showed low severity reflection cracking. The cracking can only be seen when walking the test sections. In summary, the construction of the moderate and high RAP content mixes went well. The high RAP content mixes performed well in terms of rutting. Two sections exhibited low severity cracks, and all the other sections had no cracking. ACKNOWLEDEMENTS This study is sponsored by the Oldcastle Materials Group, Inc., North Carolina Department of Transportation, and Alabama Department of Transportation. The views expressed in this paper and the accuracy of the data and facts contained herein are the sole responsibility of the authors, and do not necessarily represent the official views of the listed sponsoring agencies. This paper does not constitute a standard, specification, or regulation. Comments contained in this paper related to specific testing equipment and materials should not be considered an endorsement of any commercial product or service; no such endorsement is intended or implied. REFERENCES FHWA. 2003. Distress Identification Manual for the Long-Term Pavement Performance Program, U.S. Department of Transportation, Federal Highway Administration, Pub. No. FHWA-RD-03-031.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Analysis of in-pavement sensor data for CC2 new rigid test items at the FAA National Airport Pavement Test Facility D.R. Brill Federal Aviation Administration, Airport Technology R&D Branch, William J. Hughes Technical Center, Atlantic City International Airport, New Jersey, USA

E.H. Guo SRA International, Inc., New Jersey, USA

ABSTRACT: Full-scale testing of three new rigid pavement test items took place at the Federal Aviation Administration (FAA) National Airport Pavement Test Facility (NAPTF). Pavements were trafficked to complete failure with 4- and 6-wheel gear loads. The performance of slabs under traffic was monitored using visual surveys, crack mapping, destructive and nondestructive testing. Cores recovered from cracked areas of the slabs revealed that some cracks initiated from the surface (“top-down”), while others initiated from the bottom surface (“bottom-up”) or were inconclusive. By analyzing data from the in-pavement sensors, it was possible to supplement the information from the visual surveys and destructive tests. The gage data supplied new information about the relative prevalence of top-down versus bottom-up crack initiation, as well as the timing of crack formation. This is a key consideration for future development of the FAA’s rigid design procedures, which currently consider a single failure mode based on bottom-up cracking. 1

INTRODUCTION

Full-scale traffic testing of three new rigid pavement test items took place during 2004 at the NAPTF, located at the FAA William J. Hughes Technical Center, Atlantic City International Airport, New Jersey (USA). These tests were part of the NAPTF rigid pavement experiments collectively referred to as Construction Cycle 2 (CC2). A full description of CC2 is given elsewhere (Brill, et al. 2005). The major testing consisted of three test items designated MRC, MRS, and MRG. The last letter of each test item designation refers to the type of foundation: C for conventional, or aggregate base, S for stabilized base (econocrete), and G for slabon-grade. (The letter M designates medium-strength subgrade, CBR 7-8; R indicates a rigid pavement type.) Traffic tests are designated using the test item name in combination with the letter N or S, to indicate the north or south traffic lane, e.g. MRC-N. The test items were trafficked to complete failure with loads simulating 4- and 6-wheel airplane landing gears with wander. Each test item was trafficked on two lanes, resulting in a total of six failures. Trafficking of the CC2 test items took place from April to December 2004. Not all test items were trafficked simultaneously. Test item MRC-S was trafficked from April 27–May 20, test item MRC-N from May 6–June 30, and the remaining test items from July 6–December 10. (Testing on MRS-N was stopped on September 23.) As shown in Figure 1, the loading consisted of a 6-wheel gear on the north side and a 4-wheel gear on the south, except for MRC-N, which also received a 4-wheel gear. Wander was applied using a 66-position wander pattern simulating a normal traffic distribution with σ = 775 mm (30.5 in.). However, a modified wander pattern was used for MRC-N only, so that no wheel loads were applied directly to the outside row of slabs (Figure 1). Performance monitoring consisted of four components: visual observations (Pavement Condition Index (PCI) surveys, crack mapping), nondestructive testing (heavy weight deflectometer (HWD), profile measurements), destructive tests 1383

MRC

Carriage 2 Trafficked Area

MRG

MRS 18.3 m (60 ft)

Carriage 1 Trafficked Area

CENTERLINE

22.9 m (75 ft) 7.6 m (25 ft) Transition Area (Typ.)

Figure 1.

22.9 m (75 ft)

22.9 m (75 ft)

Direction of Traffic

Layout of CC2 test items at the NAPTF.

(extracted cores), and in-pavement sensors. The instrumentation for CC2 consisted of 264 embedded sensors, including concrete strain gages (CSG), vertical displacement transducers (VDT), thermistors, soil moisture gages, relative humidity (RH) sensors, and horizontal displacement transducers (HDT). The CC2 database contains a large volume of sensor data that can be analyzed alone or in combination with other performance data to explain how the test items failed. To date, only a fraction of these data have been analyzed. The FAA’s previous experience with testing rigid pavements in an indoor environment confirmed the importance of controlling moisture-induced curling to avoid premature corner failures (McQueen et al. 2002). Therefore, special efforts were made to minimize curling and slab/base separation including: reduced slab size [all slabs were 4.6 × 4.6 m (15 × 15 ft)], doweling all slabs in both directions, and watering of the slab surface such that the slabs were kept continuously wet from concrete placement until the end of trafficking. These efforts were largely successful, as daily slab corner measurements demonstrated that upward curling remained less than 0.5 mm (20 mil). 2

TOP-DOWN AND BOTTOM-UP CRACKS

Current FAA thickness design procedures (FAA, 2008) assume that load-induced cracks in rigid slabs initiate from the bottom of the slab and propagate toward the top. Top-down cracks are generally associated with loss of base support, e.g., from upward curling, and are not explicitly considered in structural thickness design. As reported previously (Brill et al. 2005), both top-down and bottom-up cracks were observed in all CC2 test items, although the slabs remained essentially flat. Top-down load-induced cracks were observed on the outside slabs of MRC-N even though, as noted above, no traffic was applied to those slabs. Figure 2 shows the distribution of top-down and bottom-up cracks in test item MRC at the end of testing, as determined by examination of extracted cores. Solid black lines represent top-down cracks, while dotted black lines represent bottom-up cracks. Thin gray lines indicate cracks for which no core was taken or the core was inconclusive. Figure 2 shows that there are many cracks for which cores were not taken, making direct observation of these cracks impossible. However, indirect analysis of the crack development may still be possible using data from nearby sensors. A similar method was previously used by Guo et al. to analyze crack formation and progression in the first-year (CC1) rigid test items at the NAPTF (Guo, et al. 2002). Essentially, anomalies in the sensor histories were combined with visual survey data to provide information about how and when cracks developed. In the case of the CC1 data, the main goal was to determine when and how premature corner breaks formed. In the present case, it is shown that many load-induced longitudinal/transverse/diagonal (LTD) fatigue cracks are top-down, suggesting that the current design model assuming bottom-up cracking is a considerable simplification of the real case. The results presented in this paper are based on sensor data from test item MRC, primarily MRC-N. Sensor data from other CC2 test items is currently being analyzed. 1384

N

S1

S2

S3

S4

S5

S6

S7

S8

S9

S10

C L S11

S12

S13

S14

S15

S16

S17

S18

S19

S20

Figure 2. Locations of top-down (heavy black lines) and bottom-up (heavy dotted lines) cracks in the final distress map for test item MRC in CC2, based on core examination. Light gray lines represent cracks of unknown or indeterminate direction. Stars represent core locations.

3

MRC-N SLAB S8 DATA ANALYSIS

An example of sensor data analysis providing information about the cracking history of a slab is presented in this section. Figure 3 shows a photograph of slab S8 in MRC-N in the final failed condition, with the observed cracking pattern superimposed. As shown in Figure 3, several cores were taken from diagonal crack 37 shortly after it appeared. Based on these cores, crack 37 was identified as a top-down crack. Corner crack 45, transverse crack 55, and longitudinal crack 63 all appeared after crack 37, but no cores were retrieved from these other locations. Figure 4 shows the locations of strain gages and VDTs within slab S8. It should be noted that most strain gages were stacked in pairs, so that, for example, the location CSG-9 refers to two separate gages, CSG-9A (top of slab) and CSG-9B (bottom of slab). The direction of the symbol in the figure corresponds to the gage orientation. Comparing Figures 3 and 4, it is noted that crack 55 crosses approximately the position of VDT-5 and CSG-9 (A and B), so it is reasonable to assume these gages may supply information relevant to crack 55. Likewise, longitudinal crack 63 crosses interior strain gages CSG-11 (A and B), CSG-13 (A and B), and VDT-7, so the formation of crack 63 may be reflected in the gage responses. First, consider the response of the CSG pair 9A and 9B. For MRC-N, the NAPTF test vehicle used a modification of the normal NAPTF wander pattern consisting of 76 positions on 5 tracks, designated 0 through 4. This modified wander pattern was used to eliminate wheel loads on the outside row of slabs. Track 0 resulted in wheel loads directly on sensors CSG-9A and -9B, VDT-4, VDT-5, and VDT-6, while the other tracks produced loads at varying offsets from these sensors. Therefore, for this analysis, the data set was restricted to track 0 responses, which resulted in the maximum response and are the simplest 1385

Figure 3.

Slab S8 in MRC-N after trafficking, with superimposed cracking pattern.

Figure 4.

Locations of in-pavement sensors, MRC-N.

to analyze. The data set was further restricted to consider only west-to-east vehicle passes. Although in the ideal case, the west-to-east and east-to west movement should produce the same peak response due to symmetry, in practice there is a consistent difference in the average peak strain depending on the vehicle direction. In the case of CSG-9A, it was found 1386

that the average peak strain for east-west passes was approximately 3.4 percent less than for west-east passes over the same time period. The reason for this deviation from the symmetric case is not known, but it could be due to a directional bias in joint load transfer, or to other unknown structural factors. By restricting the data to only west-east passes on track 0, a usable, repeatable subset of the data was obtained. Figure 5 plots values of peak longitudinal strain recorded in CSG-9A and -9B as a function of time, for the above data subset. The major testing milestones for MRC-N, and the associated passes, are also labeled. Variability in the recorded peak strain may have several sources, including: variations in environmental conditions such as ambient temperature and humidity, tire load fluctuations, changes over time in tire contact pressure and area, noise in the sensor response, and signal sampling errors. Figure 5 gives an idea of the level of variability in the peak strain associated with daily traffic, as well as the increase in variability with time associated with damage to the pavement and/or the sensors. Figures 6a and 6b give a closer view of this latter phenomenon. Figure 6a presents a summary of peak strains recorded in CSG-9A (top of slab, negative, compressive) and CSG-9B (bottom of slab, positive, tensile) for the week of May 10, 2004, which was the second week of traffic. For both gages, the repeatability of the peak response is high, which is consistent with a new and essentially undamaged pavement. It is noted that the strain measured at the top of the slab is higher than the strain at the bottom (by approximately 35%), which, if a true reflection of the strain, may indicate some degree of effective bond between the slab and the base layer. Figure 6b is similar to 6a, except that the peak responses are for the week of June 7, 2004, which was week 6 of testing. It may be seen from Figure 6b that the level of scatter in the top sensor (CSG-9A) has increased considerably, while the readings at the bottom of the slab continue to show very little scatter. Anomalous readings in Figure 6b on June 7 and June 9 are probably associated with the formation of cracks 55 and 63, respectively. If it is assumed that a significant change in the repeatability of the local peak strain response is a reasonable measure of material damage to the slab, all else being treated as equal, than Figures 5 and 6 are consistent with a top-down transverse crack.

0.15 Start of traffic on MRS-N

Pass 12692, traffic stopped

Peak Strain × 10–3

0.1 0.05 0 4/23/04

5/3/04

5/13/04 5/23/04 6/2/04

6/12/04 6/22/04 7/2/04 7/12/04

–0.05 –0.1 Pass 5781, crack 37 observed

–0.15

Pass 7909, crack 63 observed

Cores taken

Pass 6997, crack 55 observed

CSG-9B (Bottom Slab)

CSG-9A (Top Slab)

Figure 5. Peak longitudinal strains recorded by CSG-9A and CSG-9B for the period May 5–June 30, 2004. Data shown for west-to-east passes on wander track 0.

1387

Since CSG-9A is longitudinal and at the top of the slab, its normal response to the rolling tire load is tensile ahead of the load, then compressive as the load passes directly over the gage, then tensile again as the load leaves. In the CC2 database, the maximum value of the positive (tensile) strain is stored as Peak 1, while the maximum negative (compressive) strain under the tire is stored as Peak 2. As cracking takes place at the surface of the slab, the ability of the concrete to develop tensile stress is gradually reduced, resulting in lower measured tensile strains. This trend is clearly shown in Figure 7, which plots both the reverse (tensile) peak strain and the compressive peak strain in CSG-9A as a function of the pass number. Three distinct phases can be identified. From passes 1 to 3610, the response is relatively stable. The magnitude of Peak 1 is approximately 40% of Peak 2. From pass 3610, where there was a distinct change in Peak 1 as the surface crack initiated, to pass 6731, Peak 1 continued to diminish as the crack propagated downward. At approximately pass 6731 the crack became full-depth. The reverse peak strain values after pass 6731 are close to zero and are more

0.1 0.05

0.05

Peak Strain × 10–3

Peak Strain × 10–3

0.1

0 5/10/04 0:00

5/11/04 0:00

5/12/04 0:00

5/13/04 0:00

5/14/04 0:00

5/15/04 0:00

–0.05

–0.1

0 6/7/04 0:00

6/8/04 0:00

6/9/04 0:00

6/10/04 0:00

6/11/04 0:0

–0.05 –0.1 –0.15

CSG-9A Peak Linear (CSG-9A Peak)

CSG-9B Peak Linear (CSG-9B Peak)

CSG-9A Peak Linear (CSG-9B Peak)

(a)

CSG-9B Peak Linear (CSG-9A Peak)

(b)

Figure 6. Peak longitudinal strains recorded by CSG-9A (top of slab) and CSG-9B (bottom of slab), for the periods (a) May 10–15, 2004, and (b) June 7–10, 2004.

0.06 0.04

Strain x 10

–3

0.02 0

Pass 3609, surface crack initiated

–0.02

Pass 6731, crack became full-depth

–0.04 –0.06 –0.08 –0.1 0

1000

2000

3000

4000

5000

6000

7000

800

Pass Number CSG-9A Peak 1 (Reverse Peak Strain, Tensile) CSG-9A Peak 2 (Peak Strain, Compressive) Figure 7. Peak longitudinal tensile and compressive strains recorded by CSG-9A (top of slab) as a function of pass number.

1388

erratic. The change from initial crack to full-depth crack status required 3,120 additional passes. Significantly, although Figure 7 shows crack 55 initiated at pass 3610, it was not observed by visual survey until pass 6997, shortly after it became full-depth (see Figure 5). The anomalous reading in CSG-9A Peak 2 at pass 6731 seems to correspond to the point at which crack 55 became full depth. Peak responses were also analyzed for the VDTs in slab S8. It was found that significant changes in the VDT peak response generally coincided with the appearance of LDT cracks and corner breaks on the surface (Figure 8), but it was not possible to determine from the VDT peak responses alone whether a given crack was top-down or bottom-up. As shown in Figures 8 and 9, the peak VDT readings tended to decrease steadily during the course of daily testing, then recover when testing began again the following day. This trend was apparent from the start of MRC-N testing and appears to be related to the PCC temperature. In general, the biggest factor driving temperature change near the PCC surface is the daily variation in ambient air temperature. However, it was observed that CC2 slabs subjected to tire loading experienced a somewhat greater temperature increase near the surface (2–3 degrees Celsius) as compared to non-trafficked slabs (Figure 9). Moreover, the shapes of the two temperature curves are different, with a sharp peak in late afternoon coinciding with the cessation of traffic on the loaded slab. On the basis of a preliminary heat transfer analysis conducted by the authors (not presented here), this additional increment of temperature increase can plausibly be attributed to contact between the rolling tires and the pavement surface. Full dynamic strain gage histories, in addition to the extracted peak responses, were needed to analyze longitudinal crack 63 at the center of the slab. A review of the peak responses for CSG-11A, -11B, -13A and -13B, showed that both bottom gages started recording anomalous responses very early in the testing, while the top strain gages continued to record normal responses for a large number of passes. The most reasonable explanation is that a longitudinal

4/23/04 0.1

5/13/04

6/2/04

6/22/04

4/23/04 0

7/12/04

5/13/04

6/2/04

6/22/04

7/12/04

Deflection, mm

Deflection, mm

–0.2 –0.4

–0.9

–0.4 –0.6 –0.8 –1

–1.4

(a) VDT-4 (corner), track 0 passes 4/23/04 0

5/13/04

6/2/04

6/22/04

(b) VDT-5 (center edge), track 0 passes 7/12/04

4/23/04 0

5/13/04

6/2/04

6/22/04

Deflection, mm

Deflection, mm

–0.1 –0.5

–1

–0.2 –0.3 –0.4

–1.5

–0.5

(c) VDT-6 (corner), track 0 passes Figure 8.

(d) VDT-7 (center slab), track 3 passes

Peak deflections recorded at VDTs in slab S8 for the period May 5–June 30.

1389

7/12/04

25

–1.1

20

–1

15

–0.9

10

–0.8

5

–0.7

0

–0.6

Deflection, mm

Temperature, deg. C

End of daily trafficking

5/10/04 0:00 5/11/04 0:00 5/12/04 0:00 5/13/04 0:00 5/14/04 0:00 5/15/04 0:00

Temp T9-A (top of slab, trafficked area) Temp T17-A (top of slab, non-trafficked area) VDT-4 Peak Deflection Figure 9. Plot of daily temperature variation at the top of the slab for the period May 10–May 15, 2004. A plot of VDT-4 (corner) peak response is superimposed on the temperature plot to show the relationship between the daily temperature variation and the change in the peak deflection response.

crack initiated at or near the bottom strain gage site after a small number of passes, which then propagated upwards toward the surface with additional passes. Figure 10 illustrates the qualitative and quantitative changes in the bottom gage response over the first few days of testing. Figure 10(a) shows the top and bottom transverse strain histories for a traffic event (pass 9) just after the start of testing on MRC-N. It should be noted that the responses of CSG-13A and -13B (transverse strain) were analyzed for events corresponding to wander track 3, which placed the wheel load directly on top of the gage. Pass 9 was selected because it was the first pass on MRC-N corresponding to track 3. As expected, the top and bottom strains are nearly equal in magnitude, but opposite in sign. Both responses show two distinct peaks, corresponding to the two tires in tandem. Figure 10(b) shows the response of the same gage pair for pass 124 (corresponding to pass 47 of the second wander pattern repetition). While the shape of the response remains reasonable, the bottom tensile strain magnitude has increased nearly 100% compared to pass 9, indicating possible microcracking at the gage site. The magnitude of compressive strain at the top of the slab has also increased, but much more modestly (about 20%), which could be attributed to a weakened section. Further deterioration of the gage 13B response is shown in Figure 10(c), which is a record of pass 470, on the third day of trafficking. At this point, two distinct peaks are no longer distinguishable. Figure 10(d) shows that by pass 2446, the signal itself has started to degrade. Analysis of the longitudinal gages at the same location showed a similar trend. For approximately the first 50 passes, the strain readings at CSG-11A and CSG-11B were of similar magnitude and opposite sign. With additional passes, the CSG-11B strain reading first increased in magnitude, then became increasingly distorted. However, the CSG-11A response retained its integrity much longer, eventually becoming unstable after pass 7037. 1390

0.12 0.06

0.08 Strain × 10-3

Strain × 10-3

0.04 0.02 0

–0.02

0.04 0 –0.04

–0.04

–0.08

–0.06 0

5

10

0

15

5

CSG-13A

CSG-13A

CSG-13B

(a) Event 1398, Pass 9, May 5, 2004, 14:24 hrs.

15

CSG-13B

(b) Event 1513, Pass 124, May 6, 2004, 08:01 hrs.

0.5

0.4

0.4

0.3 Strain × 10–3

Strain × 10-3

10 Time, s

Time, s

0.3 0.2 0.1 0

0.2 0.1 0

–0.1 0

5

10

–0.1

15

0

Time, s CSG-13A

5

10

15

Time, s

CSG 13B

CSG-13A

CSG-13B

(c) Event 1859, Pass 470, May 7, 2004, 07:57 (d) Event 3835, Pass 2446, May 17, 2004, 08:29 hrs. hrs.

Figure 10. Recorded transverse strains at CSG-13A (top of slab) and CSG-13B (bottom of slab) for four different traffic events. Strains recorded at center of slab S8, MRC-N.

The sequence shown in Figures 10(a–d) strongly suggests that a longitudinal crack formed at the center of slab S8 very soon after the start of MRC-N trafficking at full tire load. From detailed analysis of the longitudinal and transverse strain gage histories for the first day of MRC-N traffic, the initial rupture probably occurred between passes 57 and 65. However, as Figure 5 shows, a visible crack (crack 63) did not appear at this location until pass 7909, that is, approximately 5 weeks after the start of testing. During this 5-week interval, crack 63 was present, but had not yet propagated to the surface. It is therefore reasonable to conclude that crack 63 was bottom-up. 4

FUTURE RESEARCH

Current research suggests that the quality of the subbase may be one of the factors influencing rigid pavement cracking modes. Hall, et al. (2005), in a study conducted for the Innovative Pavement Research Foundation (IPRF), indicated that high strength or thick stabilized base layers are a major cause contributing to early-age slab cracking, and high-strength bases lead to higher induced slab stresses where curling and warping are present. These higher induced stresses would tend to favor top-down cracking modes. To date, the only CC2 sensor responses that have been analyzed in detail are those from test item MRC, which consisted of 305-mm (12-in.) concrete slabs on a 254-mm (10-in.) unbound aggregate base (FAA item P-154), on the medium-strength clay subgrade. However, comparisons with data from the other two test items, MRS and MRG, may provide new information on the influence of high-stiffness bases. The structure of MRS above the clay subgrade consisted of 305-mm (12 in.) concrete slabs on a 152-mm (6-in.) stabilized econocrete base (FAA item P-306), on a 219-mm (8.6-in.) P-154 subbase, while the MRG slabs were placed directly on the clay subgrade with no base layers. Future research should use sensor data from all three test items to analyze whether the prevalence of top-down versus bottom-up cracks at various stages of trafficking is affected by the type of subbase present. 1391

5

SUMMARY AND CONCLUSIONS

The FAA conducted full-scale traffic tests on instrumented new rigid pavement test items at the National Airport Test Facility during 2004. These tests, designated CC2, produced a significant quantity of data for the trafficked pavements under 4-wheel and 6-wheel simulated full-scale airplane gear loads, including in-pavement strains, deflections, and other responses. Data analysis has been performed on a subset of these data, in particular for test item MRC. Examples of sensor data analysis were presented for several gages located on slab S8 in MRC-N, which was trafficked with a 4-wheel gear. The strain gage and VDT data analyzed, taken in combination with visual survey data, demonstrate the distresses observed on MRC-N were a combination of top-down and bottom-up cracking. Furthermore, the analysis shows bottom-up cracking in slab S8 initiated very soon after the start of trafficking at the full load, and only later progressed to the surface in the form of a visible longitudinal crack. The presence of a significant percentage of top-down longitudinal and transverse cracks in pavements that remained essentially flat throughout testing has implications for future development of FAA rigid pavement design procedures, which currently do not consider this failure mode. The examples presented in this paper demonstrate the importance of supplementing inpavement sensor data with frequent, detailed visual surveys, as well as core samples wherever possible. As was previously noted (Guo, et al. 2002) in reference to the CC1 data analysis, many of the rigid pavement sensor responses would be difficult to interpret properly except in light of the supplementary data from visual surveys and cores. Sensor data from all CC2 traffic tests, including test strips and traffic test items, have been collected in a searchable database. This database is currently being prepared for internetbased searching, and it is planned to make it available to the public through the FAA Airport Technology R&D branch web site: http://www.airporttech.tc.faa.gov/naptf/ ACKNOWLEDGMENTS/DISCLAIMER The work described in this paper was supported by the FAA Airport Technology Research and Development Branch, Dr. Satish K. Agrawal, Manager. Special thanks are due to Dr. Gordon F. Hayhoe, NAPTF Manager, for technical leadership in test planning and organization, and to Mr. Chuck Teubert of SRA International, Inc. for management of the CC2 database. The contents of the paper reflect the views of the authors, who are responsible for the facts and accuracy of the data presented within. The contents do not necessarily reflect the official views and policies of the FAA. The paper does not constitute a standard, specification, or regulation. REFERENCES Brill, D.R., Hayhoe, G.F., and Ricalde, L. 2005. Analysis of CC2 Rigid Pavement Test Data from the FAA’s National Airport Pavement Test Facility. In Proceedings of the Seventh International Conference on the Bearing Capacity of Roads, Railways and Airfields (BCRA’05), 27–29 June 2005, Trondheim, Norway. FAA 2008. Airport Pavement Design and Evaluation. Advisory Circular 150/5320-6E (Draft). Guo, E.H., Hayhoe, G.F., and Brill, D.R. 2002. Analysis of NAPTF Traffic Test Data for the First-Year Rigid Pavement Test Items. In Proceedings of the 2002 FAA Worldwide Airport Technology Transfer Conference, May 2002, Atlantic City, New Jersey, USA. Hall, J.W. (Principal Investigator), Mallela, J., Smith, K.L., Evans, L.D., Feldman, D., and Gotlif, A. 2005. Recommendations for the Use of Stabilized and Drainable Bases in Rigid Pavement Systems— Report of Findings. Report IPRF-01-G-002-1. Skokie, Illinois, USA: Innovative Pavement Research Foundation. McQueen, R.D., Rapol, J., and Flynn, R. 2002. Development of Material Requirements for Portland Cement Concrete Pavements at the National Airport Pavement Test Facility. In Proceedings of the 2002 FAA Worldwide Airport Technology Transfer Conference, May 2002, Atlantic City, New Jersey, USA.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Using the viscoelasticity and continuum damage theories to quantify the effects of loading speed in accelerated pavement testing results K.M. Theisen, D.R. Victorino, W.P. Nunez & J.A.P. Ceratti Department of Civil Engineering, Federal University of Rio Grande do Sul, Brazil

ABSTRACT: Accelerated pavement tests (APT) are important for studying the pavements performance. However, APT is limited because factors that affect pavement performance are not widely reproduced, mainly the loading speed. The traffic speed on real roads is higher (generally 80 km/h) than that used to perform APT (5 to 10 km/h). Due to the viscoelasticity of asphalt mixes, fatigue cracks appear quite rapidly in APT due to low speeds. In order to apply APT results to real loading time (RLT) roads, a formulation to estimate the influence of loading speed by employing viscoelasticity theory and Schapery’s work potential theory is presented. Experimental data were taken from APT using a HVS traffic simulator, testing at 8 km/h. An adaptation of the Schapery’s work potential theory formulation was developed and calibrated by using experimental data. The effect of loading speed then was estimated to speeds ranging from 4 to 80 km/h, showing results qualitatively similar to those observed in RLT roads. 1

INTRODUCTION

The accelerated pavement tests are effective tools for simulating field conditions when studying pavement materials. However, many field conditions cannot be simulated by accelerated tests, mainly the axle speed. The axle speed has an important influence in design parameters applied on mechanistic analysis consequently on pavement performance. Performing many accelerated tests to verify the speed’s influence is expensive and time-consuming, being unattractive to the academic and professional environments. Several researches show the influence of loading speed on degradation of flexible pavements. The major first study focused on influence of speed was probably the AASHO Road Test in 1962. This study showed that the average deflection on the flexible pavements decreased 38% and the deflection on the top of subgrade decreased 35% when speed increased from 3.2 to 56 km/h. That result shows the strong influence of speed on pavement’s behavior. Recent studies also have shown the speed influence on pavements’ behavior. Siddharthan et al. (2002) and Mostafa et al. (2006) performed Finite Layer and Finite Element numerical modeling techniques, respectively, using viscoelasticity theory to reproduce the asphalt mix behavior. That way, the influence of loading speed on pavement behavior could be simulated, where significant influence on the pavement’s structural response has been noticed. Hence, this research is motivated by the development and success of recent laboratorial studies of constitutive models of asphalt mixes along with the development of computational tools which uses the continuum mechanics theories. The objective is to employ continuum damage theories (in this case, Schapery’s Work Potential Theory) in order to determine the influence of loading speed on pavement’s performance by using accelerated pavement test data. No one complex numerical theory has been applied during this study. The intention was to perform an estimate using accelerated pavement test data easily measured in situ. Deflection bowls and crack propagation on pavement surface as well as laboratorial test were used in this study, offering a simple and viable methodology as to academic as to professional environments. 1393

2

THEORETICAL FUNDAMENTALS

2.1 Viscoelasticity theory Viscoelastic materials are defined as materials that show characteristics of both linear-elastic and viscous materials. Linear-elastic materials are characterized by total storage of mechanic energy, while viscous materials are characterized by total dissipation of mechanic energy. Thus, viscoelastic materials are characterized by partial storage of the strain energy. According to Mello (2008), different behaviors are observed in asphalt mixes depending on loading magnitude, loading time and instantaneous loading slope. Furthermore, the same author relates if the temperature and loading conditions make the fatigue cracking the main factor of preoccupation in pavement performance, viscoelasticity is accepted to model the asphalt mix behavior. Di Benedetto et al. (2001) noted that, up to a certain number of load applications and a certain strain level on the material, it is possible to employ a viscoelastic model to reproduce the material behavior. Such limits are shown in Figure 1. The asphalt mixes behavior domains are defined as a function of the strain level (ε) and the number of load applications (N). The Linear viscoelastic region in Figure 1 is reached through load level significantly lower than the material`s strength limits. Furthermore, it is possible to consider the material as isotropic (Kim et al., 2004) and undamageable (Gibson et al., 2003). Thus, the constitutive model that describes the stress-strains behavior of viscoelastic materials that follow the conditions discussed above is defined by equations 1 and 2: t

ε ij (t ) = ∫ Dijkl (t − τ ) τ0

t

∂σ kl (τ ) dτ ∂τ

(1)

∂ε kl (τ ) dτ ∂τ

(2)

σ ij (t ) = ∫ Eijkl (t − τ ) τ0

where ε(t) = time-dependent strain, D(t–τ) = material’s creep compliance, σ(t) = time-dependent stress, τ = integration variable and τ0 = loading beginning time. The integrals presented by equations 1 and 2 are calculated by using Boltzmann’s principle (1876). Furthermore, equations 1 and 2 show that stresses and strains depend on the strain

Figure 1.

Typical domains of behavior observed on asphalt mixes (Di Benedetto et al., 2001).

1394

and stress history applied on the material, accounting for the “memory effect” noticed on viscoelastic materials. The Viscoelasticity Theory also allows transform linear-elastic solutions into viscoelastic solutions. The basic constitutive relationship of viscoelastic materials is defined by equations 1 and 2. These equations are different from the basic linear-elastic relationship. However, the stress equilibrium equations and the displacement-strains compatibility equations remain the same of the linear-elastic case. Thus, the solution of a boundary value problem whose material behaves as viscoelastic can be obtained from the solution of the same boundary value problem whose material behaves as linear-elastic by applying the Elastic-Viscoelastic Correspondence Principle (EVCP). Applying the EVCP is simple: it consists in replacing algebraically linear-elastic constitutive parameters for viscoelastic constitutive parameters in problem’s solution. Such replacing does not have physical meaning if it is done in time domain. Hence, it must be done (except in restricted cases) by applying Laplace Transforms. 2.2 Schapery’s correspondence principle Schapery (1984) has proposed the extended correspondence principle that can be applied to linear and nonlinear viscoelastic materials. Schapery suggests that the constitutive equations for a certain viscoelastic media are the same of linear-elastic case. However, stresses and strains are not physical quantities but pseudo-variables (Lee & Kim, 1998) defined as shown by equations 3 and 4: t

εR =

1 ∂ε E (t − τ ) dτ ∫ ER τ ∂τ

(3)

0

t

σ R = ER ∫ D(t − τ ) τ0

∂σ dτ ∂τ

(4)

where εR = uniaxial pseudo-strain, σR = uniaxial pseudo-stress and ER = reference modulus (usually constant). The great advantage of Schapery’s correspondence principle consists of eliminating the time dependency of material by producing stress pseudo-strain or pseudo-stress-strain curves similar to the linear-elastic behavior. That approach is practical in the case of continuum damage modeling, because it isolates the damage effect on the material during the loading applications. 2.3 Damage growth modeling for asphalt mixes A common way to model the stiffness reduction of asphalt mixes due to fatigue is the continuum damage models. According Teixeira et al. (2007), continuum damage models represent homogeneous alterations in the micro scale of material`s structures and do not require micromechanical analysis. Such alterations (physical, chemical, etc.) are represented by internal state variables, whose evolution is experimentally measured. The authors also relate that the continuum damage models define the internal state variables evolution law based on strain energy. Schapery (1990) applied the method of thermodynamics of irreversible processes to develop a so-called work potential theory applicable to the mechanical behavior of elastic-media with growing damage and other structural changes. This theory represents microcracks occurring during fatigue process in the form of internal state variables. The Work Potential Theory applied to viscoelastic media is composed by three fundamental equations: Pseudo-strain energy density function (defined by equation 5), constitutive relationship (defined by equation 6), and damage evolution law (defined by equation 7).

(

W R = f ε ijR , S 1395

)

(5)

σ ij =

∂W R ∂ε ijR

(6) α

⎛ ∂W R ⎞ S = A ⎜⎜ − ⎟⎟ ⎝ ∂S ⎠ •

(7)

•

where S = internal state variables that account for damage effects, S = damage evolution rate, A and α = positive constants. The other terms were already defined. Schapery (1990) relates that the specific functional form of A is dependent upon the definition of S or on the physical significance of S. For instance, if S represents a crack length, then A is a constant for isothermal and non-aging systems. Since this study focuses on the isothermal and non-aging system, a constant value was used in the analysis. The α parameter is related to the slope m taken from the slope of creep compliance versus the time curve in a log-log scale. Several internal state variables can be applied to use Schapery’s Work Potential Theory. One of them is the damage parameters that can be seen in Lee & Kim (1998). These authors used the damage parameter Sp, calculated by using the physical stresses or strains applied to the material. The number of loading cycles (N) and damage growth parameters are also used. Equations 8 and 9 define Sp to the controlled stress and controlled strain conditions, respectively (Lee & Kim, 1998): Sp =

(∫ σ

Sp =

t

1/ N

(1+ N ) K

0

(∫

t

0

1

)

1+ dt ( N ) K

)

(8)

1

ε R (1+ N )K dt (1+ N ) K

(9)

where Sp = damage parameter and k = parameter related to the material’s crack growth rate according Schapery (1984) defined by equation 10: da k = A ( Jv ) dt

(10)

where a = crack length, Jv = Generalized J integral and A, k = positive constants. 3

EXPERIMENTAL METHODOLOGY

3.1 Accelerated tests All data shown in this study were extracted from Victorino (2008). The accelerated tests were performed by using a Dynatest’s HVS (Heavy Vehicle Simulator) traffic simulator. An axle load of 160 kN was applied to the experimental tracks during the tests, almost twice the standard axle loading (82 kN) taken to pavement designs. A one-way loading application was performed at a speed of 8 km/h (ten times lower than standard heavy vehicle speed on highways). The tire inflation pressure was 700 kPa and the type of tires was 900 × 20 sized tires. The accelerated tests were performed at BR-290 (a Brazilian federal highway) in Rio Grande do Sul, southern Brazil. First, the tests were performed on a traffic lane already trafficked since October 2004 by local traffic. The asphalt layer of these first tests (on Test Section 1, as shown in Figure 2) already was presenting degradation signals (surface cracks). From October 2004 to the beginning of accelerated tests the highway was loaded by 4,000,000 cycles (calculated by using AASHTO’s methodology). 1396

Figure 2.

Test Sections on traffic lanes to data measurements (from Victorino, 2008).

After the tests on Test Section 1, the traffic simulator was transferred to the highway shoulder, a lane with same characteristics than the previous lane. However, that lane was not loaded before and did not have any degradation. Such lane was defined as Test Section 2, as show in Figure 2. In order to collect experimental data, each Test Section was divided into ten 1-m length segments as shown in Figure 2. The four extreme segments (acceleration and no acceleration segments) were excluded from measurements. Then the deflection bowls measurements were performed at five cross sections placed on each Test Section, defined as S1 to S5. The crack length measurements were performed on the yellow areas shown in figure 2. From each pavement Test Section the following data were measured: • Deflection bowls on the cross sections S1 to S5; • Crack length propagation on the yellow areas shown in figure 2; • Asphalt layer temperature. The data described above were taken at different number of HVS loading cycles. The data related to Test Section 1 data was measured at the cycles 0; 66,000; 100,000; 123,000 and 170,000. The data related to Test Section 2 was measured at the cycles 0; 50,000; 125,000; 187,000 and 255,000. The pavement structure was composed of the following materials: a 8-cm asphalt layer (a 5.7% asphalt content conventional HMA), a 15-cm basaltic aggregate base, a 30-cm basaltic macadam subbase, and a 60-cm sand layer on the local subgrade soil. 3.2 Laboratory tests In order to obtain additional data related to the asphalt mix behavior, laboratory tests were performed. Specimens were extracted from the testing lanes then resilient modulus tests and IDT strength tests were performed. In the case of resilient modulus tests, specimens were extracted from the traffic lanes before the loading application begin. After that, the specimens were conditioned to 25oC and tested with a 0.2 second loading time and 0.8 second resting time (according ASTM D 4123, 1995). Time versus displacement curves were obtained from resilient modulus testing, which were used to determine the viscoelastic properties of asphalt mixtures. 1397

4

MODELING METHODOLOGY

The basis of the model used in this study to estimate the effect of the loading speed by using accelerated test data is Schapery’s work potential theory. Lee et al. (2003) proposed to express such theory as shown by equation 11: α1

⎛ ∂WNR ⎞ dS = AmCN ⎜⎜ ⎟⎟ dN ⎝ ∂S ⎠

(11)

where S = internal state variables, N = number of loading cycles, WRN = peak value of the pseudo-strain or pseudo-stress energy density function, CN = variable depending on the time dependency of WR, and Am, α1 = damage parameters. According Schapery (1990), if S represents a crack length Am is constant for isothermal and non-aging systems. In this study S will be taken as the field measured crack length per area, then assuming Am constant. However, the assumption taken to such procedure is to consider just one temperature during all tests. Hence, the average test temperature (21oC) was used in modeling. 4.1 N-dependent crack growth modeling The crack length per area on the pavement surface was measured from each Test section in order to obtain one function which describes the crack evolution of both Test Sections. That way, there was the need of estimating the equivalent number of HVS loading cycles due to the real traffic due in Test Section 1 have been already loaded. This estimate was performed by fitting linearly the crack growth tendency of both Test Sections, then shifting the Test section 1 line in order to overlap the Test Section 2 line as shown in Figure 3(a). The shift value found was 116,904 equivalent HVS loading cycles. Joining both sequences generated the sequence shown in Figure 3(b). As shown in Figure 3(b) there is a value of N where the pavement surface cracking started (50,000 cycles). That

(a)

(b)

(c)

Figure 3.

Fitting of N-dependent crack length per area.

1398

N = 50000

way, the variable accounted for modeling was not the absolute number of loading cycles but the loading cycles after the beginning of cracking ΔN. Thus, the data shown in figure 3(b) are plotted in function of ΔN, and by a power-law fitting the N-dependent crack growth model is obtained as shown in Figure 3(c). 4.2 Pseudo-load modeling Due to available experimental data, an adaptation of Schapery’s correspondence principle was used in this study. The concepts of loading, deflections and Stiffness-flexibility were used instead of stresses, strains, and modulus-compliances concepts. Thus, equation 12 is used to establish the physical load P and the pseudo load PR. t

P R = K Rδ = K R ∫ F (t − τ ) 0

∂P (τ ) dτ ∂τ

(12)

where KR = arbitrary constant stiffness (the value of 1 were used in this study), F = the pavement flexibility (i.e., the deflection related to a wheel loading of 1 N), and P is defined as a time-dependent function shown by equation 13: P (t ) =

Pmax 1 + p1 t − tPmax

(13)

p2

where Pmax is the physical load higher value (80,000 N); p1, p2 = fitting constants, and tPmax = time to P(t) = Pmax. The flexibility F was backcalculated from deflection bowls obtained from field measurements performed on cross sections described in 3.1. The software EVERCALC® was employed to perform these backcalculation analyses. A five-layered pavement was assumed as well as 21°C of standard temperature. After that, the moduli obtained from the four layers under the asphalt layer were used in EVERSTRESS® mechanistic analysis in order to establish a relationship between the inverse of resilient modulus (D) and the pavement flexibility. A power-law fitting as shown by equation 14 best described that relationship.

F = ADb

(14)

where A and b = positive constants. The average value of A was 5.54 × 10–7 (standard deviation = 4.48 × 10–7), and the average value of b was 0.195 (standard deviation = 0.03). International System of units was employed (N and m). 4.3 Viscoelastic parameters Resilient modulus tests were performed using 0.2s loading time in order to determinate viscoelastic parameters for the HMA. A power-law creep compliance curve was assumed as shown by equation 15: D (t − τ ) = B (t − τ )

m

(15)

where B and m = viscoelastic fitting parameters. The EVCP was applied by using the linear-elastic solution proposed by Gonzales (1975) related to the IDT test. The viscoelastic solution is shown by equation 16: u (t ) =

m +1 0.9976v + 0.2692 ⎛ m 6 i !c t B ⎜ c0t + ∑ i =1 i i m + j ⎜ h ∏ j =1 ⎝

⎞ ⎟ ⎟ ⎠

(16)

where v = Poisson ratio (assumed as 0.3 to HMA), h = specimen height, and ci = constants taken from polynomial fitting of the loading pulse L(t), given by equation 17: 1399

L (t ) = ∑ i = 0Cit i 6

(17)

By using equation 16 the constants B and m were obtained in function of the experimental data. The least square method was employed, where B = 2.78 × 10–10 and m = 0.3638 (temperature = 21°C and International system units).

4.4 Energy density function modeling The energy density function was taken as the half product of the pseudo-load PR and the related time-dependent deflection similar to the assumptions by Lee et al. (2003). However, the energy density can be expressed as a function of PR time-dependency β(t) and the deflection-pseudo-load curve slope K(S) as shown by equation 18: 2

W

R

2

R R ⎤ ⎡ Pmax 1 1 ⎡ P (t ) ⎤⎦ 1 2 ⎦ = β t 2W R = β (t ) ⎣ = P R (t ) δ (t ) = ⎣ ( ) max 2 2 K (S ) 2 K (S )

(18)

where: R P R (t ) = β (t ) Pmax

(19)

The K(S) function was taken by dividing the highest PR from each data related to the testing cross sections by the corresponding deflection. The average deflection bowls of each Test Section for different N values were used. The figure 4 shows the resultant curve for the function K(S). The β(t) function (shown in equations 18 and 19) was obtained by integrating equation 12 for different times and loading speed values. The result of that procedure is shown by equation 20: i

⎛ V ⎞ i 6 β (t ) = ∑ i = 0 β i ⎜ ⎟t ⎝ 8 km / h ⎠

Figure 4.

K(S) function.

1400

(20)

4.5 Schapery’s Am and α1 parameters determination Substituting equation 8, the equation in figure 4 and the equation in Figure 3(c) into equation 11, a model to determine the Schapery’s Am and α1 parameters is obtained as shown by equation 21:

(

d S1ΔN S2 d ΔN

)

⎡ ⎛ 0.5⎡PR ⎤2 ⎞ ⎤ ⎦⎥ ⎟ ⎥ ⎢ ∂ ⎜⎜ k +⎣⎢kmax 1 2 ln( S ) ⎟ ⎟⎥ ⎠ = AmCN ⎢ ⎜⎝ ⎥ ⎢ ∂S ⎥ ⎢ ⎥⎦ ⎢⎣

α1

(21)

where CN depends on α1 as shown by equation 22: CN (α1,v ) = ∫

tcycle

0

β ( t,v )

2α1

dt =

CN1θ CN 2α1 + CN 3 V

(22)

8 km / h

where CN1, CN2 and CN3 are equal to 2.625, –4.277 and 0.075, respectively. By using least square fitting on the values 0.000166 (standard deviation = 6.620217 × 10–6) and 0.127318 were found to Am and α1, respectively. These values allow predicting the crack propagation and deflection evolution during the loading cycles for different loading speeds. 5

PREDICTING THE LOAD SPEED INFLUENCE

The Am and α1 parameters allow determining both the crack growth on pavement surface and the N-dependent deflection. Such procedure can be done by isolating S in equation 21 and solving the resultant differential equation expressed by equation 23:

{⎡⎣k1 + k2 ln (S )⎤⎦ S}

α1

(

R ⎞⎡ ⎛ C θ C N2α1 + CN 3 ⎟ ⎢ − k2 Pmax ds = Am ⎜ N 1 ⎟⎟ ⎢ ⎜⎜ V 2 8 km / h ⎠ ⎢⎣ ⎝

)

2 ⎤α 1

⎥ d ΔN ⎥ ⎥⎦

(23)

Integrating both terms in equation 23 results the N-dependent cracking for any loading speed as shown by equation 24: ⎧ ⎛ R ⎞⎡ ⎪ ⎜ CN 1θ C N2α1 + CN 3 ⎟ ⎢ − k2 Pmax ⎪ Am ⎜ ⎟⎟ ⎢ V 2 ⎪⎪ ⎜ 8 km / h ⎝ ⎠ ⎢⎣ S ( ΔN ) = ⎨ b1 ⎪ ⎪ ⎪ ⎪⎩

(

)

2 ⎤α 1

⎥ ⎥ ⎥⎦

1

⎫ b2 ⎪ ΔN ⎪ ⎪⎪ ⎬ ⎪ ⎪ ⎪ ⎪⎭

(24)

where b1 = 0.960816, b2 = 1.071339. That values come from the first term integration in equation 23 according equation 25:

∫0 {⎡⎣k1 + k2 ln ( s )⎤⎦ s}

α1

S

1401

ds = b1S b2

(25)

5.1 Speed-dependent cracking evolution prediction By applying equation 24 it is possible to predict the cracking evolution for any loading speed. The values of Am, α1, A and b were taken from data referent to Test Section 2 and N = 0, where 0.000170, 0.127318, 6.81747 × 10–7 and 0.220322 were assumed to the mentioned parameters, respectively. Figure 5 shows the cracking prediction for some speeds in comparison to field measured data. It is noticed in Figure 5 that as loading speed decreases, pavement crack length increases for a given ΔN. Also it is noticed that cracking rate difference are more notable for lower speeds. Thus, the model reproduces the degradation effect of low speeds on pavement performance as shown in several previous studies about the theme. In order to present the speed degradation effect, Figure 6 presents the number of loading cycles needed to obtain 1 m/m2 cracking length: 5.2 Speed dependent defection evolution The N-dependent deflection evolution is calculated by using equation 26: t ∂P (τV ) pR (t ) ∫o F (t − τ ) ∂τ dτ . δ (t ) = = K (S ) K (S )

(26)

The top deflection evolution depending on loading speed and loading cycles is shown in Figure 7.

Figure 5.

Crack growth for different loading speeds.

Figure 6.

Number of loading cycles necessary to obtain crack length = 1 m/m2.

1402

Figure 7.

Deflection growth for different loading speeds.

Figure 8.

Effect of loading cycles on deflection bowls for different loading speeds.

As the case of crack growth the gradient increases with the loading speed decreasing, being the highest deflection growing rates differences for low speeds. The effect of loading cycles and loading speeds on deflection bowls is shown in figure 8:

6

CONCLUSIONS

Taking into account the results presented during this study, it is possible to make the following conclusions: • It is possible to estimate the loading speed influence on the pavement behavior by using accelerated pavement data, laboratory tests and continuum damage models; 1403

• The results of this study show a behavior tendency alike to the experimental behavior seen in several studies about accelerated testing: increasing in pavement degradation when loading speed decreases. That phenomenon occurs as for cracking propagation as for deflection evolution; • In order to obtain the results mentioned above there was not necessary apply complex numerical models (for instance, finite elements). It was just necessary use variables as load, stiffness or flexibility, and deflections. That deflection could be calculated by using common mechanistic analysis software of pavement structures as EVERSTRESS® and EVERCALC®. For future studies it is suggested the validation of results obtained during this study, as well as developing rutting prediction models that take into account the loading speed influence. The validation of the model proposed during this study surely motivates the developing of new tools for verifying the loading speed influence no pavement structures. That way, such development will lead the engineers to a more rational methodology of pavement design and consequently to more affordable pavement structures.

REFERENCES American Society of Testing and Materials, 1995. Standard test method for indirect tension test for resilient modulus of bituminous mixtures. ASTM D4123-82. 4 p. Boltzmann, l. 1876. Zur theorie der elastichen nachwirkung. Pogg. Ann. Physic, v. 7, p. 624. di Benedetto, H., Partl, M.N., Francken L., de la Roche, C. 2001. Stiffness testing for bituminous mixtures. materials and structures/matériaux et constructions, vol. 34, pp. 66–70. Gibson, N.H., Schwartz, C.W., Schapery, RA. and Witczak, M.W. 2003. Viscoelastic, viscoplastic, and damage modeling of asphalt concrete in unconfined compression. transportation research board (trb) annual meeting cd-rom. Kim, Y.R., Seo, Y., King, M., Momem, M. 2004. Dynamic modulus testing of asphalt concrete in indirect tension mode. Transportation Research Board (TRB) Annual Meeting CD-ROM. Lee, H.J., Kim, Y.R. 1998. Viscoelastic continuum damage model of asphalt concrete with healing. journal of engineering mechanics, ASCE, Vol. 124, no. 11, pp. 1224–1232. Lee, H.J., Kim, Y.R., Lee, S.W. 2003. Fatigue live prediction of asphalt mixes using viscoelastic material properties. 2003 Annual Meeting of the Transportation Research Board. Mello, L.G.R. 2008. A teoria do dano em meio continuo no estudo da fadiga em misturas asfalticas. Phd Thesis, Unisersity of Brasilia, Prazil. in Portuguese. Mostafa, A.E., Al-Qadi, I.L., Yoo, P.J. 2006. Viscoelastic modeling and field validation of flexible pavements. Journal of Engineering Mechanics, Vol. 132, n. 2, pp. 172–178. Schapery, R.A. 1984. Correspondence principles and a generalized j-integral for large deformation and fracture analysis of viscoelastic media, International Journal of Fracture Mechanics, vol. 25, no. 3, pp. 195–223. Schapery, R.A. 1990. A theory of mechanical behavior of elastic media with growing damage and other changes in structure. Jr. mech. phys. solids, 38, pp. 215–253. Siddharthan, R.V., Krishnamemon, N., El-Mously, M., Sebaaly, P.E. 2002. Investigation of tire contact stress distributions on pavement response. Journal of Transportation Engineering, v. 128, n. 2. Teixeira, V.F., Souza F.V., Soares, J.B. 2007. Modelagem da vida de fadiga e do acúmulo de deformações permanentes em pavimentos asfálticos por meio de um modelo de dano contínuo. transportes (rio de janeiro), v. 15, pp. 17–25. in Portuguese. Victorino, D.R. 2008. Análise de desempenho de um pavimento flexível da rodovia br-290/rs solicitado por um simulador de tráfego móvel. MS dissertation, Federal University of Rio Grande do Sul, Brazil. in Portuguese.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Full-scale aircraft tire pressure tests C. Fabre A.IRBUS S.A.S, France

J. Balay Laboratoire Central des Ponts et Chaussées—LCPC, France

P. Lerat Civil Aviation Technical Center, France

A. Mazars Laboratoire Régional des Ponts et Chaussées—LRP, Toulouse, France

ABSTRACT: This paper describes an outdoor full-scale test planned to improve experimental and theoretical knowledge related to the effects of aircraft internal tire inflation pressure on the behavior and damage of flexible pavement. Since modern aircraft can have tire pressures greater than 15 bar, the tests focus on pressures from 15 to 17.5 bar. The experimental pavement located on the Toulouse-Blagnac airport in France will include up to seven al different test sections, representative of current airfield flexible pavement. Variant parameters from one section to another are thickness of AC surface layer and its performance towards rutting, and surface treatment as grooving. The aircraft simulation vehicle will drive four dual-wheel gears spaced enough in order to prevent from any interaction between them, making it possible to test two different tire pressures (15 and 17.5 bars) and two weights par wheel (28.5 and 33.2 tons) simultaneously. The seven test sections will be instrumented in order to measure resilient strains, and resilient and permanent displacements (rutting). The structure have been designed according to the French airport pavement design method, for 10,000 passes of the heavier gear. Test will be performed until the pavement surface damage result in an airport decision to repair. The attempt will be made to isolate pavement failure related to tire pressure effects only, namely the rutting of bituminous layers according to the authors predictions, but not to test the pavement complete failure. After test completion, results will be presented at ICAO level for their consideration. 1

INTRODUCTION

The PCN (Pavement classification number) is mainly driven by the bearing capacity of two types of pavement (flexible and rigid) and for four levels of pavement strength (characterized by the CBR (California bearing ratio) for flexible pavement at the top of subgrade, and by the Westergaard modulus for rigid pavement at the bottom of the slab). In addition, a third code associated to the PCN represents tire pressure limitation (ICAO, 1983): W = No pressure limitation X = 15 bar limitation Y = 10 bar limitation Z = 5 bar limitation. High-tire pressure limitation was initially established by the Australian Air force to prevent damage to asphalt surface runways used by military aircraft with high tire pressure (around 20 bars or more). Later these limitations have been extended to commercial operations regulation. 1405

New aircraft generation (B787/B777/A340/A380 etc.) tend to increase the load per wheel therefore the internal tire inflation pressure above 16 bar in some cases. The current scale of maximum allowed tire pressure is not technically substantiated and not representative of current aircraft with higher gross weights and higher tire pressures. In order to assess the real tire pressure influence on asphalt surface layers, Airbus proposes to carry-out a full-scale test campaign by using the large aircraft vehicle simulator developed formerly in the framework of the AIRBUS Experimental Programs (LCPC, 2002 and Fabre, 2003). Seven instrumented flexible pavement sections including different asphalt concrete surface layers will be specially built for this research program, and trafficked by the heavy simulator. The main goal of this research is to study the influence of internal tire pressure inflation in respect to the permanent deformation (rutting) created by traffic at the surface asphaltic material. The second objective is to collect data on flexible pavement material behavior in regard to heavy loads application. This data will complete the A380 PEP (Pavement experimental program) database. In order to achieve these objectives, the experimental pavement will be equipped with various sensors, which will be installed both during the experimental pavement construction and after its completion. The L/G (landing gear) simulator used during the PEP will operate over the whole length of the pavement. To reproduce the distress of pavement asphalt layers due to new airplane generation such A380 or B777, it is anticipated that the simulator will make between 10,000 and 15,000 passes over the pavement.

2

BACKGROUND

In the ICAO Annex-14 (Volume I Aerodrome design and operations, third edition, 1999) it is stated that: “The PCN reported shall indicate that an aircraft with an ACN (Aircraft classification number) equal to or less than reported PCN can operate on the pavement subject to any limitation on the tire pressure, or aircraft all-up mass for specified aircraft type.” In the ICAO1 Aerodrome design manual Part.3, second edition-1983 (3–24, §3.3.4), the tire pressure category is considered as follows: “Directly at the surface the tire contact pressure is the most critical element of loading with little relation to the other aspects of pavement strength. This is the reason for reporting permissible tire pressure in terms of tire pressure categories. Except for rare cases of spalling joints and unusual surface deficiencies, rigid pavements do not require tire pressure restrictions. However, pavements categorized as rigid which have overlays of flexible or bituminous construction must be treated as flexible pavements for reporting permissible tire pressure. Flexible pavements which are classified in the highest tire pressure category must be of very good quality and integrity, while those classified in the lowest category need only be capable of accepting casual highway traffic…It will usually be adequate, except where limitations are obvious, to establish category limits only when experience with high tire pressures indicates pavement distress.” The main high pressure impacts on poor pavement surface quality (generally linked to pressure limitation) are: Shear failure: Permanent deformation of a surface or soil due to a load on a relatively small surface area, which then sinks into the surfacing. Permanent deformation: Rutting of bituminous materials is exacerbated by high asphalt concrete (AC) temperature, low load moving speed and high shear stresses, Raveling (maneuvering operations): Failure in bituminous surfacing in which aggregates are dislodged and asphalt binder is lost due to high tangential stress or errors in the laying process. Airport operators who published their flexible PCN with a code X or lower letter generally have a poor asphalt surface quality. This results in the high-pressure limit. The tire pressure limitation is not clearly justified, but it is generally considered that high tire inflation pressure mainly affects the AC surface layer rutting. Neither theoretical 1406

or numerical models, nor laboratory tests are operational for rutting prediction, so that we have considered that only full-scale tests on flexible pavement allow the possibility to best assess tire pressure influence on asphalt surface layers. 3

TEST FACILITIES

3.1 Experimental pavement design The experimental pavement will be divided into seven test sections represented by the letter A to the letter G. In order to be representative of standard flexible pavement, the seven test sections have been selected with different surface layer asphalt concrete thicknesses and different material performance in regard with rutting behavior (from low to high rutting performances). Two additional sections will be added on each end of the pavement to park and maintain the vehicle simulator. Each test section will be 7 m long; 25 m wide separated from each other by a 3.5 m neutral zone (see Figure1). The natural soil has a very poor bearing capacity (low CBR). In order to improve the soil bearing capacity, a capping layer (sub-base layer) of 70 cm thick is added on the top of subgrade, with a modulus objective of 70 MPa on the top of this layer (CBR approximately 8 to 12%). The seven test section structures are described below: (Note: definitions are according to French Standards) Test section A – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,20 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,06 m thick, 0/14D class 3, with standard rutting performance. Test section B – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,18 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,08 m thick, 0/14 class 3, with standard rutting performance. Test section C – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,14 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,12 m (2 × 0.06 m) thick, 0/14 class 3, with standard rutting performance. Test section D – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,18 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,08 m thick, 0/14 class 3, with high rutting performance. Test section E = Test section B – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,18 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,08 m thick, 0/14 class 3, with standard rutting performance. Test section F – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,18 m thick, grading 0/14 class.3 – Surface layer asphalt concrete (grooved) 0,08 m thick, 0/14 class 3, with standard rutting performance and grooved surface. 1407

26 cm (11 In)

A

B

C

D

7m E

7m

3.5 m

7m

EAST 3.5 m

7m

105 m

3.5 m

7m

3.5 m

7m

3.5 m

15 m

3.5 m

WEST

F

7m

20 m

G

GB3: Base Layer Asphalt concrete Variable thickness: Depends of surface course thickness Base course + surface layer = 26 cm

SUB-BASE COURSE—Untreated Graded Aggregate (UGA) 40 cm (15.7 In)

SUBGRADE + CAPPING LAYER (70 Mpa / CBR: 8 to 12%)

Figure 1.

Test item cross sections.

Figure 2.

The Airbus aircraft simulator on the Toulouse-Blagnac Airport.

Test section G – Subbase 0,40 m, of UGA (Untreated graded aggregate) 0/31,5 de type 2 – Base layer asphalt concrete 0,18 m thick, grading 0/14 class.3 – Surface layer asphalt concrete 0,08 m thick, 0/14 class 3, with low rutting performance. The pavement structures and materials of sections B and E are identical, in order to verify the homogeneity of the construction procedures and assess the accuracy and the repeatability of the measurement devices. 3.2 Simulator vehicle 3.2.1 Specifications The simulator vehicle selected for tire pressure test will be the same as the one used for the PEP and its technical specification was widely described in the PEP flexible and the PEP rigid brochure (see Figure 2). Specifically, the simulator vehicle concept is modular and can be loaded up to 32 tons per wheel and each module has variable track and tandem distances geometry. Modules can be assembled according to various dimensions in 2 to 5 module arrangements depending on the aircraft L/G represented. Each module is individually loaded with applicable steel plates. A dual cantilever system equally distributes the weight on the wheels 1408

on 6-wheelers to ensure uniform load distribution. In the 4-wheel configuration, a forefront driving diabolo with minimal loading acting as a cantilever distributes load without influencing significantly the instrumentation. The vehicle behaves as a real aircraft on pavement at any specific aircraft maximum takeoff weight (MTOW) at most aft CG main L/G position. The weight of each module results from steel plates visible on figure 2, which the handling is done by mean of a cantilever crane. The vehicle is hydraulically self-powered for trajectory and speed. Nominal taxiing speed is 5–6 km/h. 3.2.2 Configuration The tire pressure influence is assumed to be directly at the surface layer. In our case, the attempt is made to isolate pavement failure to tire pressure effect only. Although strains and displacements will be continuously monitored and followed, the L/G configuration has been selected to avoid wheel and gear interactions in the deepest layers (the distance between wheels and gears is considered sufficient to minimize wheels and gear interaction). The L/G configuration should be capable of simulating two internal tire pressures inflation simultaneously, (15 bar/217 psi and 17.5 bar/254 psi), for loading case and in the same thermal conditions (see Figure 3). The distance between wheels is 1550 mm (wheel axle to wheel axle) and the distance between gears is 5000 mm (axle to axle). Each dual gear is equipped with the same tire (Michelin 1400 × 530R23 40PR) and inflated at the same internal tire pressure inflation. The distance between wheels is sufficient to consider independently the tire pressure influence of each wheel directly at pavement surface. 3.2.3 Loading case Calculated Unloaded pressures are derived from worst-case loads for each landing gear multiplied by the ratio of rated load and pressure for the specified tire: For MLG (Main landing gear) tires, usual worst case is for STATIC LOAD @ MRW & AFT CG conditions, For NLG (Nose landing gear) tires, usual worst case is for STABILISED BRAKING LOAD @ MRW & FWD CG conditions, Worst-case load depends of aircraft landing gear concept: E.g.: For multiple gear (A340, B747, A380) max static loads between flat & cambered runway condition (LG oleo compression for each gear to be considered). In this case, the attempt is to evaluate the tire pressure effect directly at the surface. In order to isolate the tire pressure parameters, it is obviously easier to compare different tire pressure with the same vertical static loads, but aircraft operational internal tire pressure inflation is derived from the tire ratings provided by the tire manufacturer for an optimized use. By using tire ratings, a tire pressure of 15 bar would result in a vertical load of 28.5 t/wheel whereas 17.5 bar would result in a vertical load of 33.2 t/wheel. Comparison of these two loading cases would lead to a rutting severity level higher for 17.5 bar/33.2 t but because of the load itself, and the load limitation is already included in the PCN number. For these reasons, all loading cases 17080 mm 2-W bogie B1 2-W bogie B2 2-W bogie B3 2-W Bogie B4 15 bar/28.5 t 5000 mm 15 bar/33.2 t 5000 mm 17.5 bar/33.2 t 5000 mm 17.5 bar/28.5 t

1550 mm

Figure 3.

1550 mm

1550 mm

Vehicle simulator configuration.

1409

1550 mm

2.0 2.0

25 m

Axle L4 A

B

C

D

E

F

Axle L3 G Axle L2 Axle L1

P1A P2A P3A P1B P2B P3B P1C P2C P3C P1D P2D P3D P1E P2E P3E P1F P2F P3F P1G P2G P3G

Figure 4.

Instrumentation location.

will be covered resulting in over or under inflated conditions for direct tire pressure comparison at the same vertical load and nominal inflated conditions for tire pressure comparison at the nominal loading conditions (nominal means vertical load derived from tire ratings). 4

INSTRUMENTATION

4.1 Localization Three transversal reference profiles have been selected for each test section (see Figure 3). The sensors will be installed following these transversal profiles (P1, P2, P3) and the axles L1-L4 defined by the L/G simulator configuration. 4.2 Type of sensors The first test objective, namely surface rutting survey could have been simply assessed by topography measurement during the test (rut depth measurement). However, to determine the origin of the rutting and to survey the initiation of the damage mechanism, the overall pavement structure behavior against L/G simulator loading must be known (rutting can be initiated by the high tire pressure inflation but also by the vertical load or the combination of load in the deepest layers). These considerations led us to select different sensors capable of monitoring continuously the pavement damage process. The number of channels of the HBM data acquisition system used for the measurement, and cost considerations, were also decisive for finalizing the pavement instrumentation. They led to equip some pavements sections and some landing gear wheel-paths and but not others. The sensors are as follows:

Table 1.

Fixed deflectometers.

Anchored Deflectometers Function: Measurement of the absolute vertical strains on top of the surface Resilient strain (= deflection) and permanent (= overall rut depth) Number = 6 Localization (per test sections and transversal profiles) A

B

C

P1 P2 P3 P1 P2 P3 L4 L3 L2 L1

X X

D

E

F

G

P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 X X

1410

X X

Table 2.

Rutting measurement device.

Rutting measurement device Function: Surface layer thickness variation measurement, Resilient (= surface layer vertical compressive strain) and Permanent (= Surface layer rut) Number = 8 Localization (per test sections and transversal profiles) A

B

C

D

E

F

G

P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 P1 P2 P3 L4 L3 L2 L1

X X

Note 1:

X X

X X

X X

XXX refers to three 3 rutting measurement devices, distance 0.50 m.

4.2.1 Anchored deflectometers For the measurement of absolute vertical strains on top of subgrade layer (see Table 1). The deflectometers will be capable of measuring the resilient vertical displacement (deflection) and the permanent vertical displacement (overall rut depth). A total of six (6) devices will be installed (one section B, D and G, reference lines L2 and L3). 4.2.2 Rutting measurement device For the measurement of the surface layer thickness variation, rutting measurement device will be capable of measuring the resilient thickness variation (surface layer vertical compressive strain) and permanent (surface layer rut). A total of 8 devices will be installed (see Table 2). 4.2.3 Interface marker Interface markers will be used to mark out the interface between the surface layer asphalt concrete and the base layer asphalt concrete (unwoven membranes impregnated with bituminous emulsion, 0.20 m × 0.20 m approximately) in order to survey the rutting of the different by layers by mean of low diameter core sampling). 4.2.4 Temperature gauges Two temperature measure profiles will be installed at different depths (PT100 sensors), plus Air temperature and black body temperature sensors (see Table 3). 4.2.5 Horizontal & vertical strain gauges Horizontal gauges will measure resilient horizontal strain in both longitudinal and transverse direction at three different depths, namely (from bottom to top) bottom of base layer asphalt concrete, top of base layer asphalt concrete and bottom of surface course. Table 3.

Temperature gauges.

Temperature gauges PT100 Function: Temperature measurement (Air temperature, black body and pavement) Number = 18 Localization (per test sections and transversal profiles) A

B

C

D

E

8+2 8

1411

F

G

Table 4.

Horizontal and vertical strain gauges. A P1

L4 L3

L2

P2

P3

B P1

P2

P3

H1 H3 Z1 Z2 Z3 H1 H2 H1 H2 H1 H2 H1 H2 H1 H2 H3 Z1 H3 Z1 H3 Z1 H3 Z1 H3 Z1 Z2 Z3 Z2 Z3 Z2 Z3 Z2 Z3 Z2 Z3

C P1

P2

P3

H1 H3 Z1 Z2 Z3 H1 H2 H1 H2 H1 H2 H1 H2 H3 Z1 H3 Z1 H3 Z1 H3 Z1 Z2 Z3 Z2 Z3 Z2 Z3 Z2 Z3

D P1 P2

P3

H1 H3 H1 H3 Z1 Z3 Z1 Z3

L1 H1 refers to 2 horizontal gauges at bottom of surface layer BB (long. and transversal) H2 refers to 2 horizontal gauges on top of base layer asphalt concrete GB (long. and transversal) H3 refers to 2 horizontal gauges at bottom of base layer asphalt concrete GB (long. and transversal) Z1 refers to a vertical gauge at top of subgrade (Untreated Graded Aggregate - UGA) Z2 refers to a vertical gauge at bottom of subgrade (Untreated Graded Aggregate - UGA) Z3 refers to a vertical gauge at top of Capping Layer

Vertical gauges will measure resilient vertical strain at three different depths, namely (from bottom to top) top of capping layer, bottom of subgrade (UGA layer) and top of subgrade A total of 117 gauges will be installed in the test sections A, B, C and D (see Table 4). These gauges consist of a 10 cm long epoxy resin strip, instrumented with a strain gage and equipped with two perpendicular aluminum bars at each end in order to ensure good anchoring in the material. The instrumentation will be connected to a data acquisition chain unit and continuously monitored and recorded. Some sensors will be directly installed during pavement construction (e.g. rutting measurement devices, vertical and horizontal gauges), and others will be installed after its completion (e.g. anchored deflectometers). 5

TEST PROCEDURE

5.1 Number of coverages and wandering The test campaign will consist in running the simulation vehicle at least 5000 times forwards and 5000 backwards (minimum 10,000, maximum 15,000 passes) with a transversal wandering of ±0.4 m (due to tire footprint width of 0.4 m) along longitudinal tire axis (the wandering magnitude is representative of aircraft movement on apron and taxiway area). To achieve this goal, 5 longitudinal lanes (named A to E), 10 cm wide, will be painted side-by-side along the pavement and used as a guide. The wandering path width is detailed in Figure 4 (only one dual gear is represented): 5.1.1 Pavement condition follow-up Both pavement surface and sub-layers will be monitored during the test using different variables measured with different devices and different modalities. As the tire pressure influence is expected to be directly at the pavement surface, regular stops will be necessary for topography measurement. For each pavement test section, 15 survey pins will be fixed on pavement surface and topography measurement will be made every 1000 passes (every 500 during the first 2000 passes). Other measurements will be made at regular stops such as small diameter core sampling (low diameter) to evaluate the bituminous layer interface condition or laser measurement over the all pavement surface.

1412

P0

P1

P2

Path width 2.35 m

1.55 m

1.95 m

P0

Figure 5.

P3

P4

Lateral wandering position.

5.2 Test temperature Bituminous material behavior is widely influenced by temperature. In order to be representative of normal airline operations, it is very important to test pavement surfaces for a range of values between approximately 0°C and approximately 45°C on pavement surface. Initial simulator passes (up to 1000/2000) must be started during low temperatures (pavement, E-modulus high resistance) to ensure pavement integrity at all levels. 5.3 Failure criteria Every attempt is made to isolate pavement failure related to tire pressure influence only, but not to test the pavement to complete failure as per the A380 Pavement Experimental Programs. Therefore, failure criterion chosen will be the same indicated in the Boeing company report2 on high tire pressure tests. “This failure criterion is to be indicative of sufficient pavement surface damage that would result in an airport’s decision to repair the damage”. Such a decision would be taken on pavement rutting with a medium severity level of 12 to 19 mm (0.5 to 0.75 in.). 6

CONCLUSION & WAY FORWARD

The tests discussed in this paper will complement the Boeing tests and will be submitted at ICAO level, via the AOSWG, Pavement subgroup (PSG). International aviation industry representatives (FAA, BOEING, CAAs) will be kept informed of test progress and would expect ICAO to take advantage of these test results to support a superior and more precise limiting tire pressure criteria methodology more in line with current and future aircraft. The test facilities were initiated in mid-2008 and completed in December 2008. The tests are planned to start in early 2009 (depending on temperature and meteorological constraints) and the final results are expected by the end of 2009/early 2010. REFERENCES ICAO, 1983. Aerodrome design manual, part.3, Pavement, Second Edition. BOEING, FAA, 2006. NAPTF, Report on high tire pressure tests, Atlantic City, NJ, USA. LCPC, AIRBUS, STBA, 2002. The A380 Pavement experimental programme, Web site: http://www.stac. aviation-civile.gouv.fr/publications/catpub04chauss.php Fabre, C., Lerat P. and Balay J.M., 2003. Airfield pavement design, European Road Review, Special issues n°1.

1413

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Comparison of precast and cast-in-place concrete pavements responses under heavy vehicle simulator loads E. Kohler Dynatest Consulting Inc, USA

J. Harvey University of California Pavement Research Center, USA

L. Du Plessis CSIR-Built Environment, South Africa

L. Motumah California Department of Transportation, USA

ABSTRACT: Precast concrete slabs offer an important advantage as a pavement rehabilitation option because they can be opened to traffic immediately upon installation, making them attractive for use on heavily traveled highways and airfields where work windows for repairs or reconstruction are very short. There is a lack of long-term performance information because precast pavements are relatively recent technology. This paper compares results of accelerated pavement tests conducted on precast and cast-in-place pavements. An experiment with a Heavy Vehicle Simulator (HVS) conducted in 2006 on a precast pavement system called the Super-Slab® is compared to previous results obtained in California with conventional jointed cast-in-place concrete pavements. The results indicate that a precast pavement system has similar ranges of service life as jointed concrete pavements. A rough approximation of failure at 200 million ESALs seems valid for both types of pavements, if a slab thickness of 200 to 225 mm is considered. 1

INTRODUCTION

1.1 Precast pavements Precast slabs are being considered more seriously as an advantageous repair method for extending the service life of distressed concrete pavement. Benefits include long life expectancy of concrete slabs cast in factory-controlled conditions and the fact that fully cured precast slabs can potentially be put into use almost immediately upon installation, making them attractive for use on heavily traveled highways where work windows for full-depth repairs are very short. 1.2 Types of concrete pavements The service life that can be obtained from alternative pavement systems is one of the most important factors that agencies take into account when deciding the pavement type for a specific project. Concrete pavements are in general considered to serve longer lives than asphalt pavements, but even the lives of concrete pavements are known to vary among and within the different possible types of concrete pavements. Jointed Reinforced Concrete Pavements (JRCPs) are seldom used today, although they were used extensively in the 1960s. The problem with JRCP is the wide transverse joint openings caused by volumetric changes that are the result of long slabs, and the appearance of transverse cracks caused by friction forces 1415

opposing the volumetric changes. Continuously Reinforced Concrete Pavements (CRCPs) are generally considered the most durable pavements (Smith et al. 1998, Gharaibeh et al. 1999, Moon et al. 2006). There are cases of CRCP serving heavy highway traffic for more than 60 years (Kohler 2007). The use of CRCP is increasing in the United States and in many European countries (Jaszienski 2008). However, by far the most common type of concrete pavement is jointed plain concrete pavement (JPCP). A great deal of field performance data exist for JPCPs that show a wide range of service lives, meaning extraordinary good performance in some cases, and not so good in other situations. For the cases in which JPCPs have not performed as well as expected, the problems are generally attributed to issues during construction, particularly built-in thermal curling, which precludes good support under the slabs. A newer type of concrete pavement, known as Precast Concrete Pavement Systems (PCPS), has gained popularity in the last 6 or 7 years in the United States for use in roadways. However, because its development and use are fairly recent, performance data is not yet available. Although a market exists for PCPS pavements due to the very short construction windows in congested highways, it is important for transportation agencies responsible for selecting the most cost-effective pavement solution to be able to compare the expected lives of PCPS against cast-in-place concrete pavements such as JPCP or CRCP. The purpose of this paper is to provide comparative information regarding the structural capacity of one system of precast pavement and cast-in-place jointed pavements. Given that precast pavements have not been in service for long enough time to see them fail, an accelerated pavement test was conducted in California using a Heavy Vehicle Simulator (HVS). Results from previous experiments with HVS on JPCP allow for a meaningful comparison of JPCP versus PCPS. It must be stated that, although accelerated pavement testing (APT) offers relatively quick and cost-effective answers regarding long-term performance using full-scale systems, there are limitations to APT including the use of overloads to accelerate damage, lack of long-term exposure to the environment and relatively few replicates. 1.3 Precast versus rapid setting concrete One of the main applications of precast concrete is for rehabilitation of jointed concrete pavements, meaning replacement of failed slabs. Concrete pavement contractors prefer the use of rapid setting concrete, as it involves the use of paving equipment and crews that are experienced in conventional concrete pavement construction, as opposed to the risk of new installation technology required for precast slabs. The major constraint when paving on short construction windows is the time necessary for the concrete to gain strength. Kumara et al. (2006) investigated early strength requirements of concrete for slab replacement, loading experimental slabs with an HVS at 6 hours after placement. The study confirmed that having a flexural strength greater than the anticipated maximum induced stress at the time the slab is open to traffic is essential to ensure that the concrete will not fail prematurely. There are products that are being used for slab replacement that can gain strength rapidly, but the issue remains whether a rapid strength concrete can last as long as regular concrete. There is some evidence that show that the fatigue life of regular concrete made with Type I/II cement and fatigue life of fast-setting concretes are comparable as long as the flexural strength is the same, and assuming similar stresses which means that shrinkage must be similar (Kohler et al. 2005). 1.4 Heavy vehicle simulators The HVS is the most common type of accelerated pavement testing device in use today, with approximately ten of these machines in operation around the world. The testing on PCPS and JPCP presented in this paper was conducted using one of the HVS machines that belongs to the California Department of Transportation (Caltrans). Depending on the test being performed, an HVS is capable of simulating up to 20 years of heavy, inter-urban freeway truck traffic in approximately two to three months of operation. It accomplishes this by trafficking the test pavement with almost no interruptions during such a period, and by loading the wheel with up to 2½ times the typical truck wheel load, or up to almost 4 times typical truck wheel 1416

loads when an aircraft tire is used. The dimensions and load capabilities of the HVS, as used for concrete pavement testing in California, can be found elsewhere (Kohler et al. 2007). 2

CALIFORNIA HVS EXPERIMENTS ON PRECAST AND CAST-IN-PLACE CONCRETE PAVEMENTS

2.1 Precast pavements near San Bernardino A precast test pavement was constructed near San Bernardino, an hour east of Los Angeles. It consisted of 10 slabs in a 2 by 5 arrangement. The details of the test slab installation were developed to mirror the pavement details of a potential specific project in nearby highway I-15. The main components of the installation are as follows (Kohler et al. 2006): – – – –

A 150 mm (6 in.) cement treated base. A thin (8 mm) layer of fine bedding material (stone sand). Precast Super-Slabs®, 225 mm thick (9 in.), placed upon the precisely graded sub-base. Grout application at the joints where there are slots for the dowels and tie bars, and application of a second type of grout under the slab (bedding grout). – Diamond grinding of the surface of the slab to meet smoothness requirements of the project. Two test sections were evaluated between June 2005 and August 2006, one on each side of the 2 by 5 panel arrangement, as shown in Figure 1. The main test objectives were to evaluate whether traffic can be safely allowed on newly placed slabs before grouting, to identify how much traffic loading the system can carry (which relates to years of expected service), and to determine failure mechanisms for this type of PCPS. Traffic loading was applied to each section to simulate the exposure to traffic from the time of placement of the slabs to the time of grouting, which would normally occur during the next nighttime closure. After the preliminary loading of the ungrouted pavement, the grouted sections were loaded for extended periods under different conditions in the sequence shown in Table 1 (note that testing in section 1 resumed after finishing section 2). Section 1 was heavily overloaded to cause failure and identify failure modes while Section 2 was utilized to

a) Figure 1. Table 1.

b) Precast pavement testing. a) Placement of a slab, and b) HVS applying traffic loads. Sequence of test and loading conditions.

Section

Duration (months)

Test and load conditions (pavement/tire type/avg load level)

1 1 2 2

3 (June–Sept, 2005) 5 (May–Aug, 2006) 5 (Sept, 2005–Feb, 2006) 2 (Feb–May, 2006)

Dry/Aircraft/120 kN Wet/Aircraft/116 kN Dry/Truck dual/98 kN Wet/Truck dual/93 kN

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Load repetitions (millions)

ESALs (millions)

1.05 0.54 2.33 1.13

163 79 99 43

determine performance under more realistic loads, yet using an accelerated number of repetitions compared to the field. Wet pavement conditions were simulated by applying water directly on the slabs at the joints. Only Section 1 reached the end of its serviceable life, and for that reason the results of Section 2 are presented first. The loading in Section 2 consisted of a total of approximately 142 million ESALs, applied with dual truck tires. No sign of any distress was observable at the end of the dry test (99 million ESALs). The test consisted of two loading conditions, 60 kN and later a 100 kN load level. Once the responses measured by the sensors indicated a stable condition at 100 kN load, water application at the joints was then initiated and loading continued. During the wet part of the test, loading was applied at 60 kN, 80 kN, and 100 kN. No distresses were observable at this stage either, despite the fact that considerable pumping of material from under the slab occurred during the wet trafficking. The pumping of fine sand, however, did not result in any significant rise in corner deflections. An investigation was carried out to evaluate the extent of the suspected voids under the slab caused by pumping. It revealed that the pumped material was comprised of the finer particles from the sand bedding layer and disintegrated bedding grout. There was no clearly observable void in the wheelpath under the joint, but there were widespread channels of washed fines. Loading in Section 1 was applied with an aircraft tire able to apply levels loads above 100 kN. The total number of ESALs applied on this section was 242 million. Corner cracks appeared on both sides of one of the two loaded joints. HVS trafficking under dry conditions was stopped when, after the cracks had appeared, the pavement responses were once again stable. After the wet traffic was initiated, the slabs were able to withstand 79 millions ESALs before traffic was stopped, which was a clear indication of a still sound structural condition of the cracked slabs. Failure of Section 1 was reached in the form of a localized collapse at one of the joints and a more extended corner crack on the other joint. Forensic investigation revealed that the localized failure happened between dowel bars, exactly under the wheelpath. The combined observations point toward concrete fatigue under channelized traffic and the loss of support caused by pumping. The other joint in Section 1 presented a failure that can be considered typical of cast-in-place, with large concrete cracks. Both failed joints in Section 1 are shown in Figure 2. Drill cores obtained from various locations in both test sections indicated very good performance of the dowel grout. There was no sign of looseness of the dowel, which means that the grout was strong enough to sustain the compressive forces of the dowel as

Section 2

Section 1

Figure 2. Pavement condition at the end of the HVS test for Section 2 (not failed) and Section 1 (failed), plus map of cracking including location of MDD, excavation, and cores.

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load was transmitted across the joint. Likewise, there were no signs of de-bonding issues between the grout and the surrounding concrete of the slot. 2.2 Cast-in-place pavements in Palmdale A few years before the precast experiment the use of rapid strength concrete was investigated to evaluate its use for fast new construction of concrete pavements and for rapid rehabilitation (i.e. slab replacements). A series of HVS tests were conducted to evaluate the fatigue behavior of fast setting hydraulic cement concrete pavements (Roesler 2000). Six full-scale pavement test sections were constructed on State Route 14 near Palmdale, about an hour north of Los Angeles. Each section was 70 m long and consisted of approximately 15 slabs. The concrete used for the slabs was an 80/20 blend of Ultimax® and Type I/II Portland cement. Joints were sawed at 90 degrees, and the joint spacing followed an alternating pattern of 3.7, 4.0, 5.5, 5.8 m. It must be emphasized that although a fast-setting hydraulic cement concrete blend was used, the slabs were cured for many months before HVS testing and had reached flexural strengths comparable to ordinary PCC slabs. As stated earlier in this paper, the comparison presented in this paper is not between PCPS and JPCP slabs tested after only a few hours of curing when they have had low flexural strengths, but rather with JPCP slabs that have strengths comparable to typical highway concrete pavement. The pavements in Sections 1, 3, and 5 consisted of plain jointed concrete slabs of various thicknesses, and were tested between July 1998 and May 1999. These three sections were placed on a compacted granular base. Sections 7, 9, and 11 were designed and constructed on 100 mm of cement treated base on top of 150 mm of an aggregate base. The differences among these sections are as follows: Section 7 had no dowels and an asphalt concrete shoulder; Section 9 was constructed with dowels, normal lane width, and a concrete shoulder with tie bars (the tied shoulder was the adjacent lane); and Section 11 was constructed using a widened truck lane (4.26 m instead of 3.66 m wide) and doweled joints. The testing on Sections 7, 9, and 11 took place between June 1999 and December 2001. The main mode of failure observed on all JPCP sections under HVS loading consisted of the development of a longitudinal crack parallel to the direction of traffic but outside the wheelpath. The majority of the cracks started as transverse cracks, but turned into longitudinal or, in some cases, corner cracks. Figure 3 shows typical examples of the cracking observed in the 23 locations tested within the six sections. The longitudinal cracking was found to be associated with built-in curling of the slabs, and to a lesser extent, to the half axle loading. In addition to the use of fast-setting high-early-strength concrete, these pavements were built in desert conditions and under daytime construction. These conditions resulted in top-down shrinkage and thermal cracks (Heath 1999) and high estimated built-in temperature differential values (Rao 2005). Regardless of the inclusion of dowels and tie bars on the North Tangent’s sections, the study showed that slab curling played a major role on the deflections observed under HVS loading, and therefore on the stresses that led to cracking of the concrete. The slabs were slightly curled upwards all along its longitudinal edge which created a cavity between the bottom of the PCC layer and the base. The loss in support from the substructure especially in the proximity of the longitudinal free edge resulted in the development of high tensile stresses at the top of the concrete which in turn caused the slabs to crack in the observed fashion. In general, deflection sensors placed just below the concrete in the base layer close to the edge registered very small deflections, even with the application of test loads greater than 90 kN. Deflections recorded in the base layer were typically less than 0.2 mm, while the surface mounted sensors recorded deflections between 1.0 and 1.2 mm for the same test. This means that the slab was not in complete contact with the base, as less than 20 percent of the surface deflections were passed on to the base layer (Du Plessis 2005). Temperature also played a significant role in the structural behavior of the concrete slab. Daily variations in slab temperatures caused the slabs to go through cycles of expansion and contraction, which had a noticeable effect on the measured load transfer efficiency (LTE) (Du Plessis 2005). During the hot part of the day the slabs expanded, the joints locked up, and LTE values close to 100 percent were commonly calculated. At night, when slab contraction took place, LTE values dropped 1419

Figure 3.

Typical cracks observed in slabs from Palmdale (Du Plessis 2002).

below 80 percent. Also, owing to temperature differentials (temperature at the surface of the slab minus the temperature at the bottom of the slab), the concrete slabs went through curling cycles. High deflection measurements were associated with lower surface temperatures. The advantages of dowels, tie bars, and a widened lane, were clearly illustrated in the study. Even after the application of aggressive 150-kN loading, no obvious LTE deterioration could be detected on the sections constructed with dowels, tie bars, and widened lanes. Although significant cracks developed during the testing period, no significant drop in LTE values could be detected after the formation of the cracks, which is an indication of the effectiveness of the dowels to transfer load across joints, even after extensive joint deterioration. The dowels had a significant influence in controlling slab edge movements. In contrast to this, the sections with no dowels or tie bars experienced significant reductions in LTE due to traffic loads and after the appearance of corner cracks. The damaging effect of repetitive loading caused a significant reduction in the life of the pavement in comparison with the doweled jointed sections. 3

COMPARISON OF STRUCTURES AND TRAFFIC LOADING TO FAILURE

Only one precast pavement type was tested in San Bernardino, while various structures of JPCP were studied in Palmdale. The main structural characteristics of the test sections, including slab thicknesses, and edge support condition are presented in Table 2. Note that JPCP Sections 1 and 3 were constructed with reduced slab thickness of 100 mm and 150 mm, and therefore are not comparable to the precast sections that were 225 mm thick. The slab thickness of the JPCPs was similar to the PCPS slab thickness (see rows a and b in Table 2), and even though the underlying materials do not exactly match (see row c in Table 2), it was considered close enough to compare the performance of the two types of pavements. PCPS and JPCP sections of comparable structure are shown in Figure 4. The particular features 1420

Table 2. Comparison of structure, ESALs, and expected life for precast and cast-in-place pavements loaded with HVS in California.

Summary

PCPS PCPS JPCP section section section 1 2 1

JPCP section 3

JPCP section 5

JPCP section 7

JPCP section 9

JPCP section 11

a. Design slab thickness, mm 225

225

100

150

200

200

200

200

b. Mean measured thickness, mm 225

225

107

163

211

226

221

222

150 AggB

150 AggB

100 CTB 100 CTB 100 CTB 150 150 150 AggB AggB AggB

No dowels None

No dowels Asphalt

c. Underlying structure, mm 150 CTB

150 150 CTB AggB

d. D esign features Load transfer Shoulder Slab size Length, m Width, m

Dowels Dowels No Asphalt Asphalt dowels None 4.57 4.57 3.96 3.96 3.69–5.80 3.66

No dowels None

e. # of HVS tests

1

1

3

5

4

4

3

3

f. Edge Load Factor

1

1

0.050

0.050

0.050

0.050

0.161

0.163

g. Average ESALs, millions

242

142

10

8

45

142

241

187

–

–

4, 4, 22

0, 4, 5, 11, 18

2, 8, 31, 102

39, 48, 35, 162, 115, 363 526

57, 205, 298

80

>47

3

3

12

47

79

61

1–7

0–6

1–34

13–119

12–173

19–98

h. ESALs each test, millions i. Average Years to failure* j. Range of years to failure*

Dowels Tied PCC

Dowels Wide Lane

3.67–5.91 3.58–5.77 3.70–4.03 3.64–5.91 3.62–5.86 4.26 3.66 3.66 3.66 3.66

* Years to failure assumes 3.04 million ESALs per year in design lane.

PCPS

JPCP -5

JPCP -7

JPCP -9

JPCP -11

225 PCPS 8 Bed Sand 150 CTB (dowels & grout)

200 JPCP 150 AggB (no dowels)

200 JPCP 100 CTB 150 AggB (no dowels)

200 JPCP 100 CTB 150 AggB (dowels)

200 JPCP 100 CTB 150 AggB (dowels)

AC Shoulder

AC Shoulder

AC Shoulder

PCC Tied Shoulder

Wide lane

Figure 4. Test sections characteristics for the cast-in-place study, thickness, materials, presence of dowel bars, and edge support conditions.

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of the JPCP pavements are listed in row d, such as the use of dowels in the transverse joints and edge support conditions. The HVS used in these experiments is an Mk III model, which is able to test up to 8 m of pavement, and therefore in most cases three slabs/two joints were evaluated per HVS test. As indicated previously, two HVS tests were conducted in the precast pavement, one on each side of the 2 by 5 slab arrangement. On the JPCP there was room for up to five replicate tests in each section, as shown in row e in Table 2. The total number of Equivalent Single Axle Loads (ESALs) applied to a pavement takes into consideration the various load levels used during the course of an HVS test. The HVS passes are normalized to the passage of an 80 kN axle load through the ESALs calculation. The computation of ESALs in this study was done according to Equation 1, where L is the half-axle load level in kN and ELF is the Edge Load Factor. 4.2

⎛L⎞ ESALs = ∑ ⎜ ⎟ × ELF −1 ⎝ 40 ⎠

(1)

An ELF accounts for the difference in pavement damage caused by a wheel load applied at the edge of the pavement with respect to the damage caused when the load is in the wheelpath. The ELF for the HVS loads to the JPCP sections were determined from an Illinois DOT study (Zollinger and Barenberg 1989). The ELFs are reported in Table 2 in row f. For HVS tests in PCPS the ELF was taken as 1.0, as the wheel load was at the wheelpath, i.e. approximately at 460 mm from the edge, as it can be observed from Figure 2. For the JPCP sections, the wheel loads were at the edge of the slab as it can be seen from Figure 3 (except in the case of the widened truck lane, where the load was 0.6 m from the edge of wide slab, at the edge of the expected truck traffic wander pattern). The ELFs shown in Table 2 are estimates, and should used for rough comparison purposes, and are intended to provide approximate comparisons between the JPCP and PCPS sections. The average number of ESALs that each section was able to sustain before the end of the HVS loading is shown in row g. of Table 2. These are followed in row h. by the ESALs in a given section of all the HVS tests in that section. A wide range of scatter can be seen from the individual test data, associated to the variable field conditions. To make the results more easily understood, the total ESALs were converted in to a number of years in service. This is an arbitrary conversion of the results based on the current traffic on Interstate 15 (I-15) near the site of the precast pavement experiment. The estimate for the design lane at that location is 3.04 million ESALs per year, and this value was assumed constant for the computations (zero rate of increase over the years for traffic volume and axle loads). The trucks per year in the design lane is based on the Average Daily Truck Traffic of 21,425, multiplied by 365 days per year, a 0.5 directional factor and an assumption of a design truck lane factor of 0.8, per the Caltrans Highway Design Manual. The trucks per year information was multiplied by a factor of 973 ESALs/1000 trucks from WIM data from 1991 to 2001 (Lu et al. 2002). The results are presented in rows i and j in Table 2, for average and range respectively and indicate average lives between 3 and 80 years, and ranges from 1 to 173 years. These results provide a relative comparison, and an approximate estimate of actual life for individual slabs, with consideration that long-term exposure to climate is not included in the loading. A graphical representation of the ESALs to failure for the PCPS and JPCP sections is shown in Figure 5. The authors interpret these results as a rough indication that the expected life of precast concrete pavement systems is not much different from what can be expected from cast-in place jointed plain concrete pavements. However, these results should be used with some caution. 4

CONCLUSIONS

Because precast concrete pavement systems are relatively new and have not been widely used, there is a lack of information on the capacity of such pavements to carry large volume 1422

600

ESALs (millions)

500 400 Not loaded to failure

300 200 100 0 PCPS section 1

PCPS section 2

JPCP section 5

JPCP section 7

JPCP JPCP section 9 section 11

Figure 5. Comparison of Equivalent Single Axle Loads for the PCPS and the different JPCP pavements of the study.

of heavy traffic loads. Since field performance data under real traffic conditions does not exist, and because this type of information is needed to provide a preliminary evaluation of the cost-efficiency of the use of precast pavements, this study compared the number of ESALs that precast and cast-in-place jointed pavement resisted under Heavy Vehicle Simulator loads. It must be emphasized that although a fast-setting hydraulic cement concrete blend was used, the slabs were cured for many months before HVS testing and had reached flexural strengths comparable to ordinary PCC slabs, and the comparison presented in this paper is not between PCPS and JPCP slabs tested after only a few hours of curing when they have had low flexural strengths. The results indicated 200 million ESALs is a rough approximation that is valid for both types of pavements, PCPS and JPCP of 200 mm slab thickness. This finding provides a first full-scale experimental comparison regarding a key issue about use of precast pavements, and the results presented are intended to begin to clarify one of the major sources of controversy: which pavement type lasts longer. Unfortunately only two PCPS sections could be tested, and they were loaded differently, which meant no replicate tests, thus precluding assessment of variability. One can speculate that slabs manufactured in a precast plan would be more uniform in terms of thickness and strength, leading to less field variability than with JPCP. The JPCP results confirmed field observations in the sense that JPCP there is considerable variability in performance, some failing (cracking) very early under live traffic, while others lasted considerably longer. The precast experiment showed in one section that after 142 million ESALs a precast pavement may be intact (no cracks or faulting or any other distress), while the other section failed after 242 million ESALs. Transverse or corner cracking was observed in one of the JPCP tests as early as 160 thousand ESALs, while another took up to 536 million ESALs. In sum, based on the limited results presented in this paper, the preliminary assessment is that doweled JPCP and PCPS pavement of similar thickness may be expected to have similar performance and failure mechanisms. 5

ACKNOWLEDGMENTS AND DISCLAIMER

This report was prepared in cooperation with and with funding from the State of California, Department of Transportation. The authors acknowledge Bill Farnbach, Chief, Office of Pavement Engineering, for providing valuable technical oversight during this research work. 1423

The contents of this paper reflect the views of the authors who are responsible for the facts and accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the State of California or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. REFERENCES Du Plessis, L., Bush, D., Jooste, F., Hung, D., Scheffy, C., Roesler, J., Popescu, L. and Harvey, J.T. (2002). “HVS Test Results on Fast-Setting Hydraulic Cement Concrete, Palmdale, California Test Sections, South Tangent”. Report UCPRC-RR-2002-03. Du Plessis, L., Jooste, F., Keckwick, S. and Steyn, W. (2005). “HVS Testing of the Palmdale Test Site, North Tangent Sections: Evaluation of Long Life Pavement Rehabilitation Strategies-Rigid”. Report UCPRC-RR-2005-02. Gharaibeh, N.G., Darter, M.I. and Heckel, L.B. (1999). Field Performance of Continuously Reinforced Concrete Pavement in Illinois, Transportation Research Record—Journal of the Transportation Research Board 1684, pp. 44–50. Heath, A. and Roesler, J. (1999). “Shrinkage and Thermal Cracking of Fast Setting Hydraulic Cement Concrete Pavements in Palmdale, California”. Report UCPRC-RR-1999-07. Jaszienski, A. (2008) Presentation at Workshop “CRCP—Design, Practice and International Experiences” 9th International Conf on Concrete Pavements, San Francisco, California, August 2008. Kohler, E., Ali, A. and Harvey, J. (2005). “Goal 4 Long Life Pavement Rehabilitation Strategies-Rigid: Flexural Fatigue Life of Hydraulic Cement Concrete Beams”. University of California Pavement Research Center Report UCPRC-RR-2005-04. Kohler, E., Du Plessis, L. and Theyse, H. (2006). “Construction and Preliminary HVS Tests of Pre-Cast Concrete Pavement Slabs”. University of California Pavement Research Center Report UCPRC-RR-2006-10. Kohler, E., DuPlessis, L. and Harvey, J.T. (2007). “Evaluation of Technologies for Rapid Concrete Pavement Rehabilitation using Heavy Vehicle Simulators”. International Conference on Optimizing Paving Concrete Mixtures and Accelerated Concrete Pavement Construction and Rehabilitation. Atlanta, Georgia, November 2007. Kohler, E.R. “Accelerated Load Tests of Continuously Reinforced Concrete Pavements and Case Studies of CRCP in the US” Proc. International Conf on Concrete Roads, Midrand, South Africa, August 2007. Kumara, M.W., Tia, M., Bergin, M. and Choubane, B. 2006. Evaluation of Early Strength Requirement of Concrete for Slab Replacement Using Accelerated Pavement Testing. J. Transp. Engr., Volume 132, Issue 10, pp. 781–789. Lu, Q., Harvey, J., Lea, J., Quinley, R., Redo, D. and Avis, J. (2002). “Truck Traffic Analysis using Weigh-In-Motion (WIM) Data in California”. University of California Pavement Research Center Report UCPRC-RR-2002-01. Rao, S. and Roesler, J. (2005). “Characterization of Effective Built-in Curling and Concrete Pavement Cracking on the Palmdale Test Sections”. Report UCPRC-RR-2005-09. Roesler, J., Scheffy, C., Ali, A. and Bush, D. (2000). “Construction, Instrumentation, and Testing of Fast-Setting Hydraulic Cement Concrete in Palmdale, California”. Report UCPRC-RR-2000-05. Smith, K.D., Wade, M.J., Peshkin, D.G., Khazanovich, L., Yu, H.T. and Darter, M.I. (1998). Performance of Concrete Pavements. Volume II: Evaluation of In-service Concrete Pavements. FHWA-RD-95-110. Won, M., Kim, D-H., Cho, Y-H. and Medina-Chavez, C. (2006). “Long-Term Performance of Continuously Reinforced Concrete Pavement in Texas”. Proc International Conf on Long-Life Concrete Pavements, Illinois, October 25–27, 2006. Zollinger, D. and Barenberg, E.J. (1989). “Proposed Mechanistic Based Design Procedure for Jointed Concrete Pavements”. 18, Illinois Cooperative Research Program, University of Illinois, Urbana. Report TES-057 of Project IHR-5.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Field testing of concrete pavements at Chicago O’Hare International Airport Y.-S. Liu & D. Lange University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

ABSTRACT: In concrete pavements, differential temperature and drying gradients cause slabs to curl as shrinkage occurs. Internal stress in concrete is induced when slab corners lift off the ground, making the slabs susceptible to cracking under applied loads. In this study, concrete pavement instrumentation was employed to obtain pavement response data for the purpose of improving the understanding of slab behavior, which leads to confidence in pavement design. The sensor layout design incorporated the full suite of pavement sensors, including lift off gauges, joint opening gauges, and internal temperature and relative humidity sensors. Two testing projects were implemented: the preliminary testing at the Advanced Transportation Research and Engineering Laboratory (ATREL) test facility near the University of Illinois campus, and the field testing at the Chicago O’Hare International airport. In both tests, the expected cyclic diurnal variations and gradients with respect to depth from surface of the slab were observed. The pavement response data were collected and analyzed to infer stress and movement of the slab owing to environmental loads generated by temperature and moisture gradients. Those responses were also used to monitor the occurrence of cracking. 1

INTRODUCTION

It is an ongoing trend that the engineers, designers, and researchers pay more attention to climatic loading and its influence on airport pavement performances. In 1992, the Federal Aviation Administration (FAA) initiated a major research effort to study the in-situ response and performance of Portland cement concrete (PCC) pavements in airports. Static and dynamic sensors were instrumented to collect data under environmental and traffic loadings at Denver International Airport (Dong et al. 1997). The data were processed and stored in an online database developed in that project (Lee et al. 1997). This data has been used to study the environmental factors, mostly temperature, in concrete pavement analysis. Kapiri et al. (2000) evaluated the behavior of Denver International airport concrete pavements due to climatic loading and found changes in the pavement temperature led to significant changes in joint openings, and consequently to the effectiveness in load transfer across joints if the dowels or other load transfer devices were not present. Rufino & Roesler (2006) conducted an experimental analysis of the data from Denver International Airport to determine the effect of the slab-base interaction on concrete pavement responses and discussed that temperature differential effects gap magnitude at the interface which alters contact friction, an important parameter for stress prediction. The use of a fully bonded or unbonded interface assumption will not correctly reproduce measured field responses, especially when temperature curling is present. Besides incorporating temperature into pavement monitoring and modeling, the effect of moisture curling has also been accounted for in concrete pavement studies. Test results at the National Airport Pavement Test Facility (NAPTF) showed concrete slabs developed corner cracking caused by curling (Ricalde & McQueen 2003). Since the slabs were constructed indoors, slab curling due to moisture gradient became distinct from temperature differential. Differential drying shrinkage contributes slab warping, or upward curling, and high tensile 1425

stress occurred on the top surface of slabs due to self-weight. This undesirable predominant tensile stress accelerates cracks when an external wheel load is applied to the slabs. In 2006, an instrumentation system was utilized at Atlanta Hartsfield-Jackson International Airport to monitor the environmental response of the rigid pavements (Brill et al. 2007) to provide information on how temperature and moisture induced slab curling affect rigid pavement life. In the Chicago O’Hare International Airport the instrumentation was also developed for gathering in-situ slab data as part of the O’Hare Modernization Program. This paper presents the field testing located in taxiway L/ZD section cast as part of the south airfield runway 10L-28R extension project. Issues such as power supply and casting method with regard to survivability of embedded sensors will be discussed. In this paper the preliminary testing at ATREL will also be mentioned for its role in verifying the sensor network development and optimizing the technology. 2

PRELIMINARY TESTING PROJECT AT ATREL

Before the instrumentation took place in the pavements at O’Hare airport, the research team constructed a mock up test structure that replicated the nominal design to be used in O’Hare at the ATREL located at the University of Illinois in July 2006 in order to develop and optimize the technology. Three test slabs were constructed for different boundary conditions, i.e. interface bonding and dowelled joints. Figure 1 demonstrates the sensor layout. As shown in the figure, a portion of the slab has a bond-breaker layer (polyethylene sheet) between the asphalt base and concrete slab, while the rest has a natural bond interface. The installed sensors include embedded environmental (relative humidity and temperature) sensors and embedded slab lift-off gages. The joint opening gauges were installed after the casting of the concrete. Data, collected hourly, proved that most of the embedded

Figure 1.

Sensor layout at the University of Illinois ATREL (1 ft = 0.30 m; 1 in. = 25.4 mm).

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environmental sensors work as expected. However, the survival rate of the embedded slab lift-off gages appeared to be undesirable. Some of the sensors that were damaged during construction operations and some were susceptible to moisture penetration problems. These lift-off sensor failures led to a new design of embedded sensors later used at O’Hare airport. Among the recorded data, the internal relative humidity and temperature showed the expected diurnal variations together with a gradient along the depth of slab. The joint opening data also show marked difference in behavior between dowelled and un-dowelled joints. Although only a portion of the lift-off sensors survived the initial casting process, limited inferences about the effects of doweling and interface bonding still can be inferred that for the effect on the slab lift off, both dowelled joints and bonded interface reduced the amount of corner lift off. The results of this preliminary project verified the applicability of a developed sensor network, as well as provided information on improving the instrumentation design for O’Hare airport pavement sensor system. 3

PROJECT LOCATION AND SENSOR LAYOUT AT O’HARE

In October 2007, the instrumentation was installed at the designated location, on taxiway ZD near taxiway L (see Figure 2). The pavements were constructed as part of the south airfield runway 10L-28R extension project. Concrete slab sizes are 6.1 m by 6.1 m (20 ft by 20 ft) and 0.43 m (17 in.) thick. The instrumented sensor system includes environmental profiling sensors, joint opening gauges and corner lift-off gauges (see Figure 3). 3.1 Environmental profiling sensors The sensor unit used for environmental profiling in the concrete was developed at University of Illinois at Urbana Champaign (Grasley 2006). Each unit consists of a Sensirion STH75 digital sensor enclosed by a plastic tube and Gore-Tex as shown in Figure 4. The arrays of sensor units were placed at 13, 25, 51, 76, 152, 254, and 406 mm (0.5, 1, 2, 3, 6, 10, and 16 in.) below the slab surface. 3.2 Corner lift-off gauges The embedded corner lift-off gauges used in the preliminary test program suffered a low survival rate which led to using a different sensor package. The modified design was carry out to meet the following two challenges: (1) slip-form placement of concrete, and (2) water

T/W L

T/W ZD

Slab location

T/W M

R/W 10 extension

Figure 2. Location of instrumented slabs at O’Hare taxiway ZD near taxiway L.

Figure 3. Sensor layout in instrumented slabs at O’Hare airport.

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Figure 4.

Sensors measure relative humidity and temperature profiles.

Figure 5.

Embedded lift-off gauge and housing/bellows.

intrusion and moisture exposure in concrete. The lift-off sensor packages consisted of Macro Sensors GHSA 750 spring loaded LVDT with housing and bellows to improve the ruggedness and water-resistant as shown in Figure 5. 3.3 Joint opening gauges The joint opening gauges also used the GHSA 750 LVDT to measure the displacement. The units were placed after the placement of concrete and the joint being sawed (see Figure 6). 4

DATA COLLECTION STATION

Two types of data loggers were assembled for the instrumentation. A Campbell Scientific CR10X data logger and AM16/32 multiplexer, connected to the LVDTs through signal conditioners Macro Sensors LPC-2000, gathered displacement data hourly. The other measurement system is the field-ready multiplexer developed at UIUC (Rodden 2006) in which the relative humidity and temperature data were recorded from the time of concrete placement and were collected hourly. The instrumented slab and the data collection system were situated in an off-grid location. A self-contained power supply was assembled, which includes solar panels (total rated power 1428

Figure 6.

Joint opening sensors installed after cast of concrete.

40 W, nominal voltage 24 V), a charging regulator and a battery bank consisting of six 12 V deep-cycle batteries in serial-parallel connection, designed for 5 days operation life if not charging. The solar panels were replaced later with a 190 W 24 V high power solar panel to better withstand severe weather condition in winter weather. 5

ENVIRONMENTAL GRADIENTS AND PAVEMENT RESPONSES

Every sensor survived through the slip-form concrete paving operation. Figures 8–10 show plots of selected data. Early age temperature gradient (see Figure 8) demonstrates high internal temperature occurred due to hydration, and the amount of daily fluctuation varied along the slab depth. Early age relative humidity (see Figure 9), on the other hand, remained nearly saturated because curing compound was applied. Figure 10 provides information related to joint crack initiation. The sudden jump in the displacement data captured by the joint opening sensor indicates the time when the crack occurred, which was verified by visual inspection on the same day for joint opening sensor JtOp1. Knowing that the transverse joint cracking did not take place until two weeks after construction and the longitudinal opening was still intact, we can infer that the amount of drying shrinkage in the concrete pavement in this period of time was low, which conforms the relative humidity data mentioned above. The environmental profiles obtained from the instrumentation can be further used to help better understand concrete pavement responses. Figure 11 shows a sample result from ICON, a 3-D finite element software developed at the University of Illinois at Urbana Champaign (Lee 2007), that simulates concrete slab deformation and calculates stress distribution. The slab has a downward built-in curling because the construction was performed under cold weather conditions. The tensile stress appears high at the bottom, and the critical loading pattern could occur at the center of the slab instead of the corners or edges. This example demonstrates the potential incorporation of field testing instrumentation into pavement design models. 6

CONCLUSION

During the sensor system preparation and installation, issues such as sensor ruggedness and power supply were encountered and resolved. An extensive amount of valuable data has been collected. This data includes temperature and relative humidity profiles in concrete pavement, joint opening displacements, and vertical lift-off movements, as demonstrated in 1429

Figure 7.

Data collection station including data loggers, solar panel and battery bank.

Figure 8.

Temperature profile (x-time; y-temperature).

this paper. Useful information is also observed helping us understand how environmental loadings affect the pavement structure. Future analysis will include further integration of various types of data discussed herein, one of which is the ongoing data analysis conducted by using the finite element software ICON. Example results shown in this paper shed some light on the magnitude of slab deformation and stress response experienced by the pavement under environmental loading due to temperature and relative humidity gradients. This information is important with respect to both analyses of the pavement performance and pavement condition for performance prediction and pavement design models. 1430

Figure 9.

RH profile (x-time; y-relative humidity).

Figure 10.

Crack indication (x-time; y-displacement) (1 in. = 25.4 mm).

Figure 11.

Calculated slab deformation and stress distribution.

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ACKNOWLEDGEMENTS This study is funded by the O’Hare Modernization Program (OMP) and conducted in the Center of Excellence for Airport Technology. The assistance and expertise of OMP personnel is gratefully acknowledged. REFERENCES Brill, D.R., Flynn, R. & Pecht, F. 2007. FAA rigid pavement instrumentation at Atlanta HartsfieldJackson International Airport. 2007 FAA worldwide airport technology transfer conference. Atlantic City, New Jersey, USA. Dong, M., Hayhoe, G.F. & Fang, Y.W. 1997. Runway instrumentation at Denver International Airport: dynamic sensor data processing. In Frank V. Hermann (ed.), Aircraft/pavement technology: in the midst of change: 363–378. New York: ASCE. Grasley, Z.C. 2006. Measuring and Modeling the Time-Dependent Response of Cementitious Materials to Internal Stresses. Ph.D. dissertation, University of Illinois at Urbana-Champaign. Kapiri, M., Tutumluer, E. & Barenberg, E.J. 2000. Analysis of temperature effects on pavement response at Denver International Airport. In Shashi Sathisan Nambisan (ed.), The 2020 vision of air transportation: emerging issues and innovative solutions: 124–143. Reston: ASCE. Lee, C.J. 2007. Response of Concrete Structures Subject to Material Aging and Volume Instability. Ph.D. dissertation, University of Illinois at Urbana-Champaign. Lee, X., Hovan, M., King, R., Dong, M. & Hayhoe, G.F. 1997. Runway instrumentation at Denver International Airport: development of database. In Frank V. Hermann (ed.), Aircraft/pavement technology: in the midst of change: 348–362. New York: ASCE. Ricalde, L. & McQueen, R.D. 2003. Portland cement concrete test strip pavement at the FAA National Airport Pavement Test Facility (NAPTF). In Moses Karakouzian (ed.), Airfield pavements: challenges and new technologies: 217–230. Reston: ASCE. Rodden, R.A. 2006. Analytical Modeling of Environmental Stresses in Concrete Slabs. MS Thesis, University of Illinois at Urbana-Champaign. Rufino, D. & Roesler, J. 2006. Effect of slab-base interaction on measured concrete pavement responses. Journal of Transportation Engineering 132(5): 425–434.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Unbonded concrete overlay movements in response to gear loads D.A. Morian, S. Sadasivam & J. Reiter Quality Engineering Solutions, Conneaut Lake, USA

S.M. Stoffels & L. Yeh Pennsylvania State University, University Park, PA, USA

A. Ioannides University of Cincinnati, Cincinnati, OH, USA

ABSTRACT: Full-scale experimental testing of unbonded concrete overlays was undertaken at the Federal Aviation Administration’s National Airport Pavement Test Facility, under a project sponsored by the Innovative Pavement Research Foundation. Three experimental test items with different thickness configurations were constructed and trafficked until failure. The unbonded concrete overlay was separated by an asphalt interlayer from the underlying pavement slab. As a part of this study, several concrete slabs were instrumented with linear position transducers (LPT) to monitor the vertical movement of the slabs in response to environmental and traffic loading. The relative movements of the slabs in response to environmental and applied loads were also evaluated for this same period. LPT gage responses indicated an increased magnitude of downward movement at slab corners relative to the midslab position. However, both corner and mid-slab locations exhibited a steady cumulative downward movement with increasing load when compared to an initial reference position. 1

INTRODUCTION

Unbonded concrete overlays represent a viable and cost-effective rehabilitation option for existing rigid airfield pavements. This approach adds structural capacity and takes full advantage of the support provided by the existing pavement. While unbonded overlays have been used successfully many times, much remains to fully understand how they perform. The Innovative Pavement Research Foundation (IPRF) has an objective of improving the current understanding of the influence of design parameters on unbonded concrete airfield pavements, potentially leading to improve design methods. Accordingly, IPRF issued a project for a full scale experiment. The full-scale experimental testing of unbonded concrete was undertaken at the Federal Aviation Administration’s (FAA) National Airport Pavement Test Facility (NAPTF). The primary purpose of this project was to identify and investigate factors for improving understanding of unbonded concrete airfield overlays for airfields (Stoffels et al., 2008, Khazanovich, 2002). An experimental roadmap which summarized variables affecting overlay performance was developed for the study based on dimensional analysis. The first stage, designated as the baseline experiment was constructed between November 2005 and March 2006 (Stoffels, 2008). An overlay experiment with six test items was constructed having different thickness configurations and joint discontinuities to provide the data necessary to evaluate responses to these conditions with the existing mechanical models. The test items consisted of three unbonded concrete overlay structural sections with matched and mismatched joint

1433

configurations between the overlay and underlay slabs. The underlying slabs were not initially distressed prior to overlay construction, in order to provide a benchmark for deterioration observations, and to support additional experimental overlay stages. An asphalt interlayer of approximately one-inch thickness was placed between the overlay and underlay slabs. One inch diameter dowels were installed along both the longitudinal and transverse joints in the overlay pavement. Three of the test items were each trafficked to failure with dual tandem and triple dual tandem gear loads. The test items were instrumented with vertical linear position transducers, strain gages, thermistors and pressure cells. Mechanical responses from these gages were monitored and collected during the entire study period. This paper focuses on slab movement responses under both dual tandem and triple dual tandem gear loads throughout the loading period until the first visible crack appeared. The major load-related distresses reported in jointed unbonded overlays are corner and linear cracks (Hall et al., 1993). The effect of curling is more pronounced in unbonded concrete overlays than in conventional concrete pavements, as confirmed by a recent study of composite unbonded concrete pavements in Iowa by Cable et al. (2006). The inclusion of these combined effects in fatigue analysis of rigid pavements has long been suggested by several researchers (Darter and Barenberg, 1977, Lee and Darter, 1994, Kuo, 1998, Yu et al., 2004). Currently, only two existing fatigue models incorporate the effects of both loading and environmental factors (Rao and Roesler, 2005). 2

LAYOUT OF EXPERIMENTAL SECTIONS

The test pavement constructed at the NAPTF was 91.4 m (300 foot) long and 18.3 m (60 foot) wide on a controlled subgrade with a target CBR of 8. Plate load test results indicated a modulus of subgrade reaction on the subgrade of 135 psi. The pavement consisted of three structural sections with different thickness combinations of overlay and underlay slabs. The three structural sections were: 1) 229 mm of PCC overlay on 152 mm of PCC underlay, 2) 190 mm of PCC overlay on 190 mm of PCC underlay and 3) 152 mm of PCC overlay on 254 mm of PCC underlay. An asphalt interlayer of approximately 25 mm thickness separated the overlay slabs from the underlay slabs. The experimental plan provided two test items for each structural section. These were designated as North (N) and South (S) with triple dual tandem loading of the north, and dual tandem loading on the south. Each test item consisted of 12 overlay slabs approximately 3.81 m on a side. The size of the underlay slabs varied between 2.6 m and 5.0 m long to create matched and mismatched joints between the overlay and underlay slabs. The schematic illustration of test items is shown in Figures 1 and 2, while Table 1 summarizes the test items. Figure 1 shows the longitudinal length of the overlay and underlay slabs with longitudinal joint discontinuities. Figure 2 shows the transverse width of the overlay and underlay slabs including the transverse joint discontinuities.

Figure 1. Longitudinal cross-section of pavement with overlay, dowels, interlayer, underlay, base and transition slabs (slab length dimensions are shown in feet).

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NORTH

SOUTH

5

10

12.5

12.5

12.5

12.5

12.5

12.5

12.5

12.5

5

6-inch P-154 Aggregate Base

Figure 2. Transverse cross-section of pavement showing longitudinal joint mismatch of overlay and underlay joints (slab width dimensions are shown in feet). Table 1.

3

Summary of test items.

Test item

Structural section

Overlay slab thickness, mm

Underlay slab thicness, mm

Loading gear

N1 N2 N3 S1 S2 S3

1 2 3 1 2 3

229 190 152 229 190 152

152 190 254 152 190 254

Triple dual tandem Dual tandem Triple dual tandem Dual tandem Triple dual tandem Dual tandem

LOADING

The NAPTF test vehicle was configured to apply the triple dual tandem gear to the north test items and dual tandem gear to the south test items. The spacing between dual wheels was 1.372 m and the spacing between axles was 1.448 m with 606.5 kPa tire pressure. One wander pattern applied by the test vehicle consisted of 66 passes at nine carriage positions, or tracks. The transverse position of the carriages shifted by 254 mm between passes to simulate vehicle wander. The zero track was located such that the outside wheel was immediately adjacent to the longitudinal joint of the overlay centered within each test item. Figure 3 shows the carriage positions of loading tracks relative to overlay and underlay joints. Full-load trafficking began on July 25, 2006 at a wheel load of 22679.6 kg. A total of 2046 passes (31 wanders) was applied until the first occurrence of visible cracking on August 1, 2006. In this paper, corner slab movements measured by the linear position transducers (LPTs) are considered between these dates. The loading history for this period is provided in Table 2. 4

ENVIRONMENTAL RESPONSE

The scope of this paper is confined to overlay LPT response data for six selected LPTs from the north test items and three from the south test items. Test item transducers representing the north side are designated CN1, MN1, CN2, MN2, CN3 and MN3, where the letters ‘C’ and ‘M’ represent corner and mid-slab transducer positions and N1, N2 and N3 designate the specific test item. Similarly, test item transducers on the south side 1435

Under lay

Figure 3.

Over lay

Carriage positions of tracks relative to underlay (left) and overlay joints (right). Table 2. Loading history from July 25, 2006 to August 1, 2006. Date

Daily passes

Cumulative passes

7/25/2006 7/26/2006 7/27/2006 7/28/2006 7/31/2006 8/1/2006

132 396 396 264 594 264

132 528 924 1188 1782 2046

are designated CS1, CS2 and CS3. No mid-slab transducers from the south test items were included. Corner transducers CN2, CN3, CS1, CS2 and CS3 were located in the proximity of loaded slab corners with matched joints, while CN1 was located at a mismatched joint. Transducers reported responses to both environmental and test vehicle loading. Relative slab movements, as measured by the six pairs of LPTs, were evaluated for the period from installation until the first day of loading to isolate environmental effects. Relative movement was calculated for each individual LPT by comparing daily values to a unique reference value established for each LPT. Positive differences indicate downward movement measured by the LPTs, while negative differences indicate upward movement. Figures 4 and 5 depict the relative movement of the corner and mid-slab LPTs, respectively. Measurements for analysis were captured between 5:00 a.m. and 7:30 a.m. which corresponds with the maximum daily negative temperature differential in the test facility. Corner measurements during environmental loading only generally exhibited a net upward movement trend. The exceptions were test items N3 and S3 (the thinner overlay slabs), which exhibited a net downward trend. The mid-slab measurements exhibited a net downward movement trend similar to the corner transducers. In both cases, the downward movement became more pronounced after ramp-up loading (limited loading at lower load levels) that took place during the first week of July. 5

CHANGES IN SLAB POSITION WITH ACCUMULATED LOADING

The selected transducer responses under load were collected with each loading pass. Figure 6 illustrates the load response of CS1, which represents slab response to each loading pass 1436

Ramp-up loading

Relative movement, mm

−0.8 −0.6 −0.4 −0.2 0.0 0.2 0.4 0.6 0.8 7/21/2006

7/14/2006

7/7/2006

6/30/2006

6/23/2006

6/16/2006

6/9/2006

6/2/2006

5/26/2006

5/19/2006

5/12/2006

5/5/2006

4/28/2006

4/21/2006

4/14/2006

4/7/2006

1.0

Days CN1

Figure 4.

CS1

CN2

CS2

CN3

CS3

Relative movement of overlay LPTs.

Ramp-up loading

Relative movement, mm

−0.4 −0.2 0.0 0.2 0.4 0.6 0.8 1.0

7/21/2006

7/14/2006

7/7/2006

6/30/2006

6/23/2006

6/16/2006

6/9/2006

6/2/2006

5/26/2006

5/19/2006

5/12/2006

5/5/2006

4/28/2006

4/21/2006

4/14/2006

4/7/2006

1.2

Days MN1

Figure 5.

MN2

MN3

Relative movement of mid-slab LPTs.

within a typical loading wander pattern set. The figure indicates that the movement of a slab under the dual tandem load peaked at passes 5 and 13, which correlate with Tracks 0 and 1 when the corners are most directly loaded by the gear. This pattern is typical of all the south side test items. A similar pattern was observed for Tracks 0 and –1 for the north test items. Figure 6 also illustrates a trend of cumulative downward movement with increasing number of load passes. A total of 31 wanders (2046 passes) were applied during the loading period. Figure 7 illustrates the cumulative responses of corner LPTs CN1, CN2 and CN3 with load passes. The figure indicates increasing movement with cumulative load applications. The rate of movement change differed for individual test items. CN1 exhibited the highest and CN3 the lowest cumulative movements in response to accumulated loading. The net increases in corner movement for the three slabs represented by CN1, CN2 and CN3 during the loading period were 0.75 mm, 0.53 mm and 0.16 mm. 1437

0.00

0.1

0.05 0.10

0.2

0.15 0.3 0.20 0.4 0.25 0.5

0.30

0.6

0.35

Relative movement of concrete slab at loaded corner, mm

Peak deflection under load, mm

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 0.0

0.40

0.7 Number of passes Deflection under load

Figure 6.

Relative movement

Load responses and relative movements of CS1 in a typical wander pattern set.

Cumulative movement from loading, mm

1.20 Recovery period 1.00

0.80 CN1 CN2 CN3

0.60

0.40

0.20

0.00 0

330

660

990

1320

1650

1980

2310

Loading passes

Figure 7.

Cumulative corner movement measurements during loading from north test item LPTs.

Figure 8 illustrates the movements of the south test item slab corners under dual tandem loading. The trends exhibited here are similar to those observed for the north test item slab corners. The total corner movements for CS1, CS2 and CS3 from 2046 load passes were 0.4 mm, 0.3 mm and 0.44 mm, respectively. The cumulative mid-slab movements for the north test items over 2046 loading passes were 0.15 mm, 0.21 mm and 0.06 mm for MN1, MN2 and MN3 as shown in Figure 9. The increase in mid-slab movement magnitude under continued loading was not as significant as the increase in corner movements. The movement plots indicate that a mild recovery was observed in the movement magnitudes during a twoday rest period between passes 1188 and 1193. Pass 1188 was the last Track 0 pass on July 28, 2006, and 1193 was the first Track 0 pass on July 31, 2006. No trafficking occurred between these two days. Figure 10 shows both mid-slab and corner LPT measurements from the first to the final load passes. The relative measurements of each LPT were referenced to a specific gage position after construction. Increasing values (positive) of relative movement indicate downward movement of the slab, while decreasing values (negative) indicate upward movement. The slab 1438

Cumulative movement from loading, mm

1.20 1.00

Recovery period

0.80 CS1 CS2 CS3

0.60 0.40 0.20 0.00 0

330

660

990

1320

1650

1980

2310

Loading passes

Figure 8.

Corner movement measurements from the south test item LPTs.

Cumulative movement from loading, mm

1.20

1.00

0.80 MN1 0.60

MN2

Recovery period

MN3 0.40

0.20

0.00 0

330

660

990

1320

1650

1980

2310

Loading passes

Figure 9.

Mid-slab movement measurements from the north test item LPTs.

corner movements associated with CN1, CN2 and CN3 exhibited downward movements, measuring 1.01 mm, 0.91 mm and 1.01 mm, respectively. The mid-slab movements associated with MN1, MN2 and MN3 also indicated downward movements of 0.74 mm, 0.64 mm and 0.82 mm, respectively. 6

EVALUATION OF SLAB SHAPES

The relative difference in elevation between the slab corner and the mid-slab location indicates the residual slab shape resulting from both environmental and traffic load effects. Observed curling and warping trends represent the resultant slab shape under the early morning conditions each day. Positive differences in elevation indicate downward curl/ warp; that is, the corner elevation of a slab is lower than the mid-slab elevation. Negative differences in elevation indicate upward curl/warp; that is, the corner elevation is higher than the mid-slab elevation. Since both thermal and moisture effects are present, 1439

Loading passes 0

330

660

990

1320

1650

1980

2310

0 0.2 Recovery period

0.4

Elevation, mm

0.6

CN1 MN1

0.8

CN2

1

MN2

1.2

CN3 MN3

1.4 1.6 1.8 2

Figure 10.

Movement trend from the north test item LPT measurements.

–0.3 Early morning trends

–0.2

Relative difference in elevation, mm

–0.1 Late afternoon trends

0 0.1 0.2

CN1–MN1

0.3

CN2–MN2 CN3–MN3

0.4 0.5 0.6 0.7 0.8 0

330

660

990

1320

1650

1980

2310

Loading passes

Figure 11.

Relative differences in corner and mid-slab elevations with loading passes.

the combined effects on slab shape are observed. Figure 11 presents the relative differences in elevation versus the cumulative number of load passes. Figure 12 presents the relative elevation differences recorded chronologically. The shape of the slabs can be inferred from Figures 11 and 12. Before the commencement of loading, the thick slab N1 had curled down, the thin slab N3 had curled up and the slab N2 had remained almost flat. A general trend that the slab corners tend to steadily accumulate downward movement under repetitive loading can be observed in Figure 11. Upon loading, the applied weight generally has the observed effect of pushing the slab corners down irrespective of its original shape. In addition, the diurnal effects of environmental factors on slab shape can also be observed. The slab corners tend to curl up during the early morning hours and curl down during the late afternoon hours. 1440

3.0

1.0

10/20/2006

10/6/2006

9/22/2006

9/8/2006

8/25/2006

8/11/2006

7/28/2006

7/14/2006

6/30/2006

6/16/2006

6/2/2006

5/19/2006

5/5/2006

−1.0

4/21/2006

0.0 4/7/2006

Relative vertical position of LPTs in a fully instrumented slab, mm

2.0

−2.0 −3.0 −4.0 Date of LPT data N3-4 NW corner

Figure 12.

N3-5 NE corner

N3-9 center

N3-11 SW corner

N3-12 SE corner

Relative differences in corner and mid-slab elevations with time.

Figure 11 shows broken and solid lines, indicating upward curling in early morning and downward curling in late afternoon, respectively. In Figure 12, the sensors representing loaded portions of the slab exhibit downward movement during the period of loading. The sensors representing unloaded portions of the slab exhibit upward movement. Inspection of associated cracking records reveals development of a longitudinal crack between mid-slab and sensors N3-11 and N3-12. The observed uplift associated with these corner sensors represents the interaction of the cracked slab with slab bending across the adjacent doweled joints. When there is a break in loading, the individual slabs are observed to partially recover from the load-induced movement. The slab corners tend to return to their original position (compounded by environmental effects), but complete recovery is not observed from the load pattern applied to the pavement. It is reasonable to expect that the magnitude of this recovery could depend on the duration of the rest period, with a longer break in loading resulting in greater recovery. From observations of relative movements in the overlay and underlay slabs (not discussed here), it appears that this recovery may be at least partially attributed to the asphalt interlayer. Further investigation into the role of the asphalt interlayer and the underlying slabs is beyond the scope of this paper. Several possible factors may affect the cumulative rate of slab movement including pavement thickness configurations, load magnitude, gear configuration, wander pattern, number of loading cycles, and slab thermal and moisture gradients. 7

CONCLUSIONS AND OBSERVATIONS

Using LPT response measurements, the responses of the concrete overlay slabs indicated a cumulative increase in downward movements at both corner and mid-slab locations with increasing load repetitions. The weight of loading apparently creates a downward movement of slab corners, regardless of the original slab shape. Curling and warping movements of slab corners were observed in addition to these long term movement trends. While curling and warping trends can be identified prior to physical trafficking, once trafficking began the slab corner movements became intermixed. During extended interruptions in loading, a partial recovery from the overall downward movement was observed. The amount of recovery may depend upon the duration of 1441

interruption in loading compounded by environmental factors. One potentially important observation from this experiment was that the asphalt interlayer may play an important role in the observed recovery. This cannot be concluded at this time, since the accumulated downward slab movement and recovery can be attributed to a combination of the concrete structural deterioration, subbase and subgrade deformation, and potentially the viscoelastic response in the asphalt interlayer. REFERENCES Cable, J.K., Morud, J.L. and Tabbert, T.R. 2006. Evaluation of Composite Pavement Unbonded Overlays: Phase III, Center for Transportation Research and Education, Iowa State University, Iowa. Darter, M.I. and Barenberg, E.J. Design of Zero-Maintenance Plain Jointed Concrete Pavement, Report No. FHWA-RD-77-111, Vol. 1, Federal Highway Administration, McLean, VA. Federal Aviation Administration, BAKFAA Pavement Backcalculation Program. June 2005. http:// www.airporttech.tc.faa.gov Hall, K.T., Darter, M.I. and Seiler, W.J. 1993. Improved Design of Unbonded Concrete Overlays, Fifth International Conference on Concrete Pavement Design and Rehabilitation, Purdue University. Khazanovich, L. 2001. Improved Concrete Overlay Design Parameters for Airfield Pavements Report, DOT/FAA-01-G-002-2, published by the Innovative Pavement Research Foundation for the Aviation Administration, Washington, D.C. Kuo, C.M. 1998. Effective Temperature Differential in Concrete Pavements, Journal of Transportation Engineering, Vol. 124-2. Lee, Y.H. and Darter, M.I. 1994. Loading and Curling Stress Models for Concrete Pavement Design, Transportation Research Record 1449, Transportation Research Board, National Research Council, Washington, D.C. Rao, S. and Roesler, J.R. 2005. Characterization of Effective Built-in Curling and Concrete Pavement Cracking on the Palmdale Test Sections, Research Report UCPRC-RR-2005-09, Institute of Transportation Studies, University of California, Davis. Stoffels, S.M., Morian, D., Ioannides, A., Wu, S.S., Sadasivam, S., Yeh, L. and Hao, Y. 2008. Improved Overlay Design Parameters for Concrete Airfield Pavements, Innovative Pavement Research Foundation, Final Report, IPRF Project FAA-01-G-002-04-2, Skokie, IL. Stubstad, R.N., Jiang, Y.J. and Lukanen, E.O. 2006. Guidelines for Review and Evaluation of Backcalculation Results, FHWA Report No. FHWA-RD-05-152, Federal Highway Administration, McLean, VA. Yu, H.T., Khazanovich, L. and Darter, M.I. 2004. Consideration of JPCP Curling and Warping in the 2002 Design Guide. Paper presented at 2004 TRB Annual Meeting, TRB, National Research Council, Washington, D.C.

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Case histories

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Idaho Airport saves time and money with full-depth reclamation G.E. Halsted Portland Cement Association, Bellingham, Washington, USA

ABSTRACT: The rehabilitation of old asphalt pavements is often an expensive process, especially if the pavement has base or subgrade problems and a simple overlay will not result in a long-term solution. This was the case of a local airport in the town of Hailey, Idaho who rebuilt their only runway in barely 30 days time and saved over one million dollars in the process. The airport followed a construction procedure called full-depth reclamation (FDR) using Portland cement, which allowed the old deteriorated asphalt pavement to be recycled and stabilized; creating a new base that will provide an excellent foundation for long-term pavement performance. This paper will discuss the background, time constraints, alternate pavement design options, cost comparisons, construction techniques employed, and the successful outcome of the rehabilitation of the Friedman Memorial Airport runway. 1

INTRODUCTION

When asphalt pavements fail, determining the best rehabilitation procedure can be difficult. A simple asphalt overlay or a “mill and fill” approach can improve the appearance of the pavement surface, but may do little to correct the problems that caused the failure in the first place. Within a short period of time the problems will likely reappear. Long-term solutions to failed asphalt pavements include a thick structural overlay or complete removal and replacement of the existing base and asphalt surface. A third choice, recycling the failed asphalt pavement through a process called full-depth reclamation (FDR) can provide the benefits of reconstruction without the substantial costs and environmental concerns. This procedure pulverizes the existing asphalt and blends it with underlying base, subbase, and/or subgrade materials, which are mixed with a stabilizing additive and compacted to provide a new stabilized base. A new surface is then applied, which completes the FDR process, providing a new pavement structure using recycled materials from the failed pavement. Through stabilization, the new base will be more uniform, stronger, and provide better long-term performance than the original pavement. In selecting a stabilizing additive, factors that must be considered are the quality of the subgrade support soils, the type of materials to be stabilized, the purpose for which the stabilized layer will be used, the type of improvement desired, the required strength and durability of the stabilized layer, and the economic and environmental impacts. The use of Portland cement as a stabilizer is extremely effective at bonding particles together, reducing permeability, and improving compaction. A comparison of flexible pavement rehabilitation strategies is shown in Table 1. These strategies address the correction of base course deficiencies and are not intended for use when a surface course repair is warranted such as simply recycling the asphalt layer. The cost advantages of recycling materials from the original pavement are obvious; however, there are environmental advantages that are important to the FDR process. These include 1) the conservation of aggregates that must be quarried and transported to the project site, 2) the conservation of land areas that would be used to dispose of the asphalt and base materials from the failed pavement, and 3) the reduced air pollution, traffic congestion, and damage of nearby roadways resulting from hauling new materials to the site, and disposal of old materials.

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Table 1.

Characteristics of flexible pavement rehabilitation strategies.

Solution

Advantages

Disadvantages

Thick structural overlay

• Provides new pavement structure • Quick construction • Only moderate traffic disruption

• Elevation change can present challenges for existing drainage or lighting structures • Large quantity of material must be imported • Old base/subgrade may still need improvement • High cost alternative

Removal and replacement

• Provides new pavement structure • Failed base and subgrade are eliminated • Existing pavement profile/ elevation can be maintained

• Long construction cycle resulting in inconvenience to users • Increased congestion due to construction traffic • Rain or snow can significantly postpone completion • Large quantity of material must be imported • Old materials must be dumped • Highest cost alternative

Full-depth reclamation with cement

• • • •

• May require additional effort to correct subgrade problems • Some shrinkage cracks may reflect through bituminous surface

• • • • •

Provides new pavement structure Fast construction cycle Minimal change in elevation Minimal material transported in or out Conserves resources by recycling existing materials Traffic returns quickly Rain does not affect construction schedules significantly Provides moisture- and frost-resistant base Least cost alternative

FDR is most appropriate where 1) the pavement is seriously damaged and cannot be rehabilitated with simple resurfacing, 2) the existing pavement distress indicates that the problem likely exists in the base or subgrade, 3) the existing pavement distress requires full-depth patching over more than 15 to 20 percent of the surface area (agencies all over the United States responsible for pavement maintenance have experienced that it is cheaper to reconstruct an entire pavement rather than place full-depth patches when these percentages are exceeded), and 4) the pavement structure is inadequate for the current or future traffic. 2

BACKGROUND

After a pavement is selected as a candidate for FDR, a field evaluation should be performed to determine what materials and their proportions make up the current pavement structure. The best way to determine this will be to sample the proposed project. How frequently the samples should be taken depends on how variable the existing pavement is. Sampling can be done using a coring rig or a jackhammer for the asphalt and an auger or post-hole digger for the base and subgrade. At each location the thickness of the asphalt layer should be determined. If a core is taken it can be visually examined to see the condition of the asphalt and the size of the aggregate (see Figure 1). Digging below the asphalt with an auger or post-hole digger will allow for 1446

Figure 1.

Core samples from Friedman Memorial Airport showing stripping damage.

similar sampling of the base and subgrade materials. From a representative location, a sample of pavement materials should be taken back to the laboratory to perform a mix design. The thickness design for a reclaimed pavement is similar to that for a new pavement structure. The American Association of State Highway and Transportation Officials procedure for pavement design, for example, uses a Structural Layer Coefficient to model base materials. Thickness design procedures that follow a more mechanistic-empirical process can also be used (PCA 2001). The new cement-stabilized base from the FDR process will normally be between 6 and 12 inches (150 and 300 mm) in depth. The ability of a pavement base to carry loads depends on the strength of the base material and the depth of the base layer. A thin, but strong base can theoretically carry the same load as a thick, but weaker base. However, the thin, strong base should be avoided because it can become brittle and fracture, resulting in reflection cracks in the pavement surface. When selecting thicknesses for FDR pavements, a thicker base with less strength should be preferred. Designing the proper amount of water and cement for the stabilized base is not only important to obtain a good final product but it also provides important information for quality control during construction (PCA 1992). Research has shown that cement-stabilized materials have better strength and performance when they are well compacted, so determining compaction density is fundamental to the design procedure. Compaction density is determined through ASTM International (ASTM) D558 and is a common (as well as inexpensive) procedure for most construction testing labs. The amount of water and cement required in the mix will depend upon the project specified strength and gradation of the final blend obtained from pulverizing the asphalt during construction and mixing it with the base material. Typical specifications for pulverizing call for 100 percent passing the 3 in. (75 mm) sieve, a minimum of 95 percent passing the 2 in. (50 mm) sieve, and a minimum of 55 percent passing the No. 4 (4.75 mm) sieve. Using the optimum moisture content from the moisture-density test, a series of FDR specimens are prepared at different cement contents to determine compressive strength. Typically, three cement contents are chosen (ranging from 2 to 8 percent by dry weight of the material). It is recommended that a minimum of two specimens be prepared for each cement content. These specimens are moist-cured for seven days, and then tested for unconfined compressive strength (UCS) according to ASTM D1633. This will give a range of strength results in which to determine the required cement content. 1447

In general, a cement content that will provide a seven-day UCS between 300 and 400 psi (2.1 and 2.8 MPa) is satisfactory for most FDR applications. Higher strengths may be required if it is determined that the base materials are moisture sensitive, or that special conditions exist that warrant more strength. The main reason for limiting the strength is to keep the cement-stabilized base from becoming too brittle. Experience has shown that high strengths can cause additional shrinkage cracks to reflect through the pavement surface. The construction process for FDR is straightforward. The process begins by pulverizing the existing asphalt pavement (see Figure 2). Care should be taken to ensure that underground utilities and other obstructions are located and not within the depth of pulverization. Shallow utility structures such as manholes and valve boxes must be worked by hand but usually do not pose problems for contractors. Modern equipment can pulverize to depths exceeding 18 in. (450 mm), but the difficulty lies with getting compaction deeper than 12 in. (300 mm). If the depth of pulverization exceeds 12 in. (300 mm), then the material should be windrowed and compacted in two or more lifts after treatment. Once the existing pavement has been pulverized and blended together, the material is then graded to the desired elevation and shape. Portland cement is then spread over the pavement material in a controlled manner by spreader trucks that are designed for this operation. Cement is most commonly applied dry but can also be applied in a slurry form from a distributor truck equipped with an agitation system. Most specifications call for the application of cement in terms of weight per area (e.g., pounds per square yard (kilograms per square meter)). Mixing is performed by the reclaimer/mixer, either by injecting the proper amount of moisture into the mixing chamber (see Figure 3), or by placing water on the ground with a water truck in a separate operation. In either case, obtaining the correct amount of moisture is very important to achieve the target compaction. After the materials are well mixed, it is time for compaction and final grading (see Figure 4). Smooth-wheeled vibrating rollers or tamping rollers can be used to provide initial compaction, with smooth-wheeled or pneumatic-tire rollers used to complete the operation. Once the cement is mixed into the pulverized base material with water, the maximum time allowed for compaction is two hours. Proper curing is very important to the quality of the final product. If the base is allowed to dry, it will develop cracks, and the continued gain in strength over time will be compromised.

Figure 2.

Pulverizing the failed asphalt pavement at Friedman Memorial Airport.

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Figure 3.

Water being injected during mixing at Friedman Memorial Airport.

Figure 4.

Final grading at Friedman Memorial Airport.

Compacted and finished FDR contains sufficient moisture for adequate cement hydration. The newly constructed base should be kept moist (by lightly watering or misting) for a 7-day period, or a moisture-retaining cover or curing compound can be placed over the FDR soon after completion to retain the moisture and permit the cement to hydrate. If the pavement will have an asphalt surface, a bituminous prime coat can be applied at any time, as this will act as a curing membrane. The finished CTB surface is kept moist until the curing compound is applied. At the time of application, the CTB surface should be free of all dry, loose, and extraneous material. The completed FDR base can have any type of pavement surfacing (e.g., chip seal surface treatment, hot-mix asphalt, or concrete). The surfacing can be applied as soon as the FDR 1449

base is stable (does not rut or shove) under construction traffic. The time required for this can range from 4 to 48 hours. 3

FRIEDMAN MEMORIAL AIRPORT PROJECT PROFILE

3.1 Overview Central Idaho attracts a steady flow of visitors and new residents. The local airport in the town of Hailey relied on their consulting engineers, an experienced contractor (one of three bidders), and a soil-cement specialist to rebuild their one and only runway in barely 30 days time. While some local airports shut down for up to twice that length of time, the Friedman Memorial Airport selected FDR with portland cement as the preferred method to meet a master plan objective and also economically re-open for traffic in the shortest possible time span. 3.2 Investigation Project analysis began in the spring of 2006, nearly a year before actual runway construction work was accomplished. Toothman-Orton Engineering Company, a Boise, Idaho-based civil engineering firm, discovered significant asphalt deterioration after core samples were taken. Like many flexible pavements, there were a number of asphalt layers that had been placed on top of each other throughout the years. Of the 23 cores that were cut out of the existing runway, 19 indicated that the asphalt was in worse condition than expected. Even though the top layer of asphalt was rated in decent shape, the lower layers had been subjected to a deterioration called asphalt stripping. Stripping is a common type of asphalt damage, caused when moisture and traffic loads cause the asphalt cement to separate (or “strip”) away from the aggregate. Airport management realized that a pavement base problem existed that required the attention, monitoring, and eventual action that a surface course repair approach would not address. 3.3 Airport master plan The Hailey, Idaho vicinity attracts a steadily growing stream of visitors throughout the year and summer visitors exceed winter numbers even with Sun Valley ski resort nearby. This fourseason recreational area contributes to Friedman Memorial Airport’s needs to efficiently handle air traffic of all kinds. The Airport projects traffic to grow 44 percent by 2022, the target date of their long-term master plan. Aircraft operations are projected to increase from 57,888 in 2002 to around 83,800 in 2022. To meet this need, there is a strong likelihood that during the course of the next ten years or so a new airport will have to be developed and opened to replace the existing facility. Thus, there was no need for a complete runway reconstruction. 3.4 Diagnosis The airport board, management staff, and engineers initially thought that simply milling off some of the existing old asphalt and then adding an overlay would suffice for several years until the airport master plan could be implemented with a new facility. However, a more thorough pavement analysis proved useful. When the first group of cores alerted the experts to potential problems with asphalt stripping, Toothman-Orton then performed a further investigation with initial assistance from geotechnical engineers at STRATA and then Terracon that confirmed that attention had to be given to the deteriorating underlying asphalt layers. 3.5 Constraints Airports such as the one in Hailey, Idaho, have to minimize closure time. Airfield Operations Chief Pete Kramer recognizes that their summer volume is busier than winter and that a long closure directly affects tourist, convention, and conference traffic as well as the local 1450

economy. Friedman Memorial Airport management set a 30-day maximum construction time (runway shutdown) limit around which engineers and contractors had to complete the remedial pavement work. That critical parameter guided the consulting engineers as they evaluated their options. 3.6 Pavement design options Based upon airplane traffic and the underlying soils, engineers at first calculated three different asphalt-based pavement options. Conventional concrete paving was not considered as longevity was not required because of the planned total airport replacement within the next ten years or so. Initially, a standard Federal Aviation Administration (FAA) design was considered along with two other pavement sections. When none of these first three options could be constructed within a 30-day construction period, engineers approached the FAA and requested consideration for FDR. After FAA engineering expressed willingness to consider FDR, an additional pavement option was developed with input from Terracon. The four pavement alternatives considered are shown in Table 2. The standard FAA option and Alternatives #1 and #2 required roughly 45 to 50 days of runway downtime—outside the time frame established by the airport. Dave Mitchell, Project Manager with Toothman-Orton realized that they had to find a way to perform the necessary work and get it done within 30 days. Toothman-Orton enlisted the engineering expertise of Terracon who consulted on an FDR analysis and design so that their joint engineering effort could propose FDR for this airport runway application. The proposed FDR option (Alternative #3) cut 18 working days off the schedules of the other pavement rehabilitation options. Additionally, FDR allowed them to attain the 30-day goal in a sustainable fashion, as the process recycles resources already in use and also eliminated an estimated 4,000 truck trips that would have been a huge negative impact on the community. 3.7 Cost The big surprise was that the consulting group’s advice to airport management to use FDR would cut their costs over a million dollars when comparing all four possible pavement scenarios. Once the consultants proposed Alternative #3 to FAA engineering and received approval (Federal airport funding was involved) and then proposed the option to the five member Airport commission and received their approval to proceed, the project went to bid in early 2007. 3.8 Construction The low bidder was Western Construction, Incorporated who mobilized earth-moving equipment in order to start immediately after the Friedman Memorial Airport closed its sole runway Table 2.

The four pavement alternatives considered at Friedman Memorial Airport.

Standard FAA pavement

Pavement alternate #1

Pavement alternate #2

Pavement alternate #3

15.00 in (375 mm) #P154 subbase

0.00 in (0 mm) #P154 subbase

0.00 in (0 mm) #P154 subbase

0.00 in (0 mm) #P154 subbase

6.00 in (150 mm) #P209 crushed stone base

14.00 in (350 mm) #P209 crushed stone base

0.00 in (0 mm) #P209 crushed stone base

12.00 in (300 mm) FDR with cement base

4.00 in (100 mm) #P401 asphalt

4.00 in (100 mm) #P401 asphalt

14.50 in (363 mm) #P401 asphalt

6.00 in (150 mm) #P401 asphalt

25.00 in (625 mm) total section

18.00 in (450 mm) total section

14.50 in (363 mm) total section

18.00 in (450 mm) total section

1451

Figure 5.

Aerial view of Friedman Memorial Airport during FDR construction.

on April 23, 2007. Despite some late snowfall the previous week that caused some concern, weather conditions cooperated with the schedule and the project was completed by the May 23, 2007 deadline. Western selected Valentine Surfacing Company from Vancouver, Washington to perform the actual FDR work on 73,440 square yards (61,405 square meters) of runway. Approximately 6,900 feet (2100 meters) of Hailey’s 7,500-foot (2286 meter) airport runway had to be reworked (Figure 5). Chuck Valentine, President, recounted that his crew took five days to grind and five days to mix using two CMI pulverizing machines, a PR1200 and an RS800 along with a cement spreader truck and other typical grading equipment. A 2.0 percent cement rate (by dry weight of the pulverized material) was used at the start of the project but was adjusted slightly to 2.3 percent as construction proceeded to adjust for an increase in soil moisture. The FDR material was uniformly compacted to a minimum of 98 percent of maximum dry density. Field density of the compacted material was determined by nuclear method in the direct transmission mode (ASTM D2922). 3.9 Precision surveying and global positioning system technology The FAA requires a tight surface tolerance on completed pavements, allowing only +/– 0.02 foot (+/– 0.006 meter) deviation from Plan elevations. To meet this requirement, ToothmanOrton approved Western’s use of millimeter Global Positioning System technology. This technology uses a receiver on each end of a motor grader blade that receives signals from a satellite and a ground-based unit to determine its position in space and automatically raise or lower each end of the blade. Knowing that the FDR process is quick, requires precision the first time, and that crews can’t come back the next day, Western retained the services of Butler Engineering and Land Surveying to build terrain models with surveying data from the airport while also assigning experienced project engineers to oversee the work.

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Figure 6.

3.10

Completed runway at Friedman Memorial Airport.

End result

The Friedman Memorial Airport reconstruction project was successfully completed within the required 30 days (see Figure 6). No serious problems were encountered on this project, leading airport Operations Chief Pete Kramer to now recommend the FDR with cement process to other airport operators who want to minimize their runway reconstruction closure times to bare minimums. REFERENCES Portland Cement Association (PCA) (2001). “Thickness Design for Soil-Cement Pavements.” Design Procedure, PCA, Skokie, Illinois, 5–9. PCA (1992). “Soil-Cement Laboratory Handbook.” Details of Soil-Cement Test Methods, PCA, Skokie, Illinois, 14–27.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Mitigating unbound roadway rutting caused by groundwater movement V. Diyaljee GAEA Engineering Ltd, Canada

ABSTRACT: This paper addresses the rutting of a section of gravel surfaced roadway constructed in a 5 m cut section. Subsequent to its construction in 1999/2000, this roadway exhibited large and deep ruts under traffic resulting in mitigative treatments consisting of the installation of perforated pipes, replacement of wet material with large rock boulders, and the use of woven geotextiles. However, these treatments proved unsuccessful resulting in the eventual closure of the roadway. A geotechnical investigation undertaken in 2004 showed that groundwater movement was primarily responsible for the severe rutting of the roadbed. The site conditions were improved in 2005 by installing a deep trench drain encapsulated in a woven geotextile and impermeable membrane composite within one of the existing roadway ditches. Overall, this case study illustrates the value of a proper geotechnical investigation and that the use of geotextiles without proper diagnosis of the problem does not always lead to success. 1

INTRODUCTION

Shortly after its construction in 1999/2000, a 400–500 m stretch of a relocated section of the gravel surfaced Wolf Lake Road within the Province of Alberta and in the vicinity of Wolf Lake Provincial Park had to be closed to traffic as a result of severe rutting of the roadbed. This road closure resulted in traffic being re-routed to the original roadway alignment. The location of the original and relocated roadways in relation to Wolf Lake is shown in the aerial photograph, Figure 1. Wolf Lake Road facilitates primarily the movement of people and goods associated with the Forestry and Oil related sectors, as well as recreational traffic to the Wolf Lake West Provincial Park, and is under the jurisdiction of the County of Yellowhead. To combat the rutting problems, the County of Yellowhead made attempts to stabilize the roadbed using large boulders, geotextiles and cross drainage. However, these stabilization measures proved unsuccessful since they were undertaken without the benefit of any geotechnical investigation being undertaken. This approach was essentially “a seat of the pants” one, whereby a remedy is often applied if it proved successful in the past to combat problems that appeared visually to be similar or familiar. More than often, this approach works, but not always. This case is one whereby the distress manifestations would suggest reinforcement to remedy the cause of the problem, but for ground conditions that would be different than those which were present at this site. In 2004, the County of Yellowhead, the jurisdiction responsible for the roadway finally solicited a geotechnical investigation to determine the nature and cause of the problem and to determine suitable remedial measures. The findings of this investigation and the measures taken to enhance the stability of the roadbed are presented. The investigation clearly shows the importance in carrying out a proper investigation to determine the cause of a problem and to use this information to determine and design suitable remedial measures. Complete details of the investigation undertaken are provided in the project geotechnical report (GAEA 2004). 1455

Figure 1.

Showing original and relocated roadways, Wolf Lake and No-name Creek.

The scope of this work included a site review, field and laboratory work, analyzing of the findings, determination of the cause of instability, recommended remedial measures, and implementation of these measures. The lack of success of a geotextile and associated drainage measures for stabilization is also discussed in relation to the findings of the investigation. 2

SITE REVIEW—INFORMATION FROM OBSERVATIONS AND DISCUSSIONS

A site review of the distressed section of roadway was undertaken in May 2004 in the company of the Superintendent of Works of the County of Yellowhead. The objective of this review was to undertake a visual inspection to observe the prevailing site conditions for an overall understanding of the site, and for planning the proposed geotechnical investigation. At the time of the review the roadway showed significant rutting distress and ponded water on the roadway surface (see Figure 2). Observations also indicated water to be flowing in both roadside ditches (see Figure 3). Based on the observation of dry roadway surface conditions beyond the distressed section, the water on the grade and in the ditches was judged to be originating from springs. As the roadway was in a cut section, it was surmised that flows could be following the natural trend of drainage from the west toward Wolf Lake to the east. It was also observed that a No-name Creek to the south (see Figure 1) was flowing full and it was reasoned that this Creek was spring fed as well. During the site review, the Superintendent of Works indicated that remedial work was undertaken by the County since 2000 to alleviate the rutting problem. This work consisted of the placement of a woven geotextile placed about 300–450 mm below the existing roadway grade as reinforcement and applying surfacing gravel. The observation of two transverse 150 mm diameter perforated CSP pipes with their inverts at ditch level suggested that water was likely noticeably present at the time. This presumably warranted the installation of the pipes during the initial construction or at the time of undertaking remedial works. This was seen as an attempt to effect drainage of the roadbed to create a more stable grade. It should be noted that these opinions are based on site observations and on-site discussions since no historic records on the construction or any remedial measures were available for review from the County of Yellowhead. 1456

Figure 2.

3

Severe rutting and water.

Figure 3.

Water flowing in ditches.

GEOTECHNICAL INVESTIGATION

3.1 General Originally intended to be a single investigation consisting of backhoe test pitting, the investigation was later extended to the drilling of testholes for the installation of piezometers to monitor water levels and for a better understanding of the nature of the stratigraphy and ground conditions with depth. These investigations are described and the results obtained and inferences made are presented. 3.2 Test pit investigation—field work Backhoe testpitting was undertaken on June 14, 2004 using a Case 580 rubber tired backhoe. Thirteen (13) test pits were dug within the distressed section of roadway in a random fashion, but mainly in the rutted areas. The test pits were logged and left open until the end of the day when water levels were checked. A site topographical survey was undertaken during the same period of the test pitting and the stations, offsets and elevations of the testpits were recorded and are summarized in Table 1. The relative locations of these test pits are also shown on the plan drawing in Figure 4. 3.3 Laboratory work Eleven (11) samples were taken from three testpits and tested for moisture content and Atterberg Limits. At two locations (TP 5A and TP 5B) samples were taken from about 250 mm from the surface to a depth of 1.0 m to determine the variation of moisture content with depth. These results showed slightly higher moistures within the top 0.5 m of grade but there were no distinct trends. Overall, the values ranged from a low of 14 to a high of 19% and were about 12% lower than the respective plastic limits. The low moisture content values obtained did not seem to be consistent with the observations made in the field since with natural moisture contents much lower than the plastic limits, one would not have expected the extent of rutting distress occurring in the grade. 4

SUMMARY OF GROUND CONDITIONS OBSERVED FROM TEST PITS

The results of the test pit investigation show that the materials encountered in the roadbed within the top 3 m were fairly consistent in nature and that water was present under some pressure within the grade. Seepage was noted at various depths in the testpits with water levels attaining a height of 1 m below the roadway surface. 1457

Figure 4.

Relative locations of test pits.

Table 1.

Test pit locations, elevations, seepage depth.

Test pit #

Station

Offset from centre of road

Ground elevation (m)

Depth of pit (m)

Depth of water/ seepage (m)

1 2 3 4 5 5A 5B 5C 5D 6 7 8 8A

0 + 382 0 + 382 0 + 382 0 + 450 0 + 486 0 + 489 0 + 522 0 + 522 0 + 574 0 + 615 0 + 626 0 + 265 0 + 270

4.0 m rt 2.0 m lt 6.0 m lt 3.0 m lt 4.0 m lt 4.0 m lt 3.0 m rt 3.0 m rt 5.0 m rt 4.0 m rt 3.0 m rt 4.0 m rt 2.0 m rt

96.20 96.20 96.20 97.00 97.20 97.25 97.40 97.40 97.50 97.55 97.55 94.20 94.60

3.0 3.0 3.0 3.2 2.5 1.5 2.5 2.5 2.6 2.8 2.6 2.0 2.0

2.90 2.90 2.90 2.20 2.00 1.40 1.30 1.40 1.4 & 1.8 1.80 1.5 & 2.2 No seepage 1.1 & 2.0

Figure 5.

Geotextile and water in TP 5B.

Figure 6.

1458

Geotextile and seepage in TP5.

The material encountered in all test pits consisted of essentially a wet clay, gravel sand and silt mixture within the top metre of the roadway. This material is generally of glacial till origin which is prevalent in the Alberta landscape. Woven geotextile was encountered at approximately 0.3 m with cobbles and boulders present underneath (Figs. 5 and 6). It was also observed that at the bottom of the geotextile/soil interface the soil was wet. This wetness could not be attributed to surface water infiltration. Shattered sandy silty shale was encountered below this depth to a depth of 3 m where the test pits were terminated. Except for Testpit 8, water was observed in the remaining test pits to be seeping in at depths varying from 1.1 to 2.9 m below the ground surface. Water in the shale appeared to be under pressure at a few locations as inferred from flows into the test pits. 5

TEST HOLE DRILLING

Following the review of the results of the test pits, it was determined that testhole drilling would be required to evaluate the ground water conditions and the soil stratigraphy below the depth of testpit investigation. The County approved this work on July 22, 2004 and the investigation was undertaken on July 29, 2004. A total of eight (8) test holes were drilled between Sta 0 + 300 and Sta 0 + 630. Test holes were done on the backslopes as well as within the roadway to depths varying from 6 to 9 metres. All test holes, excepting test hole (TH) 4 for the pneumatic piezometer installation, were taken into shale. This shale layer varied from dry to wet. The wet shale was in a fractured state and water was observed within the fractures. The intent of the holes on the backslopes was to determine the water level outside of the roadway prism and hence to obtain some idea of the original water level before the roadway was cut. The stratigraphy encountered in each testhole was similar to that encountered in the test pits. Standpipes were placed in four (4) of the boreholes while three (3) pneumatic tips were placed in TH 4 (Sta.0 + 485, 6 m rt) at depths of 1, 3 and 4.5 m below ground level. The standpipes and piezometers were read a couple of hours after the drilling and the standpipes again on August 6. No further readings have been taken of the standpipe piezometers. The pneumatic piezometers were read on July 29, and November 8, 2004. The tip located at a depth of 4.5 m provided a pore pressure indicating a head of 1.4 m above ground level. The tip at 1 m showed zero pressure when read while the tip at 3 m depth showed a water level at 2 m below ground. In the drilling of this testhole to a depth of 6.2 m, it was noted that the water level rose to a depth of 2.5 m within an hour taken for completion of the drilling operation. This observation, along with the pore pressure at the depth of 4.5 m, and flowing water in the ditches further suggested that the site was subject to “artesian” or “sub-artesian” conditions. During drilling, a note was made of the depth at which water was first noted on the augers. At that depth, water started to flow quite rapidly in the testholes thereby establishing the water table within a couple of hours after standpipe piezometers were installed. Very little variation was found between the water levels recorded on site during drilling and those taken on August 6. In general, the ground responded in similar fashion to water movements as when the test pits were dug, i.e., rapid flows into the test pit when the water bearing strata was punctured. Water levels recorded a few hours after drilling were not significantly different from the levels recorded after about eight (8) days. The water levels varied from 0.9 m in TH 4 to 3.7 m in TH 1. The establishment of the water table in such a short time is indicative of the permeability of the underlying strata, which from visual examination consisted of clayey silt and sand (till) above fractured shale. SPT blow counts were taken in TH 6 at Sta 0 + 630 to determine the consistency of the roadbed and shale subsoil layers. The SPT blow count in the roadbed was 16 while that in the shale was in excess of 80. The roadbed was in a medium stiff state, which is typical of compacted material. The shale layer was in a very stiff state. While the shale was very dry in the upper layer at 3 m, wet layers were encountered at 4.8 and 6 m depth. Drier conditions were observed in the shale layer in other testholes. 1459

The recovered SPT sample from TH 6 was examined in the field. This sample showed, as suspected, an inner core that was much wetter than the outsides of the sample. In this wetter section, the material was sandy and silty. This confirmed the opinion that water was moving through the material by capillary suction given the characteristics of the material, which allow rapid capillary movement to take place hence providing the wet condition above the water table. The water being under a head also helps to move the moisture readily to the capillary zone. 5.1 Site photographs during test hole drilling A number of photographs were taken on site during the drilling operations. In contrast to the time the testpits were done the roadbed was very dry and flows in the ditches were somewhat smaller. Photographs of features that were thought to provide clues to the behaviour of the road. As noted in Figures 9 and 10, water was again observed at the surface of the roadbed despite the prevailing very sunny and dry conditions. 5.2 Laboratory work This consisted of undertaking moisture content tests on samples from various depths within the testholes. Twenty moisture contents were done on samples from depths from 1.5 to 9 m. The moistures to the depth of 3 m varied from 10 to 21% while the moisture at greater depths varied from 18 to 39%. From these results it was noted, in general, the trend was for the moisture content to increase with depth. In comparing the moisture contents obtained with those obtained during the testpitting, the magnitudes were generally within the same range of those of the testpit samples at corresponding depths. 5.3 Assessment of findings of test hole drilling The shale layer was mapped from the drill holes in the transverse and longitudinal directions since it was felt that the shale layer though water bearing in some instances provided a plane over which the ground water travelled. In the transverse direction, the shale was mapped as sloping toward Wolf Lake and within the roadbed it was around 5%. In the longitudinal direction, the slope was about 1.5% in the southerly direction. This information confirmed the initial suspicion that the water was moving from the higher ground to the left or west of centreline to the east i.e., toward Wolf Lake. Further, this movement was also toward the centreline culvert in Figure 1, where the culvert drains water from the No-name Creek toward Wolf Lake. The preferred direction of flow is from west to east as the slope of the shale is greater in this direction. However, field observations and review of the site contour disposition suggested that there was some seepage travelling to the roadway from the east around the middle of the

Figure 7.

Seepage channels on sideslope.

Figure 8.

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Close-up of small seepage channels.

Figure 9.

Wet location in roadbed surface.

Figure 10.

Free water on surface of grade.

distressed area. Hence, while the flow in the east ditch is primarily derived from water flowing from the west via through the roadbed as shown by the erosion scar/runnels in Figures 7 and 8, there is a small amount that is derived from flow from the east to south. This observation was an important feature in determining the nature of the remedial measure for the site. 6

OVERALL EVALUATION AND ASSESSMENT OF PROBLEM

Based on the findings of the testpit and testhole information and observations, the problem associated with this roadway was one resulting from the capillary zone above the established water table becoming saturated by capillary water. Saturation of this zone is promoted in this project primarily by the soil type (pore size distribution), traffic loading, and head of water below the ground. This capillary water cannot be removed by gravity as it is held by surface tension forces and hence results in weakening of the grade. Generally, in most typical roadway designs the road height is kept at a minimum of 1 to 1.5 m above the ditch line to ensure that water does not migrate to the surface by capillary movement. While this type of design may prove successful in relatively flat ground and in situations where the water table is deep, the same satisfactory performance is not readily obtained in hilly ground charged with water. Cuts and side-hill fills are especially prone to problems with moisture movement and generally require careful geotechnical analysis during the preliminary soil investigation stage. In hindsight, if this area were evaluated at the design stage from a geotechnical perspective then certain features would have been evident. One solution may have been to keep the grade line high or if this was not possible from a geometric perspective then the use of subsurface drains at the construction stage may have been recommended. However, despite the best understanding at times, we often choose to use the “wait and see” approach since, in many instances, the ground at times responds quite differently than what is anticipated. If this occurs then the projected expenditure may be saved. This is often the type of approach often taken in the treatment of frost heaving areas i.e., wait until they occur then decide on treatment, if required. With the condition that exists at this site, in the wintertime, this water will travel upwards as frost penetrates the ground. Hence, it is expected that this road would be generally mushy after spring thaw. As a result of the silty and sandy nature of the soil within the top 2 m of the roadbed and the proximity of the water table to the roadway surface, movement of moisture upwards is expected to be much quicker in comparison to a roadbed that was comprised of a clay of medium to high plasticity, since the permeability of this material would be lower. 1461

There was a thought of excavating and replacing the top 2 m of the roadbed material with clay. While a seemingly attractive solution, several aspects showed that this would not be a desirable solution. Apart from the fact that this material type is not readily available within close proximity of the site and that removal and replacement of at least the upper 2 m of material would be a costly exercise, the water would not be completely sealed by the clay from moving upwards. In time, though much longer than in the present circumstance, the water would continue to migrate upwards and would establish a water table similar to the one which exists now. This would result in the upper clay layer eventually being weakened with time as the water slowly moves upwards and saturates the clay layer. Any cracks or fissures in the clay layer would also cause water to migrate upwards even faster. One of the dangers (side effects) of this approach in blocking natural seepage would be its effect on the stability of the backslopes. The water table in the backslopes would increase and could result in their instability. That this is not occurring at this site at this time is a result of the water being free to flow from the slopes. Another side effect is the weakening of the clay layer, which would result in roadway performance problems of different proportions. As a result of the above reasons, it was felt that the long-term behaviour of this option was not predictable, and suitable as one that would allow the water to drain/flow in a controlled manner.

7

PREFERRED REMEDIAL MEASURE

The preferred solution to the problem of this site was the installation of subsurface drainage along the two roadway ditches to a depth of 5 m. The effect was to drawdown the water table deeper than presently existing. The depth of drain to effect satisfactory drawdown of the water table was based on the nature of the problem, observations made on the locations of seepage during the testpit and testhole investigations. The pipe size, gradation characteristics of gravel, drawdown characteristics were determined using the FHWA-TS-224 publication “Highway Subdrainage Design” (Moulton 1980). Initially, the ditch configuration chosen was one that would be backfilled with drainable crushed gravel to about 1 m from the surface of the existing ditch. Clay would then be used as backfill above the gravel. However, in consideration of possible icing in the winter, the possibility of bringing the crushed gravel to the surface of the ditch was considered. This would allow any ditch flows to be taken vertically downward into the sub-drain for disposal and hence mitigate any icing problems of the roadway surface. A rough costing of the project was undertaken. The option with gravel to the surface appeared to be too costly and as a result, the option of using a gravel drain capped with clay and the use of a waffle drain/synthetic drain was considered. The synthetic drain would use a small amount of gravel around the perforated pipe and the remainder of backfill would be the excavated material. For this option, however, there were some perceived difficulties associated with its installation to a depth of 5 m at the time. The widths that are available for this drain type are small (450 mm) and hence these narrow strips of synthetic drain would have to be stapled together before installation. With the number of widths of drain that would have to be stapled together, the difficulty in getting the drain to the depth required because of its slenderness, it was decided not to pursue this option. This decision was made since the success of the treatment was highly dependent on how well the subsurface drains were installed. In consideration of costs of gravel backfill material, it was decided to utilize a combination of crushed and pitrun gravel for drain backfill. With the pitrun gravel being about half the price of the crushed gravel, it was decided to utilize this material in the east subsurface drain above a 1 m thick layer of crushed gravel surrounding the drainage pipe. The reason for this was that most of the water was travelling from west to east and that the drain that would be most effective would be the one in the west ditch, hence crushed gravel is used up to the underside of the clay backfill. An impermeable liner–non-woven geotextile combination was recommended to line the sides of the west ditch with non-woven geotextile only in the east ditch. The impermeable 1462

liner was recommended to be placed on the east side of the west ditch since the liner would act as a cutoff to moisture flowing transverse to the sub-drain as a result of the higher transverse slope in relation to the longitudinal slope. As with any subsurface drainage system, maintenance is required to ensure its performance as intended. Blockage of the outlet of pipes by dirt accumulation often is an issue to performance. It was recommended that this installation be identified to maintenance personnel for frequent checking to determine if the drain is flowing. This is important in the winter, as well, to ensure that the water continues to flow thereby avoiding the upward movement of water to the freezing front. Steaming of the ends may have to be undertaken if the condition warrants. The schedule of maintenance during the summer could be at 3-month intervals in the first year and at longer periods, thereafter, based on observations made during the first year. 8

IMPLEMENTATION OF REMEDIAL MEASURE

The proposed subsurface drainage measures were implemented on May 2 and 3, 2005. However, as a result of costs, the County of Yellowhead decided to install the drain on the west side only. It was also decided to eliminate the geotextile on the east side. Photographs of the installation are shown in Figures 11 and 12. Since installation of the subsurface drain, traffic was subsequently re-routed to the new alignment after the roadway surface was bladed, shaped and re-gravelled. 9

FAILURE OF GEOTEXTILE REINFORCEMENT

The failure of the post-construction remedial measure was largely the result of the lack of undertaking a detailed geotechnical investigation of the site and determining the cause of the instability of the roadway. Based on the subsurface soil conditions, the use of geotextiles, shallow cross-drainage and large boulders mixed into the existing roadbed was an inappropriate solution for the roadway in question. The main reason for the failure of this stabilization approach was that geotextiles for reinforcement cannot mitigate deformations caused by commercial, industrial and recreational traffic on roadways that are expected to perform as permanent roads. For a temporary road, where large deformations are tolerable by off -highway traffic, the approach used would perhaps have been acceptable since these roads are maintained by blading and shaping and the traffic using such roads are robust. The presence of water and its ability to move to the surface of the roadway would result in roadbed instability with the materials that comprise the upper 2 m of the roadbed. The geotextile used was for reinforcement only and would require a very high modulus to reinforce

Figure 11.

Installation of subsurface drain.

Figure 12.

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Outlet end of subsurface drain.

the roadbed. In addition, the roadbed materials would have had to be of a granular nature to allow movement of water without weakening of the grade. Such design considerations require the complete understanding of the geotechnical characteristics of the site and cannot be guessed. 10 SUMMARY AND CONCLUSIONS The investigation of the problem of instability of a section of the Wolf Lake road in the vicinity of Wolf Lake Recreational Park has shown that the instability was promoted primarily by movement of water through capillary action from a high water table under a significant head. A few pertinent options were examined to mitigate the problem. These included grade raise and excavation and replacement of the roadbed with clay. The solution considered to be most effective and cost-effective for this site was the installation of subsurface drains to a depth of 5 m in both longitudinal ditches to depress the water table to a deeper depth and allow for drier conditions within the top 2 m of the roadbed. In hindsight, certain site characteristics should have signaled the need for a detailed geotechnical evaluation and assessment of the site at the time of roadway design. The roadway in cut, the presence of Wolf Lake in close proximity to the site, the presence of the No-name Creek to the south west (uphill of the site) and the observed continuous flow of the centreline culvert linking the Creek to Wolf Lake on the east, and general topography of the surrounding land were features that should have raised initial concerns. However, on the other hand, highway geometric design requirements often supersede geotechnical considerations in many instances and problems are only addressed when the roadway is constructed and the problems can be readily observed. This approach is often used since there is always a degree of uncertainty in determining the effectiveness of any geotechnical solution until actual construction is undertaken. The initial cost associated with geotechnical solutions are often weighed against their likelihood of success. On the other hand, however, the cost of geotechnical solutions after the problem has been observed can be extremely costly. The lesson to be learned from this investigation is that while the problem of rutting appeared to be the result of a weak roadway roadbed, the application of solutions based on visual observation and past experience of sites that displayed similar characteristics, may not always be successful. No matter how simple a problem appears, it is always necessary to determine its cause through a structured investigation which will allow the necessary topographic and subsurface information to be obtained to allow the understanding of the site and the design of suitable remedial measures. REFERENCES GAEA Engineering Ltd. 2004. Geotechnical Report, Grade Instability, km 0 + 060 to km 0 + 660, Wolf Lake Road, Alberta, 53 km South of Jct Hwy 16 and Wolf Lake Road. Moulton., L.K. 1980. Highway Sub-drainage Design, Report No. FHWA-TS-80-224.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Use of bitumen emulsion in urban paving C.R. de Carvalho Filho Construtora C. Regis, Recife, Brazil

F.P. Cavalcante & C. de Medeiros Brito Cavalcante JBR Engenharia Ltda., Recife, Brazil

J.A. Gonçalves de Macêdo UFCG, Campina Grande, Brazil

I.D. da Silva Pontes Filho UFPE, Recife, Brazil

ABSTRACT: The Brazilian urban road network has demanded great efforts to make it possible to find alternative pavement construction techniques, in order to contribute for reduction of the lack of urban infrastructure, especially in suburbs areas of the Brazilian metropolitan cities, where low and high income families coexist. In this context, it is indispensable that appropriate models of management are adopted and that techniques and procedures are developed that allow the progress of this indispensable sector to the urban development, and that they eliminate or minimize to its extent. To increase knowledge of pavement mechanics in Brazil, it is crucial to break some paradigms of project and construction techniques, by taking advantage of the consolidation of the subgrade, and by formulating asphalt mixtures with special grade aggregates having high internal friction. This would to work with very thin base layers when it subjected to the passing loads. 1

INTRODUCTION

In Brazil a great deficit exists in the urban paving due to combinations of several factors tied mainly the lack of investments in infrastructure. Roads are necessary for the growth of the cities, of the states and of the country. More and more studies in the paving area have been promoting the economical and social developments and the intrinsic connection with the urban network. According to Souza’s teacher Murilo Lopes the pavement is a structure of layers, in which materials of different stiffnesses and deformation characteristics are put in contact, resulting in high complexity degree in what refers to the calculation of the tensions and deformations. However, the function of the pavement is destined (Souza, 1980) to resist and to distribute, conveniently, to the soil the solicitations originating from of the vehicles. Considering approximately ten years of experience, the subgrades of non paved streets in the area of Recife are quite consolidated, due to performance of the traffic for years and years, even so, after this verification, this characteristic is not taken into account in the pavement design regarding the in place structure. Another important aspect is that in the maintenance of the non paved streets, sometimes by city intervention and sometimes by the own residents, good quality materials such as sand, clay sand, slag, etc, when submitted to traffic along the years produced good support capacity. After studying these subgrades through laboratory tests, they possess good geotechnical characteristics.

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Emulsions

CAP H2O

Figure 1.

2

Emulsions Bituminous (SFERB, 1991).

OBJECTIVE OF THE WORK

The present work has been designed, to discourse about experience in the area of Recife with use of emulsion bound treated aggregate, this mixture which develops the interaction emulsion aggregate, the material skeleton which passes in the sieve of number #4 for the generation of a bituminous mortar, with high internal friction (LRPCT, 1995), being executed as base layer on the consolidated subgrade, using the available aggregate in the area of Recife with introduction of cationic emulsion. In Brazil the design method based on California Bearing Ratio (CBR) was an adaptation of the model developed by USACE in the United States, where soils performs different geotechnical characteristics from ours. Our soils are called tropical soil provides of better capacity behavior clearly than the soils of the temperate climates. Joining this factor to long settlement period provoked by the traffic, we have established subgrades with great geotechnical behavior, but very little advantage has been taken this consolidation, which is very important to the factor of the binomial cost/benefit in our pavement design. 3

ASPHALT EMULSION

The use of the asphalt emulsions in the paving work embraces a fan of possibilities that they are going from the dense mixtures as the cold bituminous mix to surface dressing, slurry seals, coating, and even more sophisticated techniques as the slurry seal with a modified emulsion polymer. The asphalt emulsion can be characterized by a dispersion of the asphalt globules in a continuous aqueous phase, and stabilized by the action of addictive chemical (see Figure 1). Second P. Becher (SFERB, 1991) emulsion is a system heterogeneous thermodynamics unstable, holding at least two phases liquidates immiscible in that a phase is dispersed in the other under form of droplets which the diameter is in general superior to 0,1 micron. Such system possesses a minimum stability that is reached through appropriate agents’ addition as the surfactants agents. 4

INTRINSIC PROPERTIES OF THE EMULSIONS

The intrinsic properties are those properties belonging to the material, which doesn’t depend on the iteration with other materials, as for instance: the viscosity and the stability. They are

1466

of great importance, because it determines the use form, the workability, the answer of the material to its function, etc., and these factors are directly linked to the characterization of the mixture. With relationship to the viscosity, the preponderant factor is the concentration of the dispersed phase, other factors also influence the rheological properties, among them we can mention: the nature of the dispersed phase origin and class of the asphalt (penetration), type and amount of surfactants, particle size distribution of the asphalt droplets and, production procedure (mill type). A preponderant factor in the stock stability is the particle size distribution of the globules, and it that depends on other parameters: nature and amount of emulsifier, neutralization rate (ph of the aqueous phase), origin and class of the asphalt, temperature of the asphalt in the moment of the emulsifying and type of colloid mill.

5

EXTRINSIC PROPERTIES

The extrinsic properties are those related to the behavior of the emulsion related with the aggregates, these properties are: the breaking speed and adhesion. Rupture is the process in that the following stages are produced: – separation can be caused by sedimentation or creaming; – flocculation results of an agglomerated disposition of the droplets of the dispersed phase in an open chain; – coagulation implicates in the same previous conception, only that contrarily to the flocculation it produces a process that may lead on to coalescence of the particles into larger globules, resulting in a coagulum. Adhesion of the emulsion is a property that denotes certain complexity, being the interaction bitumen-aggregate, though there exist many factors that influence this interaction, as for instance, the viscosity, the temperature during the mixture of the emulsion with the mineral, the water content and the degree of cleaning of the aggregate. Another extrinsic property is the thermal susceptibility, that happens in the bituminous mixcausing the resistance loss and durability of the mixture, when this is in the lingering presence of water and it be submitted to cyclical oscillations imposed by the traffic. For this reason, it is of highest importance an appropriate formulation of the emulsion in relation to the mineral used in the mixture in order to check a strong passive adhesiveness enough to avoid stripping for the shear stress caused by the passing loads. Another important factor is the mineralogical composition of the aggregates, that in presence of materials of positive electric charge as limestone and basalt, they provoke a reaction between the aggregate and the hydrochloric acid, forming carbonate of insoluble amina of the interaction asphalt binder-aggregate that favors the adhesiveness (see Figure 2). And in presence of a material charged negatively as granite or quartzite, it provokes an attraction of the asphalt globules carried positively, forming amina-silicate of insoluble amina that is also favorable the adhesiveness. Like this, it is very important to recognize the mineralogical composition of the aggregates to prepare a correct formulation of the bitumen emulsion. It is very common in nature to find minerals in presence of others. It can speed the reaction of the emulsion provoking a fast rupture of the emulsion or it can make it less reactive by o delaying the breaking of the emulsion. In the area of Recife, we have found granite with presence of k-feldspar, which in turn, can develop a quite alkaline mixture, doing with that the emulsion reacts quickly, accelerating the rupture of the emulsion. It falls to the engineer to accompany the results of laboratory testes in order to verify the acting of the used material. It is very important the factor that should prevail is the “feeling” with the mixture, so that it can have a satisfactory behavior with the final rupture during the compaction.

1467

Figure 2.

6

Bituminous emulsions (SFERB, 1991).

ASPHALTIC MIXTURES

The formulation of the mixtures asphaltic depends a lot on the experience of the engineer regarding the design, in other words, compatibility of the modules among the layers, geotechnical conditions of the subgrade, and available materials. The French philosophy in mix formulation “Enrobés” includes the following: – first step, to avoit rut in the wheel track in function of the traffic and of the position of the layer, once satisfied the first condition in what it concerns the materials representatives of the project, we can go to the second step; – the second step is to optimize the aggregate size composition and the asphalt content in the mixture to obtain a given thickness, in order to obtain a void content so that it can promote impermeability , and the bind content should reconcile the resistance to fatigue and rut to the wheel track. If these conditions are satisfied, a mixture resists rutting and fatigue cracking. The second condition is very difficult task due to complexity that the bituminous mixtures present. According to Yves Brosseaud (2006), now in France the design of new pavements or the structural improvement in the quality of a road network stands for the adaptation of the structures and of the materials to resist to the increasing of the passing heavy loads that grow continually generated by traffic. It is important, to notice that the standard European axle possesses 115 kN, but in France it corresponds to 113 kN, adopted for more than 30 years. Therefore, it is indispensable the use of very stiff materials to resist fatigue and of permanent deformation, allowing to reduce and to distribute the tensions conveniently to an acceptable value, allowing a long life pavement. To win this challenge, the French road engineers adopted, for more than 15 years, 1468

the beginning of dissociation of the functions of the pavement layers. The base layer of the pavement assures the mechanical resistance of the structure, the surface layer assists to the use functions under the technical aspects of safety and of comfort. Therefore frequently it applies bituminous mix type “Grave bitumen” with medium stiff modulus, or “Enrobé à module élévé” (bituminous mixes of high module—EME class 2) associated to a thin bituminous mix (BBM – Béton Bitumineux Mince—or very thin (BBTM – Béton Bitumineux Très Mince—bituminous mix, used as a wearing course. 7

PLOWING WITH EMULSION

The plowing technique with Emulsion in situ “is executed” with coming materials of quarry, that is applied directly on the subgrade, that has been an adaptation of the French “Grave emulsion” (emulsion bound aggregate) type 3, according to the norm NFP-98-21, with a bind content of 3,2%. It consists of doing a mixture directly on the subgrade, through simultaneous operation of ripping-spreading, of local materials as crushed rock, recycling asphalt material, etc, and emulsion slow setting. The methodology is simple, because it doesn’t need expensive and sophisticated equipment could be mixed the materials in field. Starting from a previous study of aggregate size to embrace such a sieve is very wide concerning norms, as long as one can obtain mechanical support characteristics and flexibility, resulting from a lack of cracks with the passage of heavy vehicles, combating in an exceptional way the process of fatigue. This procedure gives us excellent results and already confirmed in experimental executions done in some streets of the metropolitan area of Recife. The experience has been demonstrating that can execute an urban street of varied length from 100 to 160 meters in a day of service. For this reason, we got to lower the costs considerably even with the use of matters of good quality (Carvalho Filho et al., 2006). As Bordes (1993), 80% of the binder in the mix holds to the fine sieve material 0/6 mm leaving the larger particles slightly coated with the binder, resulting in a dry friction of the aggregate very little lubricated, creating a high internal friction, likewise, the efforts are transmitted in compression. In the metropolitan area of the city of Recife, we have been accomplishing this mixture directly on the leveled subgrade, this operation doesn’t request sophisticated equipments and the application is ultra-fast. With these characteristics we obtain a material that resists well to the rut on the wheel path, and above this layer, depending on the traffic, we applied a very thin asphalt mix, it can be a hot A/C, cold asphalt mix. Some authors (Godard, 1991; Serfass, 2002; Carvalho Filho and Bordes, 2003), points some advantages of the use of emulsion treated aggregate as follows: – Economy of energy: as the process is cold, the emulsion can be applied in the local temperature, without the need of previous drying of the aggregates and without the heating of the materials and of the mass asphaltic during the production, transport, storage and application. Like this, the consumption of necessary energy for these stages is notably inferior in relation to the hot mix; – Environmental benefits: as the materials are not heated to high temperatures, and not provoking gas emission and smokes, dust to the environment, all of that related to the burns of fuels and the heating of the asphalt; – Variable thickness: to allow an application with variable thickness between 0 and 12 cm, mainly in leveling of deformed layers; – Flexible material: for being a flexible mixture, it possesses a good behavior on flexible layers, tends the capacity to support the deformations without causing cracks, this is due to your rich mortar in asphalt; – Not deformable: due its sieving distribution and bitumen content with great sieve particles slightly coated with asphalt (dry friction) reducing the deformations; – Storage: It can be stored by several months, doing with that your use flexibility is quite wide. This allows producing a big amount of material to stock, or just enough to use in small correction. The mixture type emulsion treated aggregate should be protected, when it be stored. 1469

8

STUDIES OF CASE—FIGUEIRA MELO

The following case study was accomplished in Melo’s street, located in the city of Recife, possessing 100 m of extension, where the backcalculation was executed. For the design of the layer thickness, we adopted the method of resilience for new Pavements included in the “Paving manual of DNIT (DNIT, 2005). 8.1 Used method Extremely, the characteristics of the used method are presented: – This proposed method calculates the total thickness of the pavement in terms of granular base in flexible pavements. – It considers the CBR support capability on the subgrade. – The method classifies, as the resilience of the fine soils of the subgrade, in three types: Soil type I: Soils with low resilience degree; Soil type II: Soils with degree of intermediate resilience; Soil type III: Soils with degree of high resilience. Table 1 gives the classification of the subgrade soil when the percentage of silty particles in the fine fraction that passes in the sieve #200. The calculation of the total thickness of the pavement (HT) in terms of granular base (K = 1,0) is obtained by the expression: Ht = 77,67 × N0,0482 × (CBR)−0,598

(1)

where Ht = Total thickness in cm, N = number of repetitions of the standard axle of 8,2t for project period, CBR = CBR of the subgrade. The minimum thickness of the bituminous coating (HCB) is obtained through the following expression: HCB = −5,737 + 807,961 / DP + 0,972 × I1 + 4,101 × I2

(2)

where DP = project deflection in 0,01 mm, I1, I2 = constants related with the characteristics of the resilient behavior of the subgrade (see Table 2). The deflection of the project DP is given by the expression: Log DP = 3,148 − 0,188 Log N

(3)

Table 1. Classification of subgrade with relationship to the percentage of silt. CBR (%)

=35

S (%) 35 a 65

>65

=10 6a9 2a5

I II III

II II III

III III III

Table 2. Constants related with the characteristics of the subgrade. Soil type

I1

I2

I II III

0 1 0

0 0 1

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Table 3. Structural value of the coating in function of the number of solicitations of the axle-pattern bus station. 8,2t N Type of subgrade

104

105

106

107

108

I II III

4,0 3,0 2,0

4,0 3,0 2,0

3,4 3,0 2,0

2,8 2,8 2,0

2,8 2,8 2,0

The method considers for the structural value (VE) of the bituminous layer (HCB) the following values in agreement with the number “N” and the type of soil of the subgrade (see Table 3). The method calculates the thickness of the granular layer (HCG) through the following expression: HCB × VE + HCG = HT : HCG ≤ 35 cm 9

(4)

DESIGN METHOD

The data used are the following: CBR of the subgrade = 20%; N = 1 × 104; Classification of the soil of the subgrade = type I (see Table 1); I1 = 0 and I2 = 0 (see Table 2); Value structure = 4 (see Table 3). Determination of the Total Thickness of the Pavement (Ht): Ht = 77,67 × N0,0482 × CBR(−0,598) Ht = 20,0 cm Calculation of the deflection project (DP): Log Dp = 3,148 − 0,188 × logN DP = 249 × 10−2 mm Imports to highlight that, the level of project deflection (acceptable) obtained with the use of the Equation 3, it is over estimated before its limitation. For this reason, it was adopted as acceptable deflection 60% of the value of DP obtained by the Equation 3. This value was defined with base in the deflectometer studies presented in all measured deflections made with the beam Benkelman in urban roads of the city of Recife where the plowing with emulsion was applied with emulsion. Dp = 249 × 10−2 mm × 0,60 24 × 10−2 mm Calculation of the minimum thickness of concrete asphaltic (HCB): HCB = −5,737 + 807,961 / DP + 0,7972 × I1 + 4,101 × I2 HCB = 0,76 cm 1471

Thickness of granular layer HCB × VE + HCB = Ht for Hcg ≤ 35,0 cm 2,5 × 4,0 + Hcg ≥ 20,0 cm

Hcg = 10,0 cm of material to granulate

The thickness requested for the layer of concrete asphaltic, considering the presented characteristics is smaller than 1 cm. However, a thickness of 2,5 cm of A/C and 8 cm of plowing with emulsion as base layer considering the structural coefficient of 1,4. The pavement design is constituted like this: – Plowing with emulsion layer of 8,0 cm of thickness; – A/C 2,5 cm (thickness).

10 STRUCTURAL EVALUATIONS For the structural characterization of the paved road deflection studies were carried out in the years of 2006 (recently built) and 2008 (with two years of service), what made possible through back analysis process, obtaining the resilient modulus of the plowing with emulsion plus a very thin A/C layer and subgrade. As it demonstrates, Table 4, gives the deflections basins measured in 2006 and 2008; they are practically the same ones, excepting the last deflection measured 150 cm away the point of application of the load, which denotes the structural answer of the subgrade. It is observed on average that the deflection corresponding to the subgrade decreases around 54%, which it evidences a better structural acting of this layer after 2 years of service in certain way. Having the results, we can evaluate the behavior of the structure through the parameter “AREA”, they expresses the structural behavior in what it concerns the distribution of the loads, in Table 5 they consist indicative values of “AREA” for different surface layers (first row Portland cement concrete, second row asphalt concrete thicker than 10 cm, third row asphalt concrete thinner than 10 cm, and the last row surface treatment).

Table 4. Deflection basins (in multiples of 0.01 mm) of Melo’s street obtained in 2006 and 2008. Distâncias radiais (cm) Deflexões (×0,01 mm) ANO

TIPO

0

25

52

75

100

125

150

2006 2008

Medida ELSYMS

95 96

75 77

53 54

39 37

30 26

25 20

22 16

7,1

Medida ELSYMS

92 89

78 82

56 59

37 35

25 25

19 17

14 13

8,8

Table 5.

AREA parameter (AASHTO, 1993).

Tipo de Revestimento

ÁREA

Pavimento de concreto de cimento Portland Concreto asfáltico, esp. ≥ 10 cm Concreto asfáltico, esp. ≤ 10 cm Tratamento Superficial

610–840 530–760 410–530 380–430

1472

RMS (%)

BACIA DEFLECTOMÉTRICA Rua Figueira de Melo MEDIDO

ELSYM5

Distâncias Radiais (cm) 0

25

50

75

100

125

150

0,0

Deflexões (×0,01 mm)

20,0

40,0

RMS (%) = 7,1 60,0

MRGE = 35.500 kgf/cm² MRSUB = 245 kgf/cm² 80,0

100,0

120,0

Figure 3.

Adjustment of the deflection basin (in multiples of 0.01 mm) measured in 2006.

BACIA DEFLECTOMÉTRICA Rua Figueira de Melo MEDIDO

ELSYM5

Distâncias Radiais (cm) 0

25

50

75

100

125

150

0,0

Deflexões (×0,01 mm)

20,0 40,0 RMS (%) = 8,8 60,0

MRGE = 36.000 kgf/cm² MRSUB = 480 kgf/cm²

80,0

100,0 120,0

Figure 4.

Adjustment of the deflection basin (in multiples of 0.01 mm) measured in 2008.

Regarding the basin medium deflection were certain the values corresponding to the years of 2006 and 2008, resulting in 645 mm and 561 mm, respectively. To compare these values with those indicated in the Table 5, we verified to be true the assertive that the plowing with emulsion causes a larger distribution of the loads. Already with relationship the back analysis, done with subsidy of the program ELSYM5, it can be verified that the module, until the moment, they don’t demonstrate great alterations for the pavement (A/C + Plowing with emulsion), however, the subgrade layer presented module relatively larger in the year of 2008. In Figures 3 and 4, they consist of the fittings among the measured basins and calculated, as well as, the resilient modulus of the layers of the pavement/subgrade. 11 FINAL CONSIDERATIONS The range of procedures and paving techniques placed the disposition of contracting parties and contracted they owe, in effect, to develop without interruption in order to adapt to the needs of the infrastructure, always in the concern of the binomial cost and benefit. 1473

The innovation is necessary with intention of assisting to the municipalities, placing the academic knowledge and political will above all to the communities’ disposition that they live in the great urban centers, the most affected for the infrastructure lack. The asphaltic mixtures done with emulsions they are constituted of specific characteristics, once these mixtures have evolutionary character, starting from a maturation of the mass asphaltic, that soon after the application it possesses low cohesion and resilient modulus, but in the course of time, and evacuation of the residual water the asphalt particles enter progressively in adhesion taking to the mixture to an excellent mechanical behavior, allowing the construction of thin pavements with the use of the structure of consolidated subgrade. Therefore, with base in the study of presented case, we can highlight: – the plowing with emulsion presented parameter “compatible ÁREA” with constituted structures of concrete asphaltic; – the resilient modulus of the layer is relatively loud, for treating from a mixture to cold, around 35.000 kgf/cm2; – the Plowing with emulsion with emulsion propitiates a better distribution of loads originating from of the traffic on the subgrade layer. REFERENCES AASHTO (1993). Guide goes Design of Pavement Strutures. Washington. Souza, M.L. of, (1980). Pavimentação Rodoviária. Rio de Janeiro, Volume 1. SFERB (1995). you Read emulsions of Bitume—Généralités applications. LRPC (1995). L`wntretien give Chaussées Du Reseau Urbain. Report of Technical Attendance of the Municipal City hall of the City of Recife—Pierre Embroiders, LRPC—Toulouse—France. DNIT (2005). Manual of Paving. Rio de Janeiro. Brosseaud, Y. (2006). Conference accomplished in the 18th Encounter of the Asphalt. Rio de Janeiro.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

A case study: Quantification and modeling of asphalt overlay delamination on an airport pavement E. Horak & J.W. Maina Built Environment, CSIR from University of Pretoria, Pretoria, Gauteng, South Africa

S.E. Emery University of the Witwatersrand and Kubu International (Pty) Ltd, Johannesburg, Gauteng, South Africa

ABSTRACT: An international airport in southern Africa is experiencing premature asphalt surface distress; crescent shaped cracks appeared on the taxiway, one of the threshold areas on the runway and turning circle. Investigations into the cause and mechanism of distress indicated that delamination of the overlaid surfacing is the main cause of the crescent shaped cracks. Investigations confirmed that construction in periods of wet weather, a flat geometry and dysfunctional surface drainage coupled with an ageing porous surface layer caused stripping and delamination of the top 50 mm asphalt overlay which then showed crescent cracks due to aircraft braking and low speed turning maneuvers. A mechanistic analysis with a multilayered elastic analysis freeware was used to model the horizontal shear forces for the design aircraft with various levels of interlayer slip. The strain energy of distortion (SED) principle was used to model and predict the crescent shaped crack formation. 1

INTRODUCTION

Hosea Kutako International Airport (HKIA) is the international airport approximately 45 km outside Windhoek, and acts as the international gateway for the booming tourism industry of Namibia. HKIA has two runways. The 45 m wide main runway 08/26 has a total length of 4673 m with turning loops on both ends. More than 80 per cent of take-offs take place from the 08 end while more than 80 per cent of touch downs occur on the 26 end. The secondary runway is 30 m wide and 1524 m long. This runway is effectively superfluous as only light aircraft occasionally land in cross wind situations and Eros airport in Windhoek handles most of the light to medium aircraft size movements. The apron area of HKIA is linked with the main runway via a parallel taxiway with most taxi movement links via Bravo and Charlie taxiways. This airport partially meets the International Civil Aviation Organization (ICAO) 4E geometric code specification, as will be discussed later. The airport was rehabilitated in 1999/2000 with a 50 mm asphalt overlay. In some cases this was accompanied with milling of identified weak spots in the old asphalt surface. Surface distress in the form of cracks had been observed as early as 2002 in isolated sections of the main taxiway and was repaired with milling and asphalt overlay under the contract liability. However, since 2005 crescent shaped cracks appeared and increased in extent ever since. The parabolic or crescent-shaped cracking appeared on the surface of some of the aircraft maneuver areas on the main runway and taxiway link to the apron area. Classical crescent shaped cracks (Tayebali et al., 2004 & Shanin, 1994) were observed on the taxiway link to the apron area in 2002. Temporary crack-filling was initially tried to contain the problem with limited success. Such crescent shaped crack type occurs when there is a loss of bond or delamination occurring between the surface asphalt and the lower asphalt layers. Subsequently these crescent shaped cracks occurred in the vicinity of the threshold area of the turning loop at the 08 end of the main runway. This area is exposed to 1475

large horizontal forces and torsion due to the turning and braking of the wide bodied aircraft during taxi maneuvers when going around the turning loop. The lack of bond between the surface asphalt and the lower asphalt layers lead to slippage and associated crescent shaped cracks occur needing continuous monitoring and emergency repair. The delamination and associated crescent shaped cracks pose a significant danger of loose material and Foreign Object Digestion (FOD) which can lead to aircraft damage. A large “carpet” of the delaminated top layer of asphalt was blown off in March 2007 by jet blast on departure of a wide body jet (Airbus A340). This incident emphasized the seriousness of the distress occurrence. This occurred on the “08 end” at the junction of the turn-out for the turning loop. Braking and torsion due to the turning action of the aircraft when negotiating the turning loop clearly shoved the old asphalt further and opened a crack just after the previously repaired section. During take-off the considerable jet blast clearly found the edge of the opened crack extending beyond the recent repair and was sufficient in force to lift a large area of old un-bonded asphalt surfacing off. The distress mechanism and possible causes were investigated. Field and laboratory testing include limited coring, permeability testing, surface texture depth determination and shear tests on core samples. A mechanistic analysis to model the slip of the delamination of the top 50 mm asphalt surfacing was also done to help quantify the problem. 2

PAVEMENT STRUCTURE

The top 50 mm asphalt overlay was done in 1999/2000 in order to rehabilitate and strengthen the existing pavement structure. Previous investigations by consultants indicated that the pavement structure was as follows: − 50 mm coarse continuously graded wearing course. − 100 mm older asphalt thickness (varying layer thickness). − 150 mm waterbound macadam base (53 mm nominal size). − 150 mm unstabilised granular sub-base of G5/G6 quality (CBR 40 to 60). − 150 mm imported sub-base of G8/G7 quality (CBR 15 to 40) on top of − in situ subgrade of G8/G9 quality (CBR 7 to 15)(CSRA, 1985). Visual inspections by various consultants done recently confirmed that the distress was limited to the upper 50 mm asphalt layer which showed evidence of various stages of ageing, map cracking, delamination and crescent shaped cracks. The observed distress and current ongoing repair work was confined to the areas coinciding with either slow taxi maneuvering or braking of wide body jets in the areas in and around the 08 end turning loop, the Charlie and Bravo Taxi-way links and on the taxiing asphalt areas adjacent to the concrete apron. 3

ORIGIN OF THE DISTRESS MECHANISM

According to Tayebali et al. (2004), Romanoschi & Metcalf (2002) & Shanin (1994) such crescent shaped cracks are normally associated with even minor loss of bond between asphalt layers which can cause stresses in overlays to increase dramatically when loaded wheels exert horizontal and vertical loads on the pavement. On roads the results are amplified at intersections where the braking action of traffic result in large horizontal forces exerted on the surface of the road. The loss of interlayer bond causes higher tensile strains in the asphalt overlay which may even result in fatigue cracking originating from the top of the layer (Romanoschi & Metcalf, 2002). The horizontal surface shear forces then cause crescent shaped cracks in the top layer if the loss of bond becomes critical (Tayebali et al., 2004 & Romanoschi & Metcalf, 2002). There is clear evidence at the areas where the crescent-shaped cracks occur that the surface of the under-laying asphalt is smooth and lack tack coat adhesion and bonding of the top 50 mm asphalt overlay onto the under-laying asphalt layer. Limited evidence of surface roughening with a milling machine of the lower asphalt layer was seen at distressed areas 1476

during patching operations. This appeared to be limited to the areas repaired during the liability period. Surface roughening can act as additional alternative mechanism for asphalt on asphalt friction (Romanoschi & Metcalf, 2004) and the lack thereof obviously causes the reverse situation as observed here. Water presence can cause stripping and de-bonding of the surface and lower asphalt layers. Visual inspections confirmed that water intrusion is the main facilitating medium for the delamination of the top 50 mm asphalt layer. Water flowed freely from such delaminated areas when repaired, even in dry periods. The question then arose how the water got in. As built reports were not available at the time of the investigation, but reports from witnesses and participants during the original overlay construction in 1999/2000 provided valuable information. Construction started at the lower end (26) of the main runway in 1999 and work progressed towards the higher end (08) where the wet period (December 1999 to February 2000) interrupted construction. This 08 end also happens to be the end where the majority of distress is appearing. It appears that a hurried or disturbed construction process during this wet period may have contributed to some water presence in the interlayer and top layer from the start. Visual inspection of the repaired delaminated areas with crescent shaped cracks and coring done at various periods of investigation confirmed that the upper 50 mm asphalt layer clearly had signs of stripping. The upper layer could be lifted with spades and picks in large slab sections with ease during emergency repair operations. Voids were clearly visible and even a loose gravelly lower side of the asphalt overlay were observed in some cases. In all cases of emergency milling and repair moisture was observed flowing out of the interlayer. The lower asphalt layer showed no signs of stripping or aggregate and binder loss. It appeared smooth and un-cracked over most of the areas exposed by patch and repairs operations. 4

ASPHALT SURFACING CONDITION

A limited set of tests were done on samples sent to the asphalt research laboratory of the CSIR. The CSIR results on these samples are summarised in Table 1. The tests show that the recovered binder from the asphalt premix is reaching the end of its service life. It was described by the CSIR as follows: “The properties of the recovered binder indicate a very viscous and rather degraded (aged) binder, close to the end of its expected service life if the original binder was penetration grade bitumen, i.e. not modified binder.” The binder type was confirmed to be not modified by people involved during the overlay construction in 1999. During the emergency patch repair operations a fine dust powder was observed on the surface of the lower asphalt layer once the upper 50 mm asphalt overlay came off. The origin of this dust layer had to be determined as it clearly acted as a bond breaker on its own and in the presence of water further lubricates the already smooth interlayer. This tended to further facilitate slippage between the layers when large horizontal forces are exerted on the top layer by shoving and braking actions of aircraft wheels. The dust sample, as well as a sample from the 50 mm asphalt, was subjected to the “ash test” where the dust and recovered binder were heated till it only left an ash residue. Normally recovered binder should leave a maximum of 2% ash mass to indicate that the recovered binder, and therefore the mix, is free of excessive filler material (van Assen et al., 1992). The recovered binder from the premix sample meets this requirement as shown in Table 1. Table 1.

Tests on asphalt cores and binder recovered from asphalt on HKIA.

Description

Dust

Asphalt

Test method (CSRA, 1987)

Binder content, % (m/m) Penetration 25°C (10–1 mm) Softening point (R & B),°C Ductility, 25°C (cm) Ash determination, % (m/m)

6.2 – – – 93.8

5.3 20 66.0 19.3 1.39

ASTM D1856 ASTM D5–05 ASTM D4402–02 DIN 52013 ASTM D482

1477

In the case of the dust it confirmed that the dust is in fact 6.2% binder content and its origin can therefore be deducted with reasonable certainty to be due to the emulsification of the tack coat and possibly from the binder in the 50 mm asphalt premix layer on top. However, the 93.8% ash residue indicates that considerable filler sized material have accumulated and bonded with the emulsified binder to form the observed sticky dust. It cannot be ruled out that some of such filler sized dust may have been due to windblown or water borne silt deposited on the tack coat prior to the final overlay. The old and aged condition of the asphalt premix is normal for the high ultra violet exposure and temperature ranges experienced at Windhoek. After 7 years age of such extreme exposure age related cracking in the upper 50-mm asphalt layer is therefore to be expected. Map cracking occurs over the whole length and width of the runway surface and clearly contributed to further water intrusion over time.

5

CONTRIBUTING FACTORS TO THE DISTRESS

Longitudinal profile survey and cross fall geometry surveys were done on the main runway at 50 m spacing along the main runway. The main purpose of this survey was to quantify the visual perception of flatness of the runway. These basic dimensions are compared with the International Civil Aviation Organisation (ICAO) (2004) specifications and recommendations for a 4E code airport. The average longitudinal slope is 0.94% which meets the ICAO specification of less than 1%. The outer quarters should be less than 0.8%. The survey found that the first and last quarter portions of the runway fall outside the ICAO (2004) specification of less than 0.8 per cent. The survey clearly showed that the cross fall can be described as flat over most of the length of the runway being in the less desirable range of 1% to 1.2%. The cross falls very seldom go into the more desirable 1.2% to 1.3% range and very seldom come close to the most desirable 1.3% to 1.5% range. It is only in the indicated zone where the transition of grades at the two runway intersections falls clearly outside the desired ranges. The preceding geometric analysis indicates that there are areas on the main runway where water may pond infiltrate and get trapped in the aged and porous 50 mm asphalt surface layer. The cross fall tend to be flat in general over large parts of the runway. At both ends of the runway the longitudinal gradient is rather steep and even more than the cross fall gradient, making it more convenient for the trapped water to longitudinally flow down hill than side ways out towards the paved shoulders. This has specific significance at the 08 end where there is evidence of water infiltration via ponding on the edges in the turning loop as well as ponding on the sides of the runway prior to the turnout to the turning-loop. Peculiar highpoints in the longitudinal gradient occurs in the vicinity of the turnoff to taxiway Bravo and Charlie which also coincide with observed distress and water flowing from surface cracks even in dry periods.

6

DETERMINATION OF LAYER INTERFACE SHEAR

Romanoschi & Metcalf (2002) used a direct shear test with normal and horizontal load to determine an interface constitutive model for asphalt layer interfaces. Phase one of this test is up to the point where the interface has failed where after the second phase of friction between the two de-bonded layers are also determined. Both these phases of testing proved to be highly temperature dependant with loading also playing a role. However, access to such a test was not possible during the evaluation of this airport, but good guidance was given and benchmark values obtained from improvised shear testing. Other similar testing results could also be used for relative benchmarking of the improvised shear testing. Tayebali et al. (2004) used a variety of shear tests to evaluate the bond strength of tack and prime coats of asphalt overlays on asphalt, concrete and cementitious 1478

Table 2. Average shear stress of shear ramp tests with emulsion and PG64-22 tack coats (Tayebali et al., 2004). Test temperature

Average for 1 and 2.5 mm/min shear rate

20°C 40°C 60°C

1100 kPa 460 kPa 2.96 to 7.71 kPa

Table 3.

Direct shear results at 20°C of HKIA cores.

Chainage (m)

Shear stress value (kPa)

1740 left 2200 left 3420 right 4220 right 1340 left Turning loop 08 120 left Turning loop 08 start Taxi way at apron close to Charlie

516 504 1135 2497 2263 800 3629 1451

bases. In Table 2 average values for the combined shear rates of 1 mm/min and 2.5 mm/min are summarized as determined by Tayebali et al. (2004) for asphalt overlay on asphalt at 20°C, 40°C and 60°C. This is also the average for two different tack coats as indicated in Table 2. Nevertheless these averaged values indicate that the shear stress of the tack coat interlayer bond is highly temperature dependant as the shear value drop dramatically as the temperature increase from 20°C to more normal working temperatures of 40°C and 60°C for this region in the summer months. These averaged results from Tayebali et al. (2004) are merely used here to provide a benchmark for the simple direct shear tests done on a limited number of in tact full depth asphalt cores from HKIA runway 08/26. Attempts with infra-red imagery to further quantify the occurrence of the delamination were unsuccessful due to the excessive patching and slurry repairs done to date (Tsubokawa et al., 2007). In order to help quantify the occurrence and describe mechanism of the debonding of the top 50 mm asphalt overlay a systematic coring program following a grid pattern was done over the whole length of the runway. These cores were non standard due to the lack of availability of equipment at the time of coring in this remote area of southern Africa. Subsequently these non-standard cores were tested with a basic shear device (Tayebali et al., 2004). The cores were put in the test rig and sheared at the interface of the top 50 mm asphalt layer and the lower asphalt layer. The tests were only done at 20°C due to the limited number of core samples. In Table 3 the shear stress values thus determined are shown with an indication where the core was taken from. There is a significant variance in shear stress values. If compared with the average shear stress values at 20°C shown in Table 3, at least 50% of the cores have lower values than the 1100 kPa average determined by Tayebali et al. (2004). It is clear that a number of these cores obtained from HKIA, though in fact, have a degraded interlayer bonding situation. As stated before, Windhoek has high summer temperatures and therefore the higher temperatures such as 40°C and 60°C would certainly imply lower bond strengths in line with the dramatic drop shown by Tayebali et al. (2004) in Table 2. The variability of the bonding of the upper 50 mm asphalt layer to the lower asphalt layers is a concern. It has been shown that the bond strength diminishes drastically at higher temperatures. It implies that even areas which are currently not yet delaminated can over time become delaminated as there is clear indications of degradation from fully bonded to zero based on the shear test results of full depth cores. 1479

Table 4.

7

HKIA pavement structure input values.

Layer

Thickness (mm)

Modulus (MPa)

Poisson’s ratio

Asphalt overlay Asphalt old layer Waterbound macadam base G6/G7 subbase G7/G8 imported subbase

50 100 150 150 150

3000 3000 500 350 120

0.44 0.44 0.35 0.35 0.35

MECHANISTIC MODELING OF INTERLAYER SLIP

Maina & Matsui (2004) developed analysis freeware, known as GAMES, which provides solutions for boundary conditions for five different types of airport pavement surface loading namely; vertical, horizontal (shear), torsion, moment and centripetal forces incorporated in the elastic. Maina et al. (2007) used the concept of quantity of strain energy stored per unit volume (V0) of the material as originally developed by Thimoshenko & Goodier (1951) as basis for the determining the limiting stress at which failure occurs. In short, Hooke’s law is applied to calculate the strain energy due to distortion (SED) (a scalar value) which can be expressed as follows; SED = V0 −

1 − 2ν (σ x + σ y + σ z )2 6E

(1)

This is basically a function of the bulk (sum of principle) stresses, the elastic modulus (E) and Poisson’s ratio (v). Using the above equation it is possible to benchmark points within the pavement structure in that points having higher values of SED will potentially fail first before points with relatively lower SED values (Maina et al., 2007). The pavement structure mentioned earlier was analyzed with material parameters and values as summarized in Table 4. One bogey with four wheels of the main gear of a Boeing 747–400 was used as the loading situation. The wheel contact footprint diameter is 458 mm and the loading of maximum 225 kN for vertical force per wheel. The horizontal force was varied from zero to 0.7 multiples of vertical force. The maximum value of 0.68 (rounded off to 0.7) of vertical force (Tayebali et al., 2004), described before in the shear test results, is based on the surface friction coefficient which is accepted as the maximum horizontal force possible at approximately 50 kph. Three interlayer slip situations at the interface between the asphalt overlay and the old asphalt layer were modeled: − No slip (zero value) − Half slip (0.5 value) − Full slip (0.99 value) The SED calculations presented as a composite of the three slip conditions are shown versus variance in the horizontal force condition in Figure 1. For the zero slip condition the SED maximum value is as expected at the interface between the wheel and the top of the overlay surfacing. This value increases significantly as the horizontal force is increased from zero to 0.7 while the interlayer SED at the overlay surfacing and the old surfacing remains relatively small. This implies that for the fully bonded situation the asphalt overlay can withstand the maximum horizontal force of 0.68 of vertical force with ease with no shear or crescent crack damage development. However, if the interlayer condition is half slip (i.e. modeled value of 0.5) the maximum SED calculated is at the top of the old or lower surfacing. The SED at the bottom of the overlay is about 60% of the abovementioned SED maximum and increase marginally to about 75% of the maximum SED at the top of the old asphalt surface. The SED at the interface between the wheel and the top of the asphalt overlay surface starts at zero, but gradually increases to about 55% of the maximum SED for the full horizontal force at 0.68 of vertical force. 1480

Top of surfacing layer

Top of old asphalt layer Bottom of 50 mm overlay

Top of old asphalt layer

Bottom of 50 mm overlay Top of surfacing layer

Top of old asphalt layer

Bottom of 50 mm overlay Top of surfacing layer

Figure 1. Composite of Strain Energy at Distortion (SED) calculations with varying degrees of interlayer slip for HKIA overlay.

This half slip analysis situation implies that even at high speeds (therefore low horizontal forces) the possibility for distress in the form of crescent shaped crack damage is relatively high. This may explain some of the crescent shaped cracks which appeared on the touch down area of the 08 end of the main runway. These cracks could not be correlated with slow moving aircraft during taxi operations. The relatively low texture depths, shown in Figure 1, implies that skidding will occur before the maximum skid of 0.68 friction coefficient can be reached, but even at lower horizontal forces, cracking will still be possible due to the relative sizes of the SED at the top of the surface layer versus the top of the old asphalt layer and the bottom of the top layer. In Figure 1, it can be seen when full slip (i.e. modeled value of 0.99) occurs at the interface between the asphalt overlay and the old asphalt that the highest SED at maximum horizontal force occurs at the bottom of the 50 mm asphalt overlay. This SED value showed an increase 1481

with increase in horizontal force while the SED at the top of the old asphalt layer remaining at a relatively high value with the variance in horizontal force values. Even though the SED at the top of the asphalt overlay increased, as the horizontal force was increased to the maximum possible at 0.68 of vertical force, it remains proportionally lower than the maximum SED calculated at the bottom of the asphalt overlay. This implies that crescent shaped crack damage formation is possible even at low horizontal force application. It also means that for fully delaminated sections crescent shaped crack damage may occur not necessarily due to low speed braking, but can happen at higher speeds where the coefficient of friction is lower. However, even though limited touch downs take place on the “08 end”, the inertia of the tires upon touchdown will exert considerable horizontal force without high vertical force. Such situations can certainly lead to considerable SED development and can explain the occurrence of crescent shaped crack damage in the touchdown area on the “08 end”. The latter area of touch down is clearly identifiable with the rubber deposits which can even be seen in the satellite image in Figure 1. 8

CONCLUSION

The occurrence of the crescent shaped crack damage on the asphalt surface of areas on HKIA can directly be linked to the delamination of the top 50 mm asphalt overlay. The cracks appear at all the places where wide bodied aircraft do low speed turning movements and where braking causes the shearing of the top layer which is slipping on the old underlying asphalt surface. Analysis of the geometry of the main runway clearly indicated that water can seep into the pavement, adding to the suspected water captured during wet weather construction, drain downhill within the 50 mm asphalt overlay layer and lead to stripping of the tack coat bond and contributing to the delamination of the top 50 mm asphalt surfacing. Field tests and laboratory testing with cores helped to determine the extent of the delamination and to benchmark the interlayer bond of intact cores with a simple shear test. It clearly showed that the bond of the interlayer is highly variable and degraded. This benchmarking with other international shear testing studies also indicated that at higher working temperatures the interlayer bond will be even more suspect and may slip and delaminate at low levels of horizontal force. This shear test benchmarking was enhanced with mechanistic analyses with the multilayered elastic freeware, GAMES, to simulate variable slip between the layers at various levels of horizontal force exerted on the surface layer. The concept of the scalar unit of strain energy of distortion (SED) assisted to benchmark the various relative slip and horizontal force permutations to explain high speed and slow speed braking leading to interlayer slip and formation of crescent shaped cracks forming at various places identified earlier. ACKNOWLEDGEMENTS The Namibian Airports Company (NAC) is thanked for permission to publish this information. However the opinions expressed here are that of the authors and not that of NAC. Buhrman and Partners Consulting Engineers (BCPE) are thanked for their survey, testing and facilitating the investigation. REFERENCES Committee of State Road Authorities (CSRA). 1985. TRH 14. Guidelines for road construction materials. Technical Recommendations for Highways (TRH), CSIR, Pretoria: South Africa. Committee of State Road Authorities (CSRA). 1987. Standard methods pf testing road construction materials. TMH 1. CSIR, Pretoria: South Africa.

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International Civil Aviation Organization (ICAO). 2004. Standards and Recommended Practices for Aerodromes. Annex 14 to the Convention on International Civil Aviation, Volume I: Aerodrome Design and Operations, Fourth Edition. 999 University Street, Montréal, Quebec, Canada, H3C 5H7. Maina, J.W. Matsui, K. & De Beer, M. 2007. Effects of Layer Interface Slip on the Response and Performance of Elastic Multi-Layered Flexible Airport Pavement Systems. Proc. 5th Int. Conf. on Maintenance and Rehabilitation of Pavements and Technological Control, Park City, Utah, USA. pp. 145–150. Maina, J.W. & Matsui, K. 2004. Developing Software for Elastic Analysis of Pavement Structure Response to Vertical and Horizontal Surface Loading. Transportation Research Record. 1896, pp. 107–118. Washington: USA. Tayebali, A.A., Rahman, M.S., Kulkarni, M.B. & Xu, Q. 2004. A Mechanistic Approach to Evaluate Contribution of Prime and Tack Coat in Composite Asphalt Pavements. Research Report 2001–04, Department of Civil Engineering, North Carolina State University: USA. Shanin, M.Y. 2004. Pavement Management for Airports and Parking Lots. Chapman and Hall, New York. Timoshenko, S. & Goodier, J.N. 1951. Theory of Elasticity. McGraw-Hill Book Company, New York. Tsubokawa, Y., Mizukami, J. & Esaki, T. 2007. Study on Infrared Thermographic Inspection of DeBonded Layer on Airport Flexible Pavement. Presented for the 2007 FAA Wolrdwide Airport Technology Transfer Conference, Atlantic City, New Jersey: USA. Romanoschi, S.A. & Metcalf, J.B. 2002. The Characterization of Pavement Layer Interfaces. Healing and Bonding Session. 9th International Conference on Asphalt Pavements, International Society for Asphalt Pavements (ISAP), Copenhagen. Van Assen, E.J., Vlok, H. & Grummett, P. 1992. Effects of Selective Sorption by Mineral Fines on Asphalt Properties. Proceedings of the 6th CAPSA conference held in Cape Town: SA. Pages IV-176 to IV-187.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Taxiway embankment over soft ground using staged construction R. Wells, X. Barrett & T. Wells Trigon Kleinfelder, Inc., Greensboro, North Carolina, USA

ABSTRACT: The Piedmont Triad International Airport (PTIA), Greensboro, NC has been undergoing an expansion including a new runway (Runway 5 L-23R) and taxiway (Taxiway E) as a result of the construction of a Mid-Atlantic regional hub for Federal Express. The presence of soft ground in the wetlands area at Taxiway E crossing required careful consideration of the effects of construction, and wetland permitting requirements. The design of the embankments had to include minimizing the total area impact as well as prevent slope stability and bearing capacity issues during construction. The use of ground stabilization to provide a working platform in conjunction with toe berms to maintain slope stability and wick drains to accelerate drainage, strength gain, and settlement offered benefits to all members of the project team. An instrumentation program was implemented to determine the fill placement rates or appropriate waiting periods during fill placement, and to prevent slope failures. 1

BACKGROUND INFORMATION

The Piedmont Triad International Airport (PTIA) located in Greensboro, North Carolina is undergoing an approximate $550 million expansion as a result of Federal Express selecting this site for their Mid-Atlantic regional hub. A photograph of the overall site is provided in Figure 1. Part of the construction of the associated Taxiway E includes the construction of the embankment over a wetlands area in an alluvial floodplain. The wetland crossing is from STA 11 + 00 and STA 17 + 00, for an approximate distance of 183 m (600 ft). The final grades in this area require the construction of an earth embankment up to 18 m (60 ft) in height over the existing soft ground, adjacent to Brush Creek. The footprint of the taxiway alignment is restricted by a Corps of Engineers agreement and other water quality standards, including wildlife habitat requirements imposed by state agencies. The wetland water quality and flow could not be impacted by the crossing, requiring that the potential for slope failures be minimized. The flow of Brush Creek was diverted into a box culvert approximately 160 m (525 ft) in length. 2

SUBSURFACE CONDITIONS

The subsurface exploration indicated the ground profile to consist of an upper zone of very soft to soft alluvial soil underlain by a residual soil profile, with groundwater at or near the ground surface. Figure 2 shows a typical boring record in the wetland area. The alluvial soils present in the borings within the wetland area extend from 1 m (3 ft) to 8 m (27 ft) below the existing ground surface. In general, the alluvial soils consist of either sandy silts or silty sands with varying amounts of mica and clay. The soil test borings and dilatometer soundings indicated a very heterogeneous alluvial profile, with the areal extent and thickness of the different soil types varying significantly. Standard Penetration Resistance values obtained in the alluvial soils ranged from Weight of Rod (WOR) to 10 blows per foot (bpf), with the majority of values less than 5 bpf. Undrained shear strengths in the fine grained soils measured between 0.96 kPa (20 psf) to 48.9 kPa 1485

Figure 1.

Piedmont Triad International Airport (PTIA).

(1000 psf), with the majority of values less than 24.5 kPa (500 psf ) (Hayes, September 1990). The surface of the alluvial soils, after stripping of the root mat, would not support the weight of a person. Below the alluvial materials is a residual soil profile consisting of sandy silts and silty sands overlying weathered rock. Standard Penetration Resistance values obtained in the residual soils range from 6 to 90 blows per foot (bpf ), with the majority of values between 15 and 55 bpf. Weathered rock consists of residual materials that exhibit SPT N-values of 100 bpf or greater. Groundwater is generally within 0.6 m (2 ft) of the ground surface. A photo of the site after clearing, but prior to construction, is provided in Figure 3.

3

PREDICTED PERFORMANCE

Settlement predictions for the alluvial soils below the embankment were based on the results of the soil test borings and dilatometer testing. Empirical analyses indicated settlement magnitudes ranging from 0.8 m (2.5 ft) to 1.2 m (4 ft) within the central portion of the embankment area. Settlements of 15 cm (6 in.) or less were predicted at the toe of the rock berm. The settlements were predicted using FHWA and Schmertmann methodologies. A stability analysis was performed in which the in-situ material properties were varied due to the heterogeneity of the alluvial soils below the embankment. The stability analysis was performed at various fill heights with parameters varied from preconstruction values to the anticipated values due to strength gains after consolidation.

4

STABILIZATION DESIGN

Various slope configurations, including one that incorporated a vertical retaining wall, were analyzed using steady state conditions in a value engineering study. This study included settlement potential and slope stability analyses. Also, various excavation and ground 1486

Figure 2.

Typical boring record.

1487

Figure 3.

View of wetlands area from the southwest.

improvement alternatives were investigated to improve the safety factors for slope stability since probable failures were predicted due to the soft alluvial soils beneath the embankment (Han, et al., Jan. 29–31, 2004). A brief description of the initially considered scenarios, the estimated cost differential for preparation below the embankment and construction time is provided below: • Complete removal of all soft alluvial materials within the zone of the taxiway crossing of the wetlands. Cost—$5,550,000.00, Duration—1 year • Partial removal of an upper zone of the soft alluvial materials to a depth of 2.4 m (8 ft) and replacement with a granular material placed below the groundwater surface. Cost— $3,850,000.00, Duration—1 year • The use of stone columns under the toe of the slopes to provide for adequate slope stability. Cost—$2,600,000.00, Duration—1 year • Sequencing the fill placement and construction over a long period of time (Ladd, 1991). Cost—$780,000.00, Duration—3 years The four considered scenarios did not fit within the desired construction budget or schedule, as dictated by the construction schedule for the Federal Express facility. The chosen option included the use of vertical wick drains in the alluvial materials to improve drainage for faster consolidation to allow shear strength improvements within the alluvial soils. Temporary rip rap berms were used beyond the toe of the final slopes in the wetlands before embankment placement to obtain the needed resisting forces from the shear strength improvement in the alluvial materials for embankment stability purposes. The berm materials outside the slope toe were removed in later stages and used for protection of the embankment faces. The timeframe required for this scenario was estimated to be up to 2 years, as the construction contract included a minimum waiting period of 90 days between 4 stages of fill placement. A sketch of the embankment cross section for this scenario is provided in Figure 4 below. An instrumentation program was considered to be a necessity, to monitor the settlement magnitude, pore pressure buildup and dissipation in the soft alluvial materials, and lateral movement of the soils beyond the embankment toe to safely control the filling rates. The required waiting periods between fill placement stages could only be reduced based on the 1488

Figure 4.

Embankment cross section (facing south).

results of the instrumentation monitoring program which added on additional $225,000.00 to the below grade construction cost. 5

INSTRUMENTATION PROGRAM CONCEPT

The instrumentation program consisted of pore pressure and settlement monitoring, slope indicator measurements of the horizontal deformations, and measurements of the vertical deformations (heave) beyond the toe of the slope. These data were used to control the fill placement rate and appropriate waiting periods during fill placement to accommodate consolidation and shear strength increases in the alluvial materials. The horizontal and vertical deformations of the materials were also monitored and if found to be excessive filling could be suspended to prevent slope failures from occurring. 6

CONSTRUCTION

The ground improvements within the floodplain area of Taxiway E included clearing the area of above-ground vegetation, and selective grubbing; the rootmat was allowed to remain since it would be very difficult to remove due to the very low shear strength of the underlying alluvium. Prior to the beginning of construction for Taxiway E, a temporary haul road had been constructed through a portion of the left side of the embankment footprint in the alluvial floodplain. The haul road was used initially and then later removed. The initial presence of the haul road restricted the location of some of the instrumentation components. Over the cleared ground, a stabilized working platform was constructed. This working platform design section consisted of a combination of biaxial geogrids, geotextile filter fabric, and 0.6 m (2 ft) of clean, uniformly graded crushed stone (Kamal, Lane, and Heshmati, March 21–22, 2005). After the working platform was constructed, wick drains were installed to facilitate drainage of the alluvial soils. The wick drains were installed utilizing a five feet triangular grid pattern through the alluvial soils, into the underlying residual material. Once the wick drain installation was completed, a layer of uniaxial geogrid was placed on the clean stone followed by 30 cm (1 ft) of well graded crushed stone, to provide a stable working platform for filling operations. A photograph of the construction of the working platform is provided in Figure 5 below. Once filling operations began, approximately 0.6 m (2 ft) of new fill was placed each 3 working days. Some delays were experienced due to weather and seasonal conditions. Filling was suspended during the winter months due to difficulties with moisture in achieving adequate completion. At other times, filling was suspended due to rainfall. Typically, up to 4 days were lost per significant rainfall event from the rain time and drying time to resume fill placement. 1489

Figure 5.

7

Construction of working platform.

INSTRUMENTATION INSTALLATION

The instrumentation for Taxiway E consisted of the installation of piezometers, slope indicators, horizontal conduits for settlement monitoring, and benchmarks to measure heave. Instrumentation was installed at several locations within the embankment, perpendicular to the slope at four selected stations. Piezometers were installed at five locations along each station; one below the rip rap berm on both sides, two at the top edge of the slope at varying depths on both sides, and one under the centerline of the embankment. Soil test borings were performed at each piezometer location to delineate the zones of fine grained soils in which to install the piezometers. The piezometer tips were pushed into the fine grained soils in order to monitor the soil possessing the potential for the greatest increases in pore pressure. Slope indicator pipes were installed approximately 9 m (30 ft) outside the toe of the rip rap berm utilizing an ATV drill rig. The slope indicator pipes used were 8.5 cm (3.34 in.) in diameter installed within 16-cm (6.25 in.) boreholes. The annular spaces were filled with sand. The pipes were placed to a depth of approximately 1.5 m (5 ft) into the underlying residual soil. A total of eight (8) horizontal settlement monitoring conduits were installed approximately 20 cm (8 in.) below the surface of the working platform. Four conduits were installed on each side of the taxiway centerline, at the four instrumentation stations. The conduits on the west side extended to the centerline of the embankment while the conduits on the east side extended upward from the toe approximately 22.9 m (75 ft). By using these conduits, the settlement of the embankment is determined along a continuous profile. Benchmarks were installed approximately 6 m (20 ft) from the toe of the slope on both sides. The benchmarks were monitored to determine the magnitude of vertical ground movements (heave) beyond the toe of the embankment at the four stations. 8

INSTRUMENTATION RESULTS

The instrumentation was monitored from August, 2006 to February, 2009. At the time this paper was prepared (February, 2009), approximately 60 cm (2 ft) of embankment fill remained to be placed. The use of the instrumentation program has proved to be an excellent 1490

tool to confirm the performance of the engineering design in the field. The results were used to control the rate of filling based on actual measurements instead of relying on estimated waiting periods, thus accelerating the construction schedule. The initial construction sequencing included a waiting period of 90 days at selected fill heights which would have resulted in an increase in the construction schedule of one year beyond the time required to place the fill. For this project, the end result was the elimination of the waiting periods altogether. The only delays experienced were weather-induced. The settlement rates were also used to determine a safe point at which to install the permanent retaining wall facia so that damage due to differential settlement along the wall alignment would not occur. The completed wall is shown in Figure 6. The horizontal settlement monitoring conduit measurements indicated settlement magnitudes in general agreement with the predicted values, based on the height of fill placed. Measured settlements under the central portion of the embankment ranged from 0.33 m (1.1 ft) to 0.81 ms (2.7 ft). Measured settlements at the toe of the rock berm ranged from 8 cm (3 in.) to 24 cm (9.5 in.). The ratio of measured settlements to predicted settlements ranges from approximately 0.38 to 0.67. This is attributed to the heterogeneity of the subsurface profile, the conservatism of the preliminary analyses, and likely, the presence of the haul road that was installed some time before the instrumentation; however, areas not monitored particularly close to the creek could have experienced larger settlement magnitudes. An important issue of soft ground construction is the excess pore pressures generated by the filling process. To evaluate the effect of the increase in pore pressures, the ratio of the change in excess pore pressures (Δμ) to the change in overburden pressure (Δσ1), termed the “B” value, was calculated each time the field measurements were obtained. This “B” value was used to control the rate of fill placement (Fell and Hunter, 2003). For this project, the critical value of “B” was set to 1.0, based on the soil types. The piezometers indicated that the pore pressure “B” values increased to no more than 0.5, as compared to the critical value for the soil types at the project site. Measurements obtained during weather delays indicated

Figure 6.

Completed wall.

1491

that the excess pore pressure generally dissipated within a time period of about 10 days after the cessation of filling operations. The slope indicator measurements did not indicate the occurrence of significant lateral movement. Lateral movements of less than 1.5 cm (0.6 in.) were measured for the time frame reported in this paper. Measurements on the heave points did not indicate the occurrence of significant vertical movement. Vertical movements of less than 1.5 cm (0.6 in.) were measured for the timeframe reported in this paper. 9

PRACTICAL ISSUES

During the design phase, the issues most important to the project team were cost and construction schedule. The least cost alternative could be used and the construction schedule potentially shortened by using the instrumentation results to control the rate of fill placement. The concerns for a slow construction schedule and the risk of slope failures into the wetlands was eliminated. The embankment was constructed within the estimated time frame at a cost differential of $1,500,000.00 (estimated) below the next least expensive option. The instrumentation devices were also monitored for settlement to allow placement of the retaining wall facia and final paving operations without concern for additional settlement that would their performance. An unexpected benefit of the instrumentation program was that while monitoring the construction of the working platform, it was noted that the surface of the first phase of the working platform exhibited better stability than expected. As a consequence, the depth of the upper layer of well graded crushed stone was decreased by 30 cm (1 ft), saving the owner approximately 20,000 tons of crushed stone and 10 days off the construction schedule. ACKNOWLEDGEMENTS Special thanks go to Mr. Ted Johnson, Mr. Mickie Elmore, and Mr. Kevin Baker, P.E. of the Piedmont Triad International Airport, and Mr. Carl Ellington, P.E. and Mr. Brian Salyers, P.E. of Talbert & Bright, who have been involved through the design and construction phases of this project. In addition, thanks to Dr. J. Brian Anderson, P.E., Professor of Civil Engineering at the University of North Carolina at Charlotte, and Dr. Manuel Gutiérrez, P.E., for their analyses input. We would also like to thank Mr. Fran Furfaro of Blythe Construction Inc., for all his help in installing the instrumentation in the field. Additional thanks to Ms. Jessica Dickson and Ms. Lisa Stafford for their word processing and formatting help. REFERENCES Fell, R., Hunter, G. 2003. “Prediction of Impending Failure of Embankments on Soft Ground.” Canadian Geotechnical Journal, Vol. 40: 209–220. Han, et al. 2004. “Evaluation of Deep-Seated Slope Stability of Embankments over Deep Mixed Foundations.” Proceedings of GeoSupport Conference: Innovation and Cooperation in the Geo-Industry, Jan. 29–31, 2004, Orlando, Florida. Hayes, J.A. 1990. “The Marchetti Dilatometer and Compressibility”, Southern Ontario Section of the Canadian Geotechnical Society. Seminar on “In Situ Testing and Monitoring”, September 1990. Kamal, Abdul Aziz, A., Lane, Pauleen, A. and Heshmati, Ali, A.R. 2005. “Parametric Study of Reinforced and Unreinforced Embankment on Soft Soil.” Proceedings of 13th ACME Conference, March 21–22, University of Manchester. Ladd, C.C. 1991. “Stability Evaluation during Staged Construction.” Journal of Geotechnical Engineering Vol. 117 (No. 4): 540–615.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Evaluation of runway bearing capacity: In-situ measurements and laboratory tests A. Graziani & F. Cardone Università Politecnica delle Marche, Ancona, Italy

E. Santagata & S. Barbati Politecnico di Torino, Turin, Italy

ABSTRACT: This paper describes the structural evaluation procedure for the new runway pavement of the Ancona Airport in Italy. As part of a major rehabilitation project, 520 m of runway were fully reconstructed along the “keel” section. The new pavement was constructed on a lime-stabilized subgrade. The base course had a lower cement stabilized layer and an upper hot mix asphalt layer. Modified binder was employed in all bituminous mixes, including the SMA wearing course. An extensive experimental program was carried out as part of the construction control activities. Dynamic Cone Penetrometer (DCP), static and light-weight dynamic plate tests were performed to estimate subgrade and foundation stiffness. Global pavement response was evaluated using deflection testing (HWD). A laboratory test program was completed to carefully assess physical and mechanical characteristics of pavement materials. In particular stiffness and fatigue properties of the asphalt layers were evaluated both on cores and laboratory compacted specimens. The analytical evaluation of the pavement strength was carried out using effective material properties for modulus and fatigue. Results were compared with calculations based on conventional FAA criteria. The study confirmed that an enhanced behavior of asphalt mixes, related to the use of modified binder, can be anticipated. 1

BACKGROUND

The “Raffaello Sanzio” airport is a former NATO Air Base located close to the city of Ancona, on the Adriatic coast of central Italy. The airport has a single runway (Tab. 1) characterized by the presence of concrete heads and a flexible pavement in the central part. As requested by the local Airport Authority, Aerdorica S.P.A., the Experimental Interuniversity Road and Airport Research Centre (CIRS) completed a project-level structural evaluation to assess the bearing capacity of the runway pavement (Santagata et al. 2006). As a result, a structurally weak area was identified along the keel section, nearby the runway head 22. After considering different rehabilitation alternatives, in view of budget and operational constraints, the full-depth reconstruction of a 520 m long, 16 m wide, pavement section was designed to restore the runway bearing capacity. On the remaining span of the keel section a new Stone Mastic Asphalt wearing course was proposed, using an inlay technique, to homogenize surface characteristics and improve pavement safety. 2

PROJECT OUTLINE

The structural design for the full-depth reconstruction was based on the CBR method, as described by the Federal Aviation Administration AC 150/5320-6D (FAA, 2004). The design

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Table 1.

Basic runway physical characteristics.

Runway designation

TORA m

TODA m

ASDA m

LDA m

Width m

04 22

2962 2962

2992 3022

2962 2962

2766.5 2812

45

ICAO Reference Code: 4D

Table 2.

Design traffic. ACN Takeoff weight kg

Tire pressure kPa

Subgrade category

Aircraft

Annual departures N

A

B

C

D

B747-200 B737-800 B757-200 BAe 146-200 ATR-72

100 1400 300 250 4000

379,000 79,000 100,250 41,000 23,000

1410 1470 1160 880 550

52 44 26 22 11

58 46 29 23 12

71 51 35 26 14

93 56 47 29 15

Table 3.

Layer

Summary of pavement design and specifications. Air Thickness Aggregate voids mm Dmax mm %

Asphalt content %

2÷6 4÷6 4÷6

6.5 ÷ 7.5 4.5 ÷ 5.5 4.0 ÷ 5.0

AC Stone Mastic Asphalt 30 AC Binder Course 40 AC Base Course 80 Cement Treated Base 200 Crushed Aggr. Subbase 100 Lime Stabilization 400 Natural Subgrade (CL-CH)

10 20 31.5

Strength*

Modulus** MPa

2.5 ≤ UCS ≤ 4.5 ≥100 CBR ≥ 40 ≥60 CBR ≥ 30 ≥50 CBR = 7

*UCS: Unconfined Compression Strength (MPa); CBR on 4 days soaked samples **Measured in Static Plate Load Test, 1st cycle (see Section 3.3)

traffic fleet (Tab. 2), was converted to 1778 yearly departures of a Boeing 747-200 aircraft (Design Aircraft) with a Takeoff Weight of 368,000 kg (810,000 lb). The spreadsheet F806FAA.xls (FAA 2005a) was used for calculations. The final structure was designed considering locally available materials and construction techniques (Tab. 3). Lime stabilization was adopted to improve subgrade strength (3% hydrated lime). A crushed aggregate subbase was placed over the stabilized layer and below a Cement Treated Base (CTB) course. The CTB was a “low-stiffness” mixture, typically used in Italian motorways. Considering that construction had to proceed as rapidly as possible, the intermediate unbound granular layer was deemed necessary to separate two layers where pozzolanic reactions were (supposedly) developing in their peak phase. The asphalt surface course was further subdivided into a Stone Mastic Asphalt wearing layer (30 mm), a binder layer (40 mm) and a base layer (80 mm). All asphalt mixtures were specified according to the current European Norm (EN 13108), and the use of a modified asphalt was required. The full-depth reconstruction project was completed in 23 days, during this period the runway was used with a displaced threshold. The residual field length (1805 m) allowed 1494

Figure 1.

Plan view of the working area (after rehabilitation).

the operations of the B737 aircraft to be safely managed, as requested by Aerdorica. New non-precision instrument approach procedures were developed as the ILS glide slope was not available during the working period. Temporary horizontal signs were provided and a Precision Approach Path Indicator (PAPI) was installed to assure a more accurate approach to the touchdown zone. The working area was divided in 2 zones (Figure 1). In the “Green Zone” located 350 m from the displaced threshold all the construction activities were carried out during the daylight, without disturbing traffic flow. In the “Red Zone”, located 160 m to 350 m from the displaced threshold, construction activities were carried out from 11:30 pm to 6:00 am. During this period the runway was closed to avoid penetration of the obstacle limitation surfaces. 3

MATERIALS CHARACTERIZATION

3.1 General remarks An extensive experimental program was carried out to achieve a careful characterization of material properties, particularly for the stabilized subgrade. The following tests were part of construction quality control: – Dynamic Cone Penetrometer tests (DCP); – Dynamic Plate Bearing tests (DPBT); – Static Plate Load tests (SPL). Cores obtained from compacted asphalt layers were tested for composition and voids. In addition a detailed laboratory characterization of the asphalt mixtures, including the evaluation of the dynamic modulus and fatigue performance, was carried out using both laboratory compacted specimens and pavement cores. 3.2 Dynamic Cone Penetrometer tests The Dynamic Cone Penetrometer (DCP) is commonly used for the determination of the strength profile of road and airfield pavements (ASTM 2003). The measured Penetration Rate (PR, in mm/blow), also referred as DCP index, can be converted into CBR or modulus values using empirically derived correlations. Variations in PR can also be used to detect layer transitions. The relationships developed by the U.S. Army Corps of Engineers (Webster et al. 1994) were used for the present project. During construction control DCP tests were performed directly on the top of the subgrade, 36 to 48 hours after stabilization. This allowed the thickness and the (short-term) strength of the stabilized layer to be determined. The strength of the underlying unstabilized soil was also measured. Results of DCP tests (Tab. 4) showed that the stabilization produced a quite uniform layer with an average thickness of 36 cm and an average CBR of 25. Results also yielded an average CBR of 6 for the underlying untreated subgrade. 1495

Table 4. DCP test results (lime stabilization). Lot averages and standard deviations (in parentheses). Lime stabilization

Untreated subgrade

Lot ID

Test N

Thickness mm

CBR %

Modulus* MPa

CBR %

Modulus* MPa

G-1 G-2 R TOTAL

9 10 4 23

336 (38) 366 (70) 395 (6) 359 (55)

26 (8) 25 (3) 23 (4) 25 (4)

260 250 230 250

6 (2) 7 (3) 6 (1) 6 (2)

60 70 60 60

*E =10 CBR Table 5.

Plate test results. Lot averages and standard deviations (in parentheses).

Layer Lime stabilization

Unbound subbase

Cement stabilized

Modulus type*

Lot ID

Test N.

Modulus MPa

Ed Ed Md Md Md Ed Ed Md Md Md Md

G-2 R G-1 G-2 R G-2 R G G-1 G-2 R

10 10 5 6 3 10 10 4 4 2 3

94 (12) 91 (22) 84 (18) 92 (19) 95 (21) 84 (9) 87 (13) 104 (25) 140 (55) 119 (22) 119 (20)

*Ed: DPBT Modulus; Md: SPL Modulus

3.3 Plate bearing tests Static Plate Load (SPL) tests are used in Italy for routine compaction control of bound and unbound layers (CNR 1992). The deformation modulus Md was calculated applying a static stress ranging from 0.15 MPa to 0.25 MPa. This parameter was used for acceptance and payment, on a lot basis. The Dynamic Plate Bearing Test (DPBT) allowed the dynamic stiffness modulus Ed to be rapidly estimated, at a stress level of 0,1 MPa (Van Gurp et al. 2000). Static and dynamic plate tests on the lime treated subgrade were performed together, 36 to 48 hours after stabilization. For the cement treated base a 7 days curing period was allowed. Measured values are summarized in Table 5. Even though a direct comparison of the Md and Ed values is not possible (they were obtained in different load conditions, at different stress levels and with different theoretical models) a similar stiffness could be predicted for the lime stabilized soil and the unbound granular layer. A clearly higher stiffness was estimated for the cement treated base. The Ed values measured on the lime stabilized soil were significantly lower than the modulus values estimated from CBR values (Tab. 4). However, a reference range for the interpretation of the deflection tests was clearly defined (see Section 4.2). 3.4 Laboratory characterization of the asphalt mixtures Acceptance and payment of the asphalt concrete layers were based on thickness, asphalt content and air voids, measured on pavement cores. Tests were performed on a lot basis, with 6 cores per lot. Results are summarized in Table 6. Mechanical tests were carried out on binder and base course asphalt mixtures, sampled at the job site. Cyclic uniaxial compression and 4 point bending tests were used to evaluate 1496

Table 6.

Asphalt concrete properties measured on pavement cores. Thickness

Layer SMA

Asphalt content

Bulk density

Air voids

Lot Tests Average Std. dev. Average Std. dev. Average Std. dev. Average Std. dev. mm mm % % kg/m3 kg/m3 % % ID N G-1 6 G-2 6 R 8

44 37 34

4.9 2.6 4.9

6.1 6.4 6.8

0.49 0.47 0.22

2241 2257 2249

27 25 13

7.2* 6.2* 6.0

0.81 0.52 0.57

Binder G-1 6 G-2 6 R 8

52 55 50

7.5 5.8 5.3

4.6 5.0 5.1

0.32 0.23 0.10

2264 2270 2169

45 48 65

5.6 5.8 9.0*

0.85 0.93 1.07

Base

95 68 82

8.4 18.9 11.3

4.5 4.5 4.9

0.87 0.18 0.12

2337 2258 2246

69 33 31

4.3 6.0 6.3*

1.78 0.52 0.77

G-1 6 G-2 6 R 8

*Detractions were applied on lot price.

respectively the complex modulus and the fatigue properties. The cylindrical specimens for modulus testing were compacted using a Gyratory Shear Compactor, while a Roller Compactor was employed to produce beam specimens for bending tests. In order to simulate actual volumetric properties of the pavement, the specimens were compacted with an air voids content ranging from 6% to 8%. The complex modulus was also measured on 3 specimens cored from the asphalt base course. 3.4.1 Complex modulus estimation The complex modulus was measured with a conventional frequency sweep compression test. A total of 10 cylindrical specimens were tested at five temperatures (0, 10, 20, 30 and 40°C) and six frequencies (20, 10, 5, 2, 1 and 0.5 Hz). The complex modulus master curve, at a reference temperature of 20°C, was constructed using the time-temperature superposition principle. A sigmoidal function was adopted to represent the master curve (Pellinen 1998): log E * = δ +

α

1+ e

β + γ log( fr )

(1)

where |E*| is the dynamic modulus absolute value, fr is the reduced frequency, δ and α represent the span of modulus values and β and γ are the shape parameters of the curve. A 3rd order polynomial model was adopted to represent isochrone curves of the complex modulus: log E * = a0 + a1T + a2T 2 + a3T 3

(2)

where ai are material parameters. Experimental results, summarized in Figure 2 and Table 7, showed that laboratory compacted specimens were characterized by somewhat higher stiffness values than cored samples. Indeed the master curve shape of the 2 materials is very similar. As a consequence similar rheological behavior can be expected and an average master curve was used for pavement evaluation. 3.4.2 Fatigue response Conventional cyclic 4-point bending tests were performed in controlled stress conditions. A sinusoidal haversine force was applied and the vertical displacement at the midstand of the specimen was measured. A total of 14 prismatic samples were tested at 10°C with a 1497

Table 7.

Experimental stiffness parameters. Master curve (@20°C)

Isochrone (@20 Hz)

Specimen type

δ

α

β

γ

a0

a1

a2

a3

Lab. compacted Cores All specimens

−2.27 −3.08 −1.55

6.72 7.45 5.99

−2.29 −2.30 −2.13

0.41 0.37 0.40

204.5

−2.112

7.46E-3

−8.84E-6

Master Curve @20°C 1.0E+05

1.0E+04

Laboratory compacted specimens All specimens Base course cores 1.0E+03 1.0E-03

1.0E-02

1.0E-01

1.0E+00

1.0E+01

1.0E+02

1.0E+03

1.0E+04

1.0E+05

Reduced Frequency (Hz)

Figure 2.

Master curve of Stiffness Modulus.

1000

100

Experimental data LEDFAA Finn

10 1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

Number of cycles

Figure 3.

Experimental Vs literature fatigue lines (for EA = 5000 MPa).

loading frequency of 10 Hz. The fatigue line of the material was defined using the classical power law: log N f = k − n log ( ε t )

(4)

where Nf is the number of cycles to failure, εt is the initial (maximum) tensile strain and k, n are material parameters. In Figure 3 the experimental fatigue line (k = 14.94, n = 4.1823) is plotted with other transfer functions currently used in airport pavement design (FAA 2005b, Finn 1977). Considering 1498

that controlled stress tests underestimate fatigue life, the data showed that a good fatigue behavior of the mixtures can be anticipated. 4

STRUCTURAL RESPONSE

4.1 General remarks The structural response of the “as-built” pavement was evaluated using a Heavy Falling Weight Deflectometer (HWD). Tests were carried out with a 30 cm loading plate, at a nominal vertical force of 160 kN. Deflections were collected using a 9-sensor configuration, with a constant spacing of 300 mm. The HWD survey, carried out 72 days after construction end, comprised a total of 42 measurement points, positioned on 4 parallel alignments (±3 and ±6 m offsets from the Center Line). The pavement temperature during the tests was measured at three different depths and a mean value of 8°C was calculated. The shape of the measured deflection basins were initially examined and 3 homogeneous sections were found, closely matching the 3 construction lots depicted in Figure 1. The backcalculation analysis was performed with the linear-elastic based program BACKFAA (FAA 2006), using the 85%-reliability deflection profiles of each homogeneous section. Asphalt stiffness moduli were referred to a reference temperature of 20°C using the stiffness-temperature relationship obtained in the laboratory. In particular, the 20 Hz isochrone curve was used (see Equation 2 and Table 7). 4.2 Back-calculation analysis A first back-calculation attempt was carried out with a 4-layered system: a single AC course was considered and the relatively thin granular subbase was merged with the underlying stabilized layer (see Table 8). Layer thicknesses were taken from construction control data. Even though the small value of the RMS error proved a close match between measured and calculated deflections, back-calculated modulus values were not consistent with the values estimated from materials testing. In particular the stiffness of layer 4, the untreated clayey subgrade, was clearly overestimated. In addition for sections G1 and R the stiffness of layer 3 was significantly less than the stiffness of layer 4, in contrast with the DCP tests results (see Table 4). A more appropriate solution was sought starting from the analysis of the surface modulus values (CROW 1998). A subgrade becoming increasingly rigid with depth seemed to be involved, suggesting that various sub-layers had to be differentiated. Consequently, a twolayer subgrade was adopted. The back-calculation for the 5-layered systems yielded a more reliable representation of the pavement stiffness (see Table 9). The results clearly showed that a poor quality cement treated base characterized section R. In particular the low stiffness value (692 MPa) suggested that in this section the base layer could hardly show a “flexural behavior” and that it should be considered at most equivalent to a conventional crushed aggregate base. Table 8.

Back-calculation results for a 4-layered system. Stiffness

Layer N 1 2 3 4

Material Asphalt concrete Cement treated base Unbound aggregate & lime stabilization Untreated subgrade

Thickness mm

Section G1

Section G2 MPa

Section R

160 200 450

6941* 2077 194

7419* 3315 410

5900* 1170 148

–

239

262

211

2.2

2.2

3.0

RMS error (μm) *@20°C, 20 Hz

1499

5

EVALUATION OF BEARING CAPACITY

5.1 General remarks The bearing capacity of the “as-built” pavement was assessed using both the FAA empirical method (FAA 2004) and an analytical approach. The analytical method was employed to appreciate the effect of “non-standard” materials and account for the structural response measured with deflection tests. All bearing capacity calculations reported in the following sections were carried out considering the structural parameters evaluated for section R (see Table 9), which clearly represents the critical part of the re-constructed pavement. 5.2 FAA empirical method The actual section was converted into an equivalent “standard” FAA section using appropriate equivalency factors. A total thickness of 90 mm (32 in) was determined for the equivalent section and the B747 aircraft design curves were used to estimate the bearing capacity. The key parameter of the evaluation procedure was the subgrade CBR value. The DCP results (see Table 4) indicated an average CBR of 6 and a design value as low as 4 (85% percentile). As a consequence, a bearing capacity of 172,000 kg (380,000 lb) was estimated. It was an exceedingly low value if compared with the MTOW of the design aircraft. This mainly derived from the fact that the pavement was built using materials that differed, somewhat considerably, from the FAA standard. 5.3 Analytical-empirical approach An elastic multi-layered model was used to calculate stresses and strains produced by the design traffic loads. These were then compared to the correspondent “critical values” to compute pavement damage. Asphalt concrete fatigue cracking and subgrade rutting criteria were considered. Damage calculations were performed following the procedure described by Monismith (Monismith et al. 1987). With this approach it was possible to directly take into account the lateral traffic wander. 5.3.1 Pavement design temperature and traffic Using a 30 years database of temperature data, 4 design periods were selected (see Table 10). For each season two different design air temperatures were determined (USACE, 2001), respectively for the analysis of the vertical strain at the top of subgrade (εv,SG) and the horizontal tensile strain at the bottom of asphalt concrete surface (εh,A). The corresponding design pavement temperatures were obtained with the relationship developed by Witczak (1972).

Table 9.

Back-calculation results for a 5-layered system. Stiffness

Layer N 1 2 3 4 5

Material Asphalt concrete Cement treated base Unbound aggregate & lime stabilization Untreated subgrade (1) Untreated subgrade (2)

RMS error (μm)

Thickness mm

Section G1

Section G2 MPa

Section R

160 200

6930* 1468

6790* 3240

6394* 692

450 1000 –

434 99 324

612 150 319

352 81 299

–

2.1

1.0

1.0

*@20°C, 20 Hz

1500

The design traffic previously used for design (see Table 2) was considered and departures were distributed between the four design periods according to the actual airport schedule. The traffic load frequency is normally assumed at 10 Hz for runways and 2 Hz for taxiways. At the airport, because of the absence of a parallel taxiway, aircrafts normally use the runway to taxi from/to the apron, thus a “midway” design frequency of 5 Hz, was selected. According to HoSang (HoSang 1978), the lateral wander was characterized with a standard deviation of 2,4 m. 5.3.2 Pavement structures and material properties As previously noted, the weakest pavement structure was selected for evaluation (see Table 9). For each design pavement temperature, asphalt concrete design stiffness values were calculated correcting the back-calculated stiffness for frequency and temperature (see Table 10). The correction factors were determined using the same stiffness-temperature relationship previously used to refer stiffness values to the reference temperature (20 Hz isochrone). A total of 8 structures were considered in the analysis. Transfer functions adopted by the FAA were used to compute the allowable number of strain repetitions for asphalt concrete (NA) and subgrade (NSG) failure criteria (FAA 2005b). 5.3.3 Structural analysis and damage computations A linear-elastic multi-layer computer program (BISAR) was used for the (forward) calculation of stresses and strains. For each landing gear the maximum strain locations were initially determined and a critical cross section identified. Along this section the strain distribution was computed using a total of 81 points with a 0.25 m spacing. At each point, the damage produced by each single aircraft was computed using Miner’s accumulation law (Monismith et al. 1987). Table 10.

Figure 4.

Design period characterization.

Design period

AC Design εv,SG analysis MPa

Modulus εh,A analysis MPa

Percent of total traffic %

1 2 3 4

2263 3841 5591 7101

3005 4653 6340 7721

45 15 20 20

June, July, August & September May & October March, April & November December, January & February

Cumulative damage for asphalt strain criterion.

1501

The damage calculations were repeated for all the design conditions described above and the results were summed to obtain the damage produced by each single aircraft. The cumulative damage was then calculated summing the effects of all the aircrafts (see Figure 4). Maximum values of 0.165 and 0.002 were found, respectively for the asphalt and subgrade strain criteria. Cumulative damage values are extremely low and fatigue in the asphalt layer is the critical condition, yielding a residual life of 121 years. This result is mainly a consequence of the direct evaluation of aircraft wander. In addition, a major contribution in limiting strain values can be credited to the stiffness properties of the modified asphalt layers obtained using HWD and laboratory testing. 6

CONCLUSION

The paper presents a case history regarding the structural evaluation of a runway pavement. The project involved the structural rehabilitation of a 520 m long asphalt concrete section through full-depth reconstruction. A careful characterization of the pavement materials was achieved through an extensive experimental program. Static and dynamic plate tests showed that the lime stabilized soil and the unbound granular subbase had similar stiffness, while a higher figure could be estimated for the cement treated base. Moreover, the combined use of DCP and plate tests allowed identifying the depth of the stabilized layer and defining a reference stiffness range for the interpretation of deflection tests. The properties of the asphalt concrete layers were measured both on cores and laboratory compacted specimens. In particular, stiffness characteristics have been assessed using cyclic uniaxial compression tests. Even if laboratory compacted specimens showed somewhat higher stiffness values than cored samples, similar rheological behavior could be predicted and a single master curve was used. In addition 4 point bending tests performed in controlled stress condition showed a good fatigue performance of the mixtures. Data from in situ and laboratory tests was used to assist the back-calculation of pavement deflections. This was of invaluable importance in identifying a consistent representation of the pavement as an elastic multi-layered system. In particular, a weaker pavement section characterized by a low quality cement treated base was identified. An analytical-empirical approach was applied to evaluate the bearing capacity of the critical section. The effective mechanical properties of the as-built pavement were employed and the effect of traffic wander directly assessed. With this approach the pavement showed an adequate bearing capacity that could not be appreciated applying the conventional FAA procedure. REFERENCES American Society for Testing and Materials (ASTM). 2003. Standard Test Method for Use of the Dynamic Cone Penetrometer in Shallow Pavement Applications. ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA. Consiglio Nazionale delle Ricerche (CNR). 1992. Determinazione dei moduli di deformazione Md e M’d mediante prova di carico a doppio ciclo con piastra circolare. Bollettino Ufficiale N. 146 (Norme Tecniche). C.N.R. Piazzale Aldo Moro, 7 Roma. (in Italian). CROW 1998. Deflection profile—not a pitfall anymore. Edited by C.A.P.M. Van Gurp, Record 17. Ede The Netherlands, May 1998. CROW 2005. Guideline on PCN Assignment in the Netherlands. Report 05–06. The Netherlands, August 2005. Federal Aviation Administration. 2004. Airport Pavement Design and Evaluation. Advisory Circular AC 150/5320-6D. U.S. Department of Transportation, Federal Aviation administration. Washington, DC. Federal Aviation Administration (FAA). 2005a. Flexible Pavement Design Spreadsheet: F806FAA.xls. http://www2.faa.gov/airports_airtraffic/airports/construction/design_software/. U.S. Department of Transportation, Federal Aviation administration. Washington, DC.

1502

Federal Aviation Administration (FAA). 2005b. LEDFAA 1.3 Computer Program for Airport Pavement Design. http://www2.faa.gov/airports_airtraffic/airports/construction/design_software/. U.S. Department of Transportation, Federal Aviation administration. Washington, DC. Federal Aviation Administration (FAA). 2006. BAKFAA Software program for back-calculation of FWD data. http://www2.faa.gov/airports_airtraffic/airports/construction/design_software/. U.S. Department of Transportation, Federal Aviation administration. Washington, DC. Finn, F.N., Saraf, C. Kulkarni, R., Nair, K. Smith, W. & Abdullah, A. 1977. The Use of Distress Prediction Subsystems for The Design of Pavement Structures. Proc. 4th International Conference on the Structural Design of Asphalt Pavements. University of Michigan, Ann Arbor, Michigan, August 1977. Vol. 1. HoSang, V. 1978. Field Aurvey and Analysis of Aircraft Distribution on Airport Pavements. Research in Airport Pavements. Special Report 175. Transportation Research Board, Georgia, USA. Monismith, C., Finn, F.N., Ahlborn, G., Markevich, N. 1987. A General Analytically Based Approach to the Design of Asphalt Concrete Pavements. Proc. 6th International Conference on the Structural Design of Asphalt Pavements. University of Michigan, Ann Arbor, Michigan, 13–17 July 1987. Vol. 1. Pellinen, T.K. 1998. The Assessment of Validity of Using different Shifting Equations to Construct a Master curve of HMA. University of Maryland, Department of Civil Engineering, MD. Santagata, E., Barbati, S.D. & Graziani, A. 2006. GPR investigations for the optimization of runway maintenance. Second International Airport Conference: Planning, Infrastructure and environment. 2–4 August 2006. Sao Paulo—SP—Brasil. U.S. Army Corps of Engineers (USACE). 2001. Pavement Design for Airfields. Unified Facilities Criteria (UFC) 3-260-02. USACE, Department of the Army, Washington, D.C. Van Gurp, C.A.P.M., Groenendijk, J. & Beuving, E. 2000. Experience with various types of foundation tests. Proc. 5th International Symposium Unbound Aggregates in Roads (UBAR5). University of Nottingham, United Kingdom 21–23 June 2000. Rotterdam: Balkema. Webster, S.L., Brown, R.W. and Porter, J.R. 1994. Force Projection Site Evaluation Using the Electronic Cone Penetrometer (ECP) and the Dynamic Cone Penetrometer (DCP). Technical Report GL-94-17, U.S. Army Engineer Research and Development Center, Waterways Experiment Station, Vicksburg, MS. Witczak M.W. 1972. Design of Full-Depth Asphalt Airfield Pavements. Proc. 3th International Conference on the Structural Design of Asphalt Pavements. University of Michigan, Ann Arbor, Michigan. Vol. 1.

1503

Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Lessons learned during regular monitoring of in situ pavement bearing capacity conditions P. Paige-Green CSIR Built Environment, Pretoria, South Africa

ABSTRACT: An investigation into the temporal variations of various pavement properties has been carried out in South Africa with regular monitoring over a period of one year. This involved the measurement of moisture content, in situ strength and pavement deflection at designated points on each road. The investigation involved nine low volume roads consisting of a thin natural gravel base course on the in situ subgrade, sealed with thin surface dressing bituminous seals. The roads were selected to represent various climatic and drainage conditions with the main objective being to assess the variation in road performance in relation to the seasonal moisture fluctuations. During analysis of the results it became apparent that a number of problems occurred with the data collection. This paper discusses the lessons learned from these problems and means of overcoming them in similar investigations. 1

INTRODUCTION

Between 1990 and 1994, the performance of a large number of roads with light pavement structures in South Africa was assessed in significant detail (Paige-Green, 1996; 1999). These roads were all low volume roads (generally less than 100 000 standard axles), mostly consisting of thin layers (generally a natural gravel base course of 100 to 150 mm with or without a 150 mm subbase on the in situ subgrade), sealed with thin bituminous surface dressings. All of the sections had unsealed shoulders and many had marginal quality base course materials, by conventional standards. The investigation included comprehensive investigations into the pavement material properties and designs, construction quality, traffic loadings and the consequent functional and structural performance of each pavement, with all of the results being incorporated into a large database. The functional, structural and traffic properties were subsequently re-assessed in 1995 and 1998. In 2001 and 2002, a follow-up investigation was carried out on a selection of these roads to assess the effect of seasonal moisture changes on the bearing capacity of the pavements. Sections of nine of the roads, covering a range of climatic (Thornthwaite Moisture Index of –20 to 20, Emery, 1992), drainage and surface conditions were selected for this monitoring over a one year period. These results were analyzed and made available to a third party for use in a larger project, but have never been published. Recently, a similar but much larger and more widespread investigation has been initiated. As part of the preparation for this project, the original database and analysis has been revisited in order to eliminate some of the shortcomings and problems encountered previously. This paper summarizes some of the problems identified and makes recommendations for avoiding a repetition of them in the current investigation. 2

FIELD TESTING

The 2001/2002 investigation was essentially designed to assess the effect of the seasonal moisture changes on the structural performance of the thin pavement structures. In addition to the large database previously acquired and which was used to characterize each pavement, 1505

Table 1.

Summary of selected road and material properties.

Base thickness Road No (mm)

Subbase thickness (mm)

Thornthwaite’s moisture index

Optimum moisture content (%)

Traffic (ESALs)

D540 D467 D2485 D404 D132 D514 D518 D646 D466

No subbase No subbase No subbase 70–80 No subbase 90–100 No subbase No subbase No subbase

–2 –10 –20 –20 –20 20 20 20 20

15.1 7.2 10.4 8.4 8.7 11.5 7.4 7.2 9.0

13 000 38 000 8 800 5 800 8 700 55 000 13 200 10 500 14 700

100–135 120–130 115–125 85–100 220–265 80–100 150–200 160–250 160–180

The measured densities of all of the base courses were between 96 and 101% AASHTO maximum dry density.

a program of fieldwork including a series of testing and sampling to provide the necessary information over a full annual rainfall cycle was designed. Each section was monitored seven times during the 12 month cycle. Full deflection bowls were measured using a Deflectograph, a single Dynamic Cone Penetrometer (DCP) test was done and samples of each pavement layer (base, subbase, where one was present, and subgrade) were collected for moisture content determinations during each monitoring trip. If no subbase was present, the upper 150 mm of the subgrade was considered as a subbase in the following discussion. All testing was carried out in the outer wheel tracks of the road, i.e., that part of the road expected to be most affected by environmental variations, and attempts were made to test and sample as close to the designated point on each road section as possible, ensuring that disturbance of the pavement was minimal and did not affect subsequent measurements. All sample holes and DCP penetration points were repaired with cold-mix asphalt to ensure the exclusion of moisture from the pavement. During the original fieldwork in the period 1989 to 1991, in situ testing and sampling was carried out in both wheel tracks as well as between the wheel tracks (in an attempt to assess the untrafficked/original material properties and the construction quality) of the heaviest trafficked lane of the road. All testing for this project was carried out as close to the original sample holes as was practically possible without being influenced by the patching of the sampling holes made earlier. The following investigation procedures were used. Some of the important parameters relative to this paper are summarized in Table 1. In situ densities were generally in the range 96 to 101 per cent of AASHTO T 180 compaction. 2.1 Moisture content Samples for the gravimetric determination of moisture content were taken using a 50 mm diameter hand auger at depths representing the base course (50 to 125 mm), the subbase where it existed (150 to 225 mm) and the subgrade (below 300 mm) in the outer wheel track. The sample sizes varied between 0.2 and 1.0 kg, depending on the material type and consistency. All samples were then oven-dried to constant mass at 105°C and the loss in mass as a percentage of the sampled mass was determined as the moisture content. Although the primary objective of the exercise was to assess variations in the subgrade moisture content related to precipitation, the moisture contents of the base (and subbase where present) were determined as samples of these materials were necessarily removed to obtain the underlying subgrade samples. Immediately after each of the samples was collected on site, they were sealed in moisture content tins with masking tape and dried in laboratory ovens on return to the laboratory (usually within 72 hours). Care was taken to ensure that the sample tins were handled to minimize damage or moisture loss. 1506

2.2 Pavement deflections Pavement deflection measurements were taken over a length of between 100 and 300 meters at each section during each visit, with the position of the original sampling site about midway. Deflections were recorded using the CSIR Deflectograph in both the inner and outer wheel paths. The Deflectograph tests the deflection with tire inflation pressures of 690 kPa and an axle load of 80 kN on a dual wheel axle at a speed of about 8 km/h. This equipment generally records between about 17 and 23 deflections per 100 meters travelled (depending on the friction between the road and the beam during placement) and the results are comparable with deflections measured using a Benkelman Beam. A full deflection bowl is measured with sensors recording the peak deflection and the deflections at distances of 127, 305, 610 and 915 mm from the peak measurement between the dual wheels and one measurement 100 mm behind the peak reading. For analysis purposes, the peak deflection reading in the outer wheel track at the last point before the sample hole was reached was used. In addition, the mean and 90th percentile values for the 10 readings before and after the sample point were also determined (a distance of about 50 meters). The Middle Layer Index (MLI), normally indicative of the contribution of the subbase to the total deflection, but in these cases more indicative of the subgrade, is defined by the difference in deflections at offsets of 305 and 610 mm (Horak, 1988). As any pertinent detail on or adjacent to the road was manually recorded on the Deflectograph printout (including the exact position of the sample point) it was possible to determine that the actual location of the deflection measurement could in reality vary from the required point by up to about 3 meters. 2.3 Dynamic Cone Penetrometer (DCP) testing A Dynamic Cone Penetrometer (DCP) test was carried out during each site visit with the primary intention of assessing the impact of changes in the pavement moisture content on the strength of the layer and subgrade materials and the entire structural capacity of the road. The results were all plotted using a modified version of the CSIR Transportek WinDCP 5.01 analysis program (CSIR Built Environment, 2008). DCP testing was carried out by measuring the penetration depth after every 5 blows, down to a depth of at least 800 mm. The number of blows to reach this depth is defined as the DCP structural number (DSN800) and was determined for each test. In addition, the weighted mean penetration rates for the base and subbase of each section were determined as an indication of the material strength in the base and subgrade. Although the penetration rate was used in all analyses, this can be converted to a California Bearing Ratio (CBR) value using any of the standard models (Paige-Green and Du Plessis, 2008). 2.4 Other details Monthly rainfall statistics for some months preceding the monitoring and during the monitoring period were obtained from the South African Weather Bureau for their stations nearest to the selected road sections. The rainfall recorded at the stations over the monitoring period (12 months) varied between 330 and 1110 mm. 3

SUMMARY OF RESULTS

The summary statistics of the results are provided in Tables 2, 3, 4 and 5. 3.1 Rainfall The mean rainfall for each road over the project period compared with the long-term mean data from the nearest weather stations is summarized in Table 2. The average rainfall during the monitoring period was slightly above the long term averages although the individual variations were high (–46.9 to +58.6%). Figures 1a and b show the rainfall at each site versus average rainfall for all of the sites. Although there are significant individual variations during the dry season, the trends are similar with two particularly 1507

Table 2.

Summary of rainfall data.

Road No

Mean (mm)

Project period (mm)

Deviation from mean (%)

D540 D467 D2485 D404 D132 D514 D518 D646 D466 Average

621 621 640 600 600 700 895 895 900 719

611 330 617 791 644 1110 970 970 970 779

−1.6 −46.9 −3.6 31.8 7.3 58.6 8.4 8.4 7.7 7.8

Table 3.

Summary of moisture content data. Moisture content (%) with % of OMC in parenthesis

Layer

Road No

Mean

Min

Max

Variation*

Base

D540 D467 D2485 D404 D132 D514 D518 D646 D466 D540 D467 D2485 D404 D132 D514 D518 D646 D466

15.8 (100) 7.5 (103) 11.3 (112) 7.4 (85) 11.2 (123) 7.8 (68) 8.5 (123) 8.7 (150) 16.0 (90) 11.0 (126) 11.5 (121) 16.3 (89) 7.0 (91) 11.1 (132) 12.0 (93) 10.3 (86) 9.7 (71) 10.6 (85)

14.6 (92) 6.5 (89) 9.7 (96) 5.7 (66) 8.3 (91) 6.9 (61) 7.2 (104) 7.8 (134) 13.0 (73) 9.0 (103) 9.1 (96) 10.7 (58) 6.0 (78) 9.7 (115) 6.6 (51) 8.6 (72) 8.0 (58) 8.3 (67)

17.4 (110) 8.3 (114) 13.1 (130) 8.7 (100) 12.4 (136) 8.8 (77) 11.1 (161) 9.1 (157) 18.0 (101) 12.0 (138) 14.6 (154) 25.4 (139) 7.8 (101) 12.8 (152) 14.7 (114) 11.3 (95) 13.5 (99) 11.8 (95)

18 24 30 41 37 24 46 15 31 27 48 90 26 28 68 26 57 33

Subgrade

wet periods. The variations in monthly rainfall outside these periods are generally less than about 60 mm. 3.2 Moisture content The maximum, minimum and mean moisture contents for the bases and subgrades of each section over the duration of the monitoring (7 individual results per section) are summarized in Table 3. The table also includes the ratio of these values to the standard optimum moisture content (AASHTO T180) for each of the layers in each road (in parentheses) and the total variation in moisture content (around the mean) over the monitoring period. 3.3 Deflection The ranges of deflection data for each road collected over the monitoring period are summarized in Table 4. These include the peak deflection, the mean and 90th percentile peak deflections of the 10 readings each before and after the monitoring points and the Middle Layer Index (MLI). The total variations in these properties over the monitoring period are also summarized. 1508

Table 4.

Summary of deflection data. Deflection (mm)

Deflection property Peak deflection

Mean peak deflection

90th Percentile peak deflection

Middle Layer Index (MLI)

*

Road No

Mean

Min

Max

Variation*

D540 D467 D2485 D404 D132 D514 D518 D646 D466 D540 D467 D2485 D404 D132 D514 D518 D646 D466 D540 D467 D2485 D404 D132 D514 D518 D646 D466 D540 D467 D2485 D404 D132 D514 D518 D646 D466

0.92 1.05 1.63 0.57 1.72 2.34 0.67 1.05 0.57 0.85 1.06 1.88 0.45 1.64 2.16 0.77 1.03 0.53 0.97 1.18 2.23 0.56 1.87 2.67 0.87 1.13 0.62 0.35 0.27 0.56 0.15 0.48 0.85 0.28 0.29 0.21

0.64 0.85 1.40 0.33 1.42 1.73 0.49 0.93 0.52 0.68 0.87 1.71 0.35 1.44 1.88 0.67 0.88 0.47 0.76 1.00 2.06 0.41 1.72 2.36 0.79 0.97 0.53 0.17 0.19 0.41 0.09 0.36 0.58 0.15 0.08 0.15

1.2 1.19 1.84 1.09 2.08 2.91 0.86 1.26 0.64 1.12 1.16 2.01 0.61 1.83 2.58 0.87 1.12 0.58 1.28 1.30 2.49 0.88 2.04 3.07 1.00 1.26 0.71 0.59 0.39 0.90 0.20 0.57 1.18 0.43 0.42 0.24

61 38 27 133 38 50 55 31 21 52 27 16 58 24 32 26 23 21 54 25 19 84 17 26 24 26 29 120 74 88 73 44 71 100 117 43

—variation about the mean during monitoring cycle (max-min/mean %).

3.4 Dynamic Cone Penetrometer data The DCP data are summarized in Table 5. These include the mean DSN800 and the DCP penetration rates (DN) of the base and subgrade of all of the monitoring data for each pavement. 4

ANALYSIS AND DISCUSSION

The data collected were analyzed in a variety of ways in an attempt to understand the influence of the moisture on the bearing capacity and structural performance of the pavements. 1509

Table 5.

Summary of DCP data. DCP parameters

Property

Road No

Mean

Min

Max

Variation*

DSN800

D540 D467 D2485 D404 D132 D514 D518 D646 D466

147 115 109 109 77 87 96 104 89

118 85 66 90 33 62 84 80 64

189 173 185 128 109 142 113 142 107

48 77 109 35 99 92 30 60 48

Mean Base strength (DN) (mm/bl)

103 D540 D467 D2485 D404 D132 D514 D518 D646 D466

5.85 4.31 7.88 3.99 6.84 3.89 5.14 5.13 7.09

Mean Subgrade (DN) (mm/bl)

Mean

66 2.54 3.49 6.87 3.13 4.25 2.43 4.06 4.00 5.16

7.70 5.49 8.56 7.00 14.74 5.74 6.17 6.99 9.78

5.6 D540 D467 D2485 D404 D132 D514 D518 D646 D466

7.1 10.5 8.9 17.0 20.2 16.5 12.1 13.9 18.9

88 46 21 97 153 85 41 58 65 72

5.5 5.0 4.9 14.5 11.0 14.4 10.4 10.4 16.1

13.9

8.0 16.8 14.9 19.7 47.0 19.7 13.9 18.9 21.6

35 112 112 31 178 32 29 61 29 71

*—variation about the mean during monitoring cycle (max-min/mean %).

Each pavement was analyzed individually and the investigations included, among other comparisons, the following, which are discussed in this paper: – Relationships between rainfall and base and subgrade moisture contents with time; – Influence of base and subgrade moisture content on peak deflection and MLI; – Relationship between base and subbase moisture contents and DSN800. 4.1 Relationships between rainfall and base and subgrade moisture contents with time Figures 2a and b show typical examples of the relationships obtained. In general the trends were poor and often opposite to those that would be expected. Typically a lag between the (high) precipitation and an increase in moisture content was observed, the lag time being anything from 2 weeks to about 3 months. In general, a similar lag time was observed for the base and the subgrade, but in a number of cases, the subgrade lag was slightly longer. Not all of the results, however, showed such trends. A number of the roads showed no definite increases in pavement layer moisture content while some even showed decreases in the moisture content after the maximum rainfall periods. No relationships could be established 1510

400 350

Rainfall (mm)

300 Rain (mm)

250

D540 467

200

2485 150

404

100 50 0 19-Apr-01

28-Jul-01

05-Nov-01

13-Feb-02

24-May-02

01-Sep-02

10-Dec-02

Date

Figure 1a. Plots of rainfall at each site versus average rainfall (Rain) for sites D540, D467, D2485 and D404.

400 350

Rainfall (mm)

300 Rain (mm)

250

132 200

514 518

150

466

100 50 0 19-Apr-01

28-Jul-01

05-Nov-01

13-Feb-02

24-May-02

01-Sep-02

10-Dec-02

Date

Figure 1b. Plots of rainfall at each site versus average rainfall (Rain) for sites D132, D514, D518 and D466 (D646 has same rainfall as D466).

between moisture changes and time lags and the conditions of the seal (i.e. cracked or uncracked) or shoulders. 4.2 Influence of base and subgrade moisture content on peak deflection and MLI The relationship between the moisture contents and peak deflection value and the MLI for two roads are shown in Figures 3a & b. It is clear that no typical values or strong trends in line with expectations were obtained. 1511

(a)

Road D540 140

20.0

18.0

100 16.0 80 14.0 60 12.0 40

Moisture content (%)

Monthly rainfall (mm)

120

10.0

20

0

8.0

19-May-01

17-Aug-01

15-Nov-01

13-Feb-02

14-May-02

12-Aug-02

Tim e Monthly rainfall

Subgrade moisture

Base moisture

(b) Road D467 120

15.0

80

10.0

60

40

Moisture content (%)

Monthly rainfall (mm)

100

20

0 19-May-01

5.0 17-Aug-01

15-Nov-01

13-Feb-02

14-May-02

12-Aug-02

Tim e Monthly rainfall

Figure 2a & b.

Subgrade moisture

Base moisture

Examples of relationships between rainfall and base and subbase moisture contents.

Different trends are evident: The peak deflections on Road D132 show a general trend to increase with increasing base and subgrade moisture content as would be expected. The MLI tends to increase as the base moisture content increases but unexpectedly shows little trend as the subgrade moisture content increases. Road D518, a generally stronger road shows a weak trend for the peak deflection to increase with increasing base and subgrade moisture content, but the MLI shows little relationship with either the base or the subgrade moisture content. It should, however, be remembered that the pavement structure below 600 mm also contributes to the peak deflection: experience during this project has shown that a large proportion of the deflection originates in the subgrade but this has not been investigated in this paper. 4.3 Examples of relationships between base and subbase moisture contents and DSN800 The influence of the base and subbase moisture contents on the DCP structural number (DSN800) was investigated and typical results are shown in Figures 4a & b. 1512

(a)

Road D132 0.60

2.20

0.50

1.80

MLI

Peak deflection (mm)

2.00

1.60 0.40

1.40 1.20 1.00 8.0

9.0

10.0

11.0

12.0

0.30 13.0

Base & subgrade moisture content (%) SG/Peak defl

Base/peak defl

SG/MLI Base/MLI

(b)

0.90

0.45

0.80

0.40

0.70

0.35

0.60

0.30

0.50

0.25

0.40

0.20

0.30

0.15

0.20 6.0

8.0

10.0

12.0

MLI

Peak deflection (mm)

Road D518

0.10 14.0

Base and subgrade m oisture content (%) SG/Peak defl

Base/peak defl

SG/MLI

Base/MLI

Figure 3a & b. Examples of relationships between the moisture content in the base and subbase and the peak deflection and MLI.

Again, contradictory conclusions were manifested in some of the sections. A decrease in structural number and layer strength with increasing moisture content would typically be anticipated. This was a general trend for road D499 (Figure 4a) although the highest moisture content value for both the base and subbase did not follow this trend on Road D466. No real trend was noted for Road D132 (Figure 4b). 5

PROBLEMS OBSERVED AND LESSONS LEARNED

Although general trends were observed in the data, it was obvious that the repeatability of the measurements was not always that desired. The problems are aggravated by the need to minimize the area of road disturbed, the possible effects of sample sites on the structural performance of the road and the need to remove samples and test sites as close as possible to each other in order to cancel the effect of natural material and construction variability. Analysis of the data indicated the following problems, which should be considered in any similar project. 1513

(a)

Road D466 110.00

DSN800

100.00

90.00

80.00

70.00

60.00 10.0

11.0

12.0

13.0

14.0

15.0

16.0

17.0

18.0

19.0

20.0

Moisture content (%) Subgrade

Base

Road D132

(b)

120 100

DSN800

80 60 40 20 0 5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

14.0

Moisture content (%) Subgrade

Base

Figure 4a & b. Examples of relationships between the moisture content in the base and subbase and the DCP structural number (DSN800).

5.1 Moisture content The samples taken for moisture content determination were generally between 0.2 and 1.0 kg. For fine materials the sample sizes seemed to be adequate, but many of the materials sampled contained large particles (often between 25 and 50 mm), which biased the moisture content determination significantly, these essentially dry materials comprising a large proportion of the sample mass. It is thus imperative that larger samples are collected when the material is coarse. This can, however, be a problem when the samples are removed using a hand auger and the pavement layers are thin. The inherent variability of natural gravels is well-known and thus requires that samples be obtained as close as possible to each other. It is thus important to take more than one sample where possible. It is, however, recommended that means of determining the in situ moisture content without disturbing the layer are used for a proper result. This would entail the installation of durable and repeatable sensors, a number of which are appearing on the market. 1514

200 180 160

DSN 800

140 120 100 80 60 40 20 0 0.00

0.50

1.00

1.50

2.00

2.50

3.00

Peak deflection (mm) D646

Figure 5.

D540

D467

D2485

D404

D132

D514

D466

D518

Plot of DSN800 against Peak deflection for all roads investigated.

Experience with nuclear density probes (not undisturbed), small ceramic psychrometers and various tensiometers has proved unsatisfactory. Techniques using capacitance measurement, time domain reflectometry or fiber-optic systems should be investigated for use, but their long-term durability, repeatability and calibration still needs to be critically assessed. 5.2 Pavement deflection It is suggested that devices such as the Falling Weight Deflectometer (FWD) or possibly the lightweight FWD systems be used to assess the pavement deflection. The depth of influence of the lightweight FWD needs to be carefully assessed and compared with conventional deflection measurements. It is also not clear what effect repeated testing at the same point using an FWD has on the properties of the pavement at that point—are compaction effects accumulated or not? The use of a traditional Benkelman Beam of course allows the deflection at an exact location to be determined. 5.3 Dynamic Cone Penetrometer testing Although the DCP test is almost non-destructive, there is no doubt that the penetration and removal of the device does affect the material immediately surrounding the test point. Tests should thus be carried out at least 100 mm from each other and the test hole sealed after extraction of the tool. A single large stone can have a significant effect on the result and it is suggested that not less than two tests be carried out to get a reasonable average result. Even this may not be sufficient to account for material variability in natural gravels and only longterm averages can provide a realistic result. It would be expected that a strong relationship exists between the deflection and DSN800. Figure 5 shows the relationship obtained from all of the roads. It is clear that although the expected trend is generally observed, certain roads do not follow the trend. It is not clear at this stage whether this is the result of testing variability or the effect of deflections resulting from the subgrade beneath the 800 mm zone tested with the DCP. 5.4 Rainfall In tropical and sub-tropical areas rainfall can be highly localized with significantly different rainfalls occurring at sites only tens of meters distant from each other. It is thus important 1515

that rainfall recording stations are established as close as possible to individual sites. Acts of vandalism usually make this impracticable, and it is recommended that residents or farmers as close as possible to the site be requested to maintain rainfall records during the investigation period for the evaluation process. 6

CONCLUSIONS

During the planning of an extensive and widespread investigation into the effects of climatic factors on road pavements, a re-assessment of an existing database developed on a smaller scale was carried out. This indicated a number of problems regarding repeatability of measurements and properties which need to be overcome in order to obtain a comprehensive and accurate data base for the current project. The lessons learned are related to the problems of monitoring rainfall, pavement moisture content, deflections and structural data which are critical to such investigations. Methods for overcoming them need to be identified, proved in practice and implemented in order to ensure repeatable and comparable data are obtained for analysis. REFERENCES CSIR Transportek. 2008. WinDCP 5.01 (Software package). CSIR Built Environment, Pretoria, South Africa. Emery, SJ. 1992. The prediction of moisture content in untreated pavement layers and an application to design in southern Africa. Bulletin 20, CSIR Research Report 644 (DRTT Bulletin 20), CSIR, Pretoria. Horak, E. 1988. Aspects of deflection basin parameters used in a mechanistic rehabilitation design procedures for flexible pavements in South Africa. PhD Thesis, University of Pretoria, Pretoria, South Africa. Paige-Green, P. 1996. Recommendations on the use of marginal base course materials in low volume roads in South Africa. Research Report RR 91/201, Department of Transport, Pretoria, South Africa. Paige-Green, P. 1999. Materials for and construction of sealed low volume roads. Proc 7th International Conference on Low Volume Roads, Baton Rouge, May 1999, Vol. 2, 10–15. Paige-Green, P. & du Plessis, L. 2008. The use and interpretation of the Dynamic Cone Penetrometer (DCP) test. CSIR Built Environment, Pretoria, South Africa.

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Bearing Capacity of Roads, Railways and Airfields – Tutumluer & Al-Qadi (eds) © 2009 Taylor & Francis Group, London, ISBN 978-0-415-87199-0

Author index

Abu Abdo, A. 295, 305 Adhikari, S. 321 Affleck, R. 1019 Agrawal, S.K. 25 Ahmed, M.U. 669 Akbulut, H. 359 Akpinar, M.V. 1117 Aksnes, J. 285, 513 Al Nageim, H. 205, 225 Allou, F. 155 Al-Qadi, I.L. 1039 Álvarez Loranca, R.L. 653 Alves, A.R.D. 1133 Angelone, S.M. 275 Anochie-Boateng, J. 1029 Antunes, M.L. 503, 1231 Apeagyei, A.K. 879 Araújo, N. 125 Arellano, D. 981 Aursand, P.O. 1091 Aurstad, J. 249, 1177 Avsar, C. 65 Azevedo, A.M. 571 Bacci, R. 387 Baek, J. 1039 Bakløkk, L.J. 285 Balay, J. 1405 Baltzer, S. 443, 859 Bandara, N. 29 Barbati, S. 1493 Barbosa, Á.S. 37 Barna, L. 1019 Barrett, X. 1485 Barros, M.A.L. 37 Bayomy, F. 295, 305 Beduneau, E. 479 Bento, B.B. 37 Berge, T. 513 Berntsen, G. 819, 1177 Bilodeau, J.P. 145 Bisht, R. 669 Bonneau, D. 479 Bordelon, A. 717 Brar, H. 57

Brill, D.R. 1383 Brito, L.A.T. 3 Bryson, L.S. 1219 Büchler, S. 339 Butt, A. 237 Caldeira, L. 1311, 1331 Cao, X. 79 Cardone, F. 1493 Cardoso, R. 1291 Carlsson, H. 1125 Cavalcante, F.P. 1465 Cavalheiro, A. 197 Ceratti, J.A.P. 1393 Cetin, E. 107 Ceylan, H. 661, 869 Chai, H. 551 Chazallon, C. 155 Chehab, G. 931 Chowdhury, T. 419 Christie, D. 5 Clec’h, P. 377 Coenen, A.R. 117 Connor, B. 89 Cortez, P. 597 Cottineau, L.-M. 467 Cox, B.R. 1143 Cruz, R.T.G. 571 Cunha, J. 1303 Curry, B. 1143 da Silva Pontes Filho, I.D. 1465 Dahlhaug, J.E. 1177 Dargenton, J.-C. 459 Dawson, A.R. 3 de Carvalho Filho, C.R. 1465 de Carvalho, M.H. 37 de Medeiros Brito Cavalcante, C. 1465 De Myttenaere, O. 963 Delgado, J. 1311, 1331 Deniz, D. 1187 Dethy, B. 215 Detry, J. 215 1517

Di Benedetto, H. 377 Diefenderfer, B.K. 419, 879 Diyaljee, V. 1455 Dombrow, W. 1349 Domingos, P. 503 Dong, C. 1001 Donovan, P.R. 619 Doré, G. 145 Du Plessis, L. 1415 Dupriet, S. 479 Edil, T.B. 1011 Eide, E. 1053 Elias, M.B. 117 Emery, S.E. 543, 1475 Erlingsson, S. 1101 Fabre, C. 1405 Facas, N. 755 Fairclough, R. 409, 849 Fengchen, C. 427 Ferne, B. 409, 849 Ferreira, T. 1291 Ferri, S. 571 Fleming, P.R. 809 Fortes, R.M. 37, 137 Fortunato, E.C. 1231 Fredriksson, R. 799 Frost, M.W. 809 Furrer, R. 755 Gallego, J. 487 Garg, N. 57 Geng, L. 495, 907 Ghaboussi, J. 679 Giannakos, K. 1263 Gieselman, H.H. 45 Goh, S.W. 315 Gomes Correia, A. 125, 197, 215, 597, 1303, 1311, 1331 Gonçalves de Macêdo, J.A. 1465 Gonzalez, C. 607 Gopalakrishnan, K. 869

Graczyk, M. 1063 Graziani, A. 1493 Grazioli, M.J. 29 Grégoire, C. 215 Griffiths, D.V. 1273 Guillard, Y. 467 Guler, E. 107 Gungor, A.G. 65 Guo, E.H. 531, 1383 Gure, A. 107 Gurer, C. 359 Hachiya, Y. 269 Hakim, H. 1125 Halahmi, I. 1159 Halsted, G.E. 1445 Han, J. 1159 Hao, L. 427 Hao, P. 1169 Harasim, P. 769 Harvey, J. 1415 Hazirbaba, K. 89 He, Y. 1197 Heckel, G. 179 Heinkele, C. 467 Hejlesen, C. 859 Hoff, I. 1053 Horak, E. 543, 1475 Hornych, P. 155 Horvli, I. 1091 Hou, X. 435 Hu, S. 1197 Huang, H. 619, 1349 Huber, G. 707 Hyslip, J.P. 1341 Indraratna, B. 5 Ioannides, A. 1433 Ishikawa, T. 1207 Jakobsen, P.E. 859 Jansen, D. 789 Jersey, S. 607 Ji, Y. 897 Jia, X. 551 Johansen, R. 819 Johansen, T.H. 697 Johanson, L. 45 Jung, S.J. 305 Kamei, T. 1207 Ker, H.W. 941 Kern, J. 237 Khoury, C. 71 Khoury, N. 71

Kim, S. 869 Kohler, E. 1415 Kolisoja, P.J. 3 Korsgaard, H.C. 689, 859 Kumar, T. 931 Kvasnak, A. 1373 Kwon, J. 1321 Lalagüe, A. 1053 Lambert, J.P. 809 Langdale, P. 409 Lange, D. 1425 Larkin, A. 57 Leandri, P. 387 Lechner, B. 1243 Lee, Y.H. 941 Lees, H.M. 1283 Lenngren, C.A. 729, 799, 829, 839 Lerat, P. 1405 Lerfald, B.O. 249, 285 Leshchinsky, D. 1159 Levenberg, E. 1361 Li, D. 1341 Li, X. 435 Li, Z. 79, 1001 Lièvre, D. 459 Lin, J.D. 941 Little, D.N. 3 Liu, Y. 315 Liu, Y. 589 Liu, Y.B. 941 Liu, Y.-S. 1425 Livneh, M. 777 Loizos, A. 451, 643, 1263 Lopes, F.M. 571 Losa, M. 387 Lu, L. 1197 Ma, S. 435 Maekawa, R. 269 Mahmoud, E. 367 Maina, J.W. 543, 561, 1475 Maranha das Neves, E. 1331 Marcelino, J. 1311 Marques, R. 597 Martínez, F.O. 275 Martins, J. 1311, 1331 Masad, E. 367 Maser, K.R. 661 Mathisen, L.U. 167 Matsui, K. 561 Mazars, A. 1405 McCartney, J.S. 1143 McCleary, T. 97 1518

McDaniel, C.R. 1341 McGrath, L.A. 661 Mechowski, T. 769 Medero, G. 1273 Meehan, C.L. 745 Mehta, Y.A. 921 Menetti, N.C. 37 Merighi, J.V. 37, 137 Metzker, K. 327 Miller, B.C. 661 Miradi, M. 633 Mishra, D. 237 Molenaar, A.A.A. 259, 633 Molenaar, S. 633 Mollamahmutoglu, M. 1113 Mollenhauer, K. 327, 339, 349 Mooney, M. 755 Morian, D.A. 931, 1433 Mork, H. 521 Motumah, L. 1415 Muraya, P.M. 259 Muriel, K.M. 921 Muzet, V. 467 Nantung, T.E. 897 Nazarian, S. 367 Nener-Plante, D.J. 397 Neves, J.M.C. 503, 1133 Nielsen, R. 305 Nimbalkar, S. 5 Nunez, W.P. 1393 Ohnishi, Y. 1207 Olard, F. 479 Olsen, K. 689 Ozawa, Y. 561 Padilla, E. 915 Paige-Green, P. 1505 Paixão, A.M. 1231 Papavasiliou, V. 643 Parsons, R.L. 1159 Pauli, D.R. 37 Pedersen, J.P. 689 Pekcan, O. 679 Penman, J. 1321 Pérez, I. 487 Petit, C. 155 Pierre, P. 145 Plati, C. 451 Pokharel, S.K. 1159 Popovics, J.S. 1187 Powell, B. 1373 Pradhan, S. 1253

Puppala, A.J. 1253 Qian, Y. 1159 Qin, W. 581 Ramos, L.F. 1311 Refsdal, G. 819 Reis Ferreira, S.M. 197 Reiter, J. 1433 Ren, J. 1243 Renken, P. 339 Ribeiro, F.V. 37 Roesler, J.R. 717, 1079 Roque, A.J. 197 Rose, J.G. 1219 Round, N. 409 Ryerson, C. 1019 Saba, R.G. 285, 513 Sadasivam, S. 931, 1433 Sadrekarimi, J. 739 Saghafi, B. 225 Said, S.F. 1125 Sanati, G. 661 Santagata, E. 1493 Santi, M.J. 295, 305 Santos, C.R.G. 571 Saride, S. 1253 Sauber, R.W. 921 Sauzéat, C. 377 Schwartz, C.W. 951 Seignez, N. 479 Sekine, E. 1207 Sert, T. 1117 Seyyedi, S. 739 Shekharan, R.A. 419 Sheng, Y. 589 Shoop, S. 1019 Siekmeier, J. 45 Simonin, J.-M. 459, 467

Sinhal, R. 849 Siraj, N. 921 Sitharam, T.G. 1253 Songgen, W. 707 Stark, T.D. 981 Stoffels, S.M. 931, 1433 Straube, E. 789 Stubstad, R.N. 689 Su, K. 269 Sun, L. 269 Suzuki, C.Y. 571 Svanekil, A. 1053 Sybilski, D. 769 Taddesse, E. 521 Tan, Y. 1073 Tarefder, R.A. 669 Tehrani, F.S. 745 Teixeira, P.F. 1291 Terrosi Axerio, A. 387 Theisen, K.M. 1393 Titi, H.H. 117 Toledano, M. 487 Tran, N. 1373 Turner, P. 1373 Tutumluer, E. 237, 619, 679, 1029, 1187, 1349

Walker, B. 543 Wang, D. 1079 Wang, H. 1169 Wang, L. 589 Wang, M.C. 581 Wang, X. 581, 973, 1073 Wang, Z. 581 Weaver, T. 305 Wells, R. 1485 Wells, T. 1485 Wen, H. 1011 West, R. 1373 White, D.J. 45 White, G.W. 889 Wistuba, M. 327, 339, 349 Wood, C.M. 1143 Woodward, P.K. 1273 Xiang, R. 1243 Yan, Z. 551 Yeh, L. 1433 Yesuf, G.Y. 697 Yildiz, A. 359 Yilmaz, Y. 65, 1113 Yiqiu, T. 427 You, Z. 315, 321 Young, C. 1143 Yufeng, B. 707

Uthus, N.S. 249 van Bijsterveld, W.T. 653 van de Ven, M.F.C. 259, 633 Van Geem, C. 963 Vaslestad, J. 697 Vennapusa, P.K.R. 45 Victorino, D.R. 1393 Visulios, P. 205

1519

Zejiao, D. 427 Zhang, K. 1169 Zhang, L. 973 Zhang, X. 1073 Zheng, Y. 551 Zhong, Y. 495, 907 Zofka, A. 397 Zohrabi, M. 991 Zou, J. 79